ux research framework

UX Research Process: A Step-By-Step Framework

11 min read

What is the UX research process? Why is it important? What are its stages?

These are only some of the questions that the article tackles. It also outlines a 9-step guide on how to conduct UX research for product managers and UX designers.

Let’s dive in!

• The UX research process is a sequence of steps to collect and analyze data on user interactions with the product to better understand their needs and preferences .
• It’s essential to build user-friendly products that satisfy their needs and offer a positive customer experience . It also helps teams empathize with users and foster customer-centric organizational cultures.
• The UX research process consists of 4 main stages, Discovery , Exploring, Testing, and Listening, which follow the development process and during which it becomes increasingly more specific.
• Each UX research project should start with goal setting and formulating research questions. In other words, decide what problem you want to solve.
• Next, choose the research audience. That’s whose problems you want to solve,
• Based on goals and audience, select a range of research techniques, like surveys , interviews, or user behavior tracking .
• To recruit research participants, reach out to your existing users or tap into the pool of participants that your analytics tool may offer.
• Talking of tools … choosing the right ones for your project is the next step. You may need a solution to collect feedback, track product usage , and create wireframes and prototypes .
• The next step involves data analysis. This includes data from your analytics tools (e.g. trends or funnel analysis ), customer feedback, or session recordings.
• Having extracted insights from the data, share them with other teams and key stakeholders to sync your efforts and ensure alignment with business goals.
• Improving UX may require a major redesign . However, you can achieve a lot with onboarding UI patterns that guide users through the product and help them achieve their goals.
• After implementing changes, test their impact and iterate to further enhance the design.
• Want to see how Userpilot can help UX researchers? Book the demo!

What is the UX research process?

The UX research process is a methodical sequence of steps that helps product teams understand user needs , behaviors, and preferences .

UX research uses different research methods like user behavior analysis and feedback to validate ideas and solutions in real-life conditions.

Why is an effective user research process crucial?

An effective UX research process is essential for several reasons.

First, you can’t build a product that meets user expectations if you don’t understand their needs, behaviors, and motivations.

Second, UX research provides valuable insights that can guide product design, ensuring that the final product is user-friendly and intuitive to use. This often translates into higher user satisfaction and retention .

Moreover, user research can identify potential obstacles and pain points and enables the design team to address these issues proactively.

Finally, it teaches teams to look at the product design process through their eyes, and so it fosters a customer-centric design culture within the organization,

Overall, UX research is the foundation for designing and building a successful and competitive product in the market.

What are the 4 phases of the UX project process?

The 4 main stages of UX research are Discovery, Exploring, Testing, and Listening.

Let’s have a closer look at each of them and the user research methods that you can use for them.

Discovery phase

The aim of the discovery phase is to give you a general understanding of user needs and the context in which you’re building the product. It enables you to find out what you don’t know and provides a focus for the rest of the research process.

Common discovery techniques include:

• Field studies
• Diary studies
• User interviews
• Stakeholder interviews
• Requirements and constraints gathering

Exploring phase

In the exploring phase, you try to gain a better understanding of user problems and the scope of the design process. During this stage, teams brainstorm different design approaches and test early-stage ideas.

Techniques that can help you during the Exploring phase include:

• Competitive analysis
• Design review
• Persona building
• Task analysis
• Journey mapping
• Prototype feedback and testing (clickable or paper prototypes)
• User stories
• Card sorting

Testing phase

The testing phase involves more granular tests and experiments to ensure that the design in development is intuitive and easy to use for users with different needs and expectations.

What research methods can you use during this phase?

• Qualitative usability testing (in-person or remote)
• Benchmark testing
• Accessibility evaluation

Listening phase

The purpose of the listening phase is to collect insights on how well the product is satisfying existing user problems. It also enables teams to discover new opportunities to further enhance the product.

During listening, teams use a range of qualitative and quantitative methods, like:

• Product analytics reviews
• Search-log analysis
• Usability-bug reviews
• Frequently-asked-questions (FAQ) reviews

9 steps for conducting UX research to gain valuable insights

With the theory covered, let’s look at how to conduct user research, step-by-step.

1. Define the objectives for your research project

Start by setting the goals for the research project.

For example, your objective may be to find out why users drop off in the user journey and identify ways to retain them. Or you could look for improvements to the onboarding process to help users adopt the features that are relevant to their goals.

Having clear goals will give the project the necessary focus, help you align your team, choose the right research methods, allocate resources efficiently, and recruit the right users.

2. Identify the target audience to be researched

If you’re in SaaS, your user base is not likely to be homogenous. This means that not all of your users will necessarily face the same challenges or pain points. Consequently, they may not be able to provide the insights you’re after.

How do you choose the right target audience then?

Use your product analytics tools or customer feedback to identify the relevant segments or user cohorts.

For example, if you see users dropping off at a particular stage of the funnel , group them together and look for common characteristics. This could be users from a specific demographic group or with a particular job role. Zero in on those.

3. Select the right UX research methods

We have briefly touched on research methods earlier. Let’s have a closer look at a few common ones that you can use at multiple stages of the project.

User experience surveys

User surveys are one of the most popular research methods.

There are a few good reasons for that.

First, they’re easy to run at scale. You can easily trigger them inside the app or deliver them online to thousands of users at once.

Second, they allow you to collect both quantitative and qualitative data . It’s a common practice to start surveys with a closed-ended question and follow up with an open-ended one.

For example, you could start by asking users to rate how easy it is to perform a task or use a feature on a Likert scale, and then justify their response in the next one.

In this way, you’ll be able to gauge what user sentiment is and understand why they’re feeling like that.

Finally, you can target specific user segments with your surveys to ensure the validity of your research.

User interviews/focus groups

User interviews and focus groups are even more effective for collecting qualitative feedback from your users. That’s because you can follow up on user responses in real time and further explore the ideas that they bring up.

That’s if you have the right interviewing skills. Users are often unable to articulate their reasons clearly or simply don’t know why they act in a particular way.

For example, if you ask users what criteria contribute to a good user experience, they may not be able to say. However, if you ask them to tell you about the last time they had a great user experience and what made it stand out, you may get more actionable insights from them.

To reap the benefits that user interviews offer, prepare carefully, for example using a template like the one below. In this way, you will make sure you use the interview time well.

User behavior data

As all user interactions with SaaS products are digital, they’re easy to track.

You can collect data on literally every user click , tap, scroll, or hover. Apart from individual user actions, you can also bundle them up into custom events, and track them as one.

Such data is invaluable for UX researchers as it is objective and can help you identify patterns in user behavior that you may need to address.

For example, you can analyze feature usage data for particular user segments to identify the features that churned users don’t use. You can then drill down into their usage patterns to understand why they don’t use them.

Usability testing

The aim of usability tests is to determine how easy it is to use the product.

You can do this by giving users a task to complete and watching how they get on with it.

Let’s imagine you’re testing a new onboarding checklist.

You give it to users to complete and offer a reward for completing it as an incentive. Then you could record how they go about finishing the tasks and analyze it for insights.

Popular usability testing techniques are:

• Guerilla testing – you ‘ambush’ users in a public place, like a cafe, and ask them to experiment with the product
• Five-second test – you show the user a part of the product, like a feature, for 5 seconds and then interview them to see if they could understand the purpose of the feature, how they felt about its design or what was their general impression of the product or brand.
• First-click testing – a technique that evaluates how intuitive the product is: do they know where to click first when they need to complete a task?
• Eye tracking – by tracking the visual interactions with the page or product dashboard , you can test different layouts and designs for distractions that prevent users from finding the right features or UI elements.

4. Recruit participants for gathering research findings

If you’ve got an existing product, you can recruit testers from your user base.

Just target the specific user segment with a modal and invite them to take part in an experiment. You can also reach out to users who took part in your fake door tests and give them an opportunity to play around with the feature.

For brand-new products, you can recruit participants via tools like Hotjar. The application gives you access to a pool of 200k+ users from different backgrounds.

5. Choose a tool for conducting user research

Based on the research method you’ve chosen, pick the right tool for your study.

Here are a few options worth considering:

• Miro, Adobe XD, Webflow, and Figma for wireframing and prototyping
• Hotjar, and Userpilot for analytics
• Optimizely and Userpilot for experimentation
• Typeform, Userpilot, and SurveyMonkey for feedback collection

When choosing the tool, consider its own UX design and how easy it is to use. Also, pay attention to their integrations so that you can easily embed them in your workflow.

6. Analyze the research data to gather insights

How you analyze collected data during your research sessions depends on your goals.

Let’s look at a few common types of analysis and the insights they can offer.

Trend analysis

Trend analysis involves visualizing and analyzing changes in a metric over a period of time.

What other insights can trend analysis offer to UX researchers?

• Trend analysis can help you identify shifts or changes in user behavior over time, allowing them to adapt designs and interfaces to better match evolving user preferences.
• You can track adoption rates of specific features to understand what aspects of the product are gaining traction with users.
• By tracking trends in user satisfaction scores or feedback, you can gauge the success of design changes or product updates.
• Trend analysis can reveal if usability metrics like task completion rates are improving or declining so that you can tweak the UI accordingly.

User feedback analysis

As mentioned, customer feedback is invaluable when it comes to understanding user behaviors and their preferences.

How do you do it efficiently?

Quantitative analysis is not a problem. If your tool doesn’t offer a dashboard with key metrics, you can fairly easily analyze and visualize the data for trends in a spreadsheet.

Qualitative analysis is a bit more challenging. Or at least it used to be until recently.

Thanks to AI, you can now analyze huge numbers of open-ended user responses for trends and patterns. Many feedback solutions , like Userpilot, also allow you to tag and group them to facilitate analysis.

Funnel analysis

Funnel analysis looks into user conversions at the main touchpoints and milestones in the user journey.

For example, you could track how users progress from signup to conversion to paid customers, or from visiting your e-commerce site to making a purchase.

It’s an intuitive technique that allows even non-technical teams to identify bottlenecks that prevent users from progressing or slow them down.

It’s enough to look at the chart to spot the stages where users experience friction because that’s where they drop off. If you can’t see this straight away, a quick look at how long it takes users to convert will reveal the friction points.

Session recordings

Session recordings are an excellent tool for in-depth analysis of user interactions with UI elements on the page.

As the name suggests, you use software like Truestory, Hotjar, or Heap to record everything that the user does on the screen.

Thanks to that, you can identify usability issues in the design. For example, users may not be able to find a feature that’s relevant to their use case, rage-click on an unclickable element, or don’t scroll far enough to access crucial information.

7. Share research insights with key stakeholders

Sharing your user experience research findings with stakeholders is an important part of the process.

For starters, it improves their ability to make informed decisions about product features, design changes, and the overall product strategy.

Moreover, sharing UX research results helps you bridge the gap between the design team and the key decision-makers and ensure that design decisions are aligned with business goals.

Finally, it creates a shared understanding between all teams involved in the product development process and improves collaboration.

8. Implement findings and optimize the user experience

There’s no point in conducting UX research if you don’t act on the insights!

How do you implement them?

As always, it depends on the nature of the problem.

Let’s imagine your users struggle to find the right features in the menu because it’s too cluttered. A simple solution would be to simplify the menu and personalize it for users with different user cases using data from welcome surveys.

Another example:

If users keep getting stuck on a particular task, you could trigger contextual UI patterns , like tooltips or hotspots, to guide them through.

9. Iterate and improve key performance metrics

When you test the UX design changes before rolling them out for all users, you increase the chances that they will move the needle in the right direction.

However, it doesn’t mean things can’t be better.

As users engage with the design, keep tracking their behavior, collecting feedback, and interviewing to identify further areas for optimization.

Then, implement the changes, and test again.

Rinse and repeat.

UX research process can help you make your product more intuitive and inclusive for users. By responding to their pain points and challenges and catering to their needs, you also boost their satisfaction and loyalty. This translates into better business performance.

If you’d like to see how Userpilot can help you with UX research, book the demo!

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UX design research methods

Effective user experience design is intuitive, accessible, and engaging. But how do you design a delightful experience that meets your target audience’s needs? Conducting user experience research gives you a glimpse inside your users’ heads, so you can understand what they care about and the challenges they face.

In this article, Figma Designer Advocate Ana Boyer weighs in on:

• What user experience research is, and why your team needs it
• Different types of UX research that support product development
• UX design research methods made easier with Figma

What is user experience research?

User experience research helps design teams identify areas of opportunity to improve user interfaces and enhance the overall user experience. According to Ana, UX research can reveal insights about target users across all phases of product development—from strategy and planning to product launch and post-launch improvements. A robust UX research framework includes both quantitative and qualitative research.

Quantitative research

Using information gathered from larger sample sizes, quantitative research yields concrete numerical data that reveals what users are doing. Researchers run statistical analyses and review analytics to gain insights into user behavior. For example, Ana says, “you might try tracking the number of times users clicked a CTA button on a newly designed web page, compared to an old version."

Qualitative research

For qualitative research, researchers collect subjective and descriptive feedback directly from users, tapping into users’ personal feelings and experiences with a product or design.  "Qualitative research gives you a more thorough explanation of why someone is doing something in the context of a flow,” Ana says.

User-centered design research often covers two types of qualitative research: attitudinal and behavioral. Attitudinal research examines users’ self-reported beliefs and perceptions related to a user experience, while behavioral research focuses on observing first-hand what users do with a product.

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3 benefits of user experience research

According to Ana, with UX research you can:

• Validate your design. "You can learn whether or not your design is hitting project goals and your users are able to accomplish a task—for example, ordering an item from your platform.”
• Put your users front and center. UX research uncovers what users want and need, so you can deliver a product that delights customers.
• Save time and resources. Doing user research and testing early and often allows you to make smaller adjustments quickly and easily. That way, Ana says, “you can take a more iterative approach to design—without having to backtrack and redo your entire UX design.”

How to conduct  UX research

Most common UX research methodologies break down into these essential activities:

• Observe how users act and react . This not only includes clicks and scrolling onscreen, but also their body language and facial expressions. Careful observation helps you understand how users normally perform a task, what interactions users pick up easily or enjoy, where they get stuck in a flow, and more.
• Empathize with your users . To create a useful and usable product, you need to consider how users' context influences them as they interact with your design.
• Analyze information to surface common themes. “Tagging key user responses helps you pinpoint what needs the most work and refinement to improve the user experience," Ana advises

When to use key UX research methods—at a glance

Given all the UX research methods you can use for  product development, when is each most useful? Ana offers these pro tips.

• User personas help you understand your core users in the early stages of development. “If you don’t know who you’re building for, then the time you invest in building and creating something will be wasted,” Ana explains. FigJam’s user persona template will help you get the ball rolling.
• Interviews gather in-depth information directly from users to test your ideas, so you can lower the risk of building a product that misses the target. FigJam’s user interview template will help you lay the groundwork.
• Card sorting invites users to show you what they think is the most intuitive way to organize high-level information in your design. Try FigJam’s card-sorting tool to shape your product’s information architecture.
• Task analysis studies users as they use your site or app to complete tasks, or jobs to be done. Use it to validate your design, and ensure users can quickly and easily accomplish their goals. Get started with FigJam’s jobs to be done template .
• Eye tracking analyzes where users look, when, and how long as they interact with your product.
• Surveys indicate how useful and usable your design is. Surveys  can provide useful insights at any phase of product development, pinpointing where users are struggling with an interface, and revealing user sentiment about a product’s colors, fonts, and overall design.

Launch & post-launch

• A/B testing shows which version or iteration of a webpage, app screen, or CTA button performs better with your users.
• Analytics track KPIs like time spent on page, bounce rate, number of clicks on key CTAs, and more to see what’s working—and what isn’t. Analytics may also reveal useful insights about your users, including location, device usage, age, and gender.
• Usability bug testing identifies and helps fix usability issues that affect your product’s quality and ease of use. “Teams struggle to invest the time and process in doing this, but it can have a huge impact on quality,” Ana says.
• Diaries captured in writing or on video track users’ thoughts and impressions over a certain time period. This self-reporting approach reveals how a product fits into and enhances users’ daily lives.

Kick off user experience research with Figma

No matter where you are in the product development process, FigJam’s research plan template can help you define your research goals. Figma’s research and design templates help you conduct research with user interviews , user personas , card sorting , and Sprig study integration .

With the insights gained from your research, you're ready to design, develop, and prototype engaging user experiences. Use Figma’s UX design tool to:

• Give and receive instant feedback on designs or prototypes—and enjoy real-time collaboration with your team. Figma's Maze integration makes testing prototypes easy.
• Set up design libraries to quickly launch user research projects and improve UX design.
• Easily share assets between Figma and FigJam to help keep your projects moving forward.

To jumpstart your UX research, browse inspiring UX research resources shared by the Figma community .

Now you're ready to roll with UX research!

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[1] https://www.nngroup.com/articles/which-ux-research-methods/

[2] https://www.uxbooth.com/articles/complete-beginners-guide-to-design-research/

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UX design frameworks: Types and use cases for each

UX designers must be prepared to adapt to new policies in the design world by constantly evolving. Despite the continuous changes, we should avoid jumping from trend to trend too carelessly.

Design frameworks exist to aid in restructuring the overall design process, and many have been around for years. These frameworks are time-tested — why not learn them so you can turn to these principles when you need a strong foundation for your design decisions?

What are UX design frameworks?

User-centered design frameworks, agile frameworks, design thinking frameworks, lean ux frameworks, atomic design frameworks, component-based design frameworks, material design frameworks, how to choose the proper framework for your project, tips for implementing and integrating ux design frameworks effectively, examples of successful ux design projects using different frameworks.

A UI/UX framework is a guide that allows designers to make and scale successful designs. Frameworks serve as guiding principles from which designers can draw inspiration. Besides driving designers to make the right design choices, they also explore user interactions with design. Frameworks were designed to allow both physical and digital products to be designed effectively.

A UX design framework provides a framework for organizing your thoughts as a designer. It assists you in ensuring that you are considering all of the critical factors when designing your product. A good UX design framework will assist you in developing designs that are both functional and visually appealing to users.

A clear and concise framework to work within is one of the most important aspects of any user experience design. This enables designers to share a common understanding of a project’s goals and objectives, ensuring everyone on the team is on the same page. A UX design framework can also assist in keeping designs on track and ensuring that they meet the needs and expectations of the users. There are numerous frameworks available, but they all share some common characteristics.

As you must have heard countless times, the design process is not rigid or a fixed law. Designers and design organizations can pick frameworks that work well for them and combine two frameworks as long as it allows them to solve their design problems.

Examples of UX design frameworks

A user-centered design framework is centered on the users. You can create solutions that make users happy by developing empathy and understanding of their needs.

As a designer, you must meet product requirements and business goals; create usable, valuable products; and improve the overall user experience. This framework focuses on that last point, arguing that focusing on the user helps your team meet business goals and create valuable products.

Adopting a user-centered design framework involves focusing on who will use the product, which tasks they must complete, how we can make the process seamless, where they will use this product, which needs are being addressed, and so on. The user-centered framework has four steps:

• Understand : this step allows you to conduct research and learn how your product is received by users. You would spend time conducting qualitative user interviews, understanding user needs, and conducting competitive analysis if you were designing a new product
• Specify : this step allows you to specify the user’s problem, what needs to be solved, and how to prioritize based on resources. After that, you can move on to developing your problem statement
• Design : you would concentrate on solutions to the user’s problems. You could design user flows, rough sketches, wireframes, mockup screens, and prototypes
• Evaluate : this step determines whether or not you have solved the user’s problems. The product should then be evaluated with real users; gathering as much feedback as possible through usability studies and user interviews is critical

UCD usually takes a long time. Conducting user interviews, usability testing, and design iterations can all lengthen project timelines and increase costs, particularly for projects with limited resources or tight deadlines. Even when using a user-centered approach, designers’ biases can have an impact on design decisions made throughout the process.

This framework has the advantage of actively involving users throughout the design process, which increases the likelihood of producing products and services that meet their expectations. The needs and preferences of users are central to the UCD process. Designers can create interfaces and experiences that are intuitive, efficient, and enjoyable for users by understanding their behaviors, goals, and pain points.

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Agile methodology is a strategic process adopted mainly by software teams, and new product development teams are beginning to buy into it to manage complexity. It combines two common product development strategies: Agile methodology and design thinking.

Agile software development is an iterative and incremental approach that delivers working software in short, frequent iterations. In contrast, design thinking is a problem-solving approach that centers the design process on the user. Together, they both foster cross-functional collaboration and continuous iteration.

Some advantages of this model include:

• It helps teams be adaptive and responsive to change by breaking down their projects into small increments of work
• Combining Agile development and design thinking can be advantageous because it allows teams to iterate quickly, validate assumptions, and continuously refine their product or solution based on user feedback

This combination indicates both efficient development and a user-centric approach to design. The disadvantages associated with this framework can be a conflict of interest, considering that Agile and design thinking methods have different timelines for deliverables. Also, there can be complexity in the learning curve as both designers and developers have to learn new frameworks.

If we didn’t discuss design thinking, we’d be missing the backbone of the UI/UX field. It is one of the most crucial frameworks for developing functional, usable, and customer-focused goods and services.

This framework has the advantage of actively involving users in the design process. This strengthens the designers’ ability to track user needs and understand their problems.

Most UX frameworks and workflows are built on the principles of design thinking, and every UX designer worldwide learns this framework when they study UX design.

The design thinking process is an iterative, user-focused framework with five stages:

• Empathize : find out the problem through research; this would help you develop empathy for your users
• Define : determine the problem you want to solve and define it for your team and stakeholders
• Ideate : develop possible solutions to users’ problems through sketches and wireframes
• Prototype : create prototypes. These are mockups of what the original product should look like
• Test : test your prototypes with users and stakeholders

Lean UX advocates creating only the features needed to test and validate assumptions. This approach helps to avoid wasting time and resources on features that aren’t necessary and instead focuses on delivering value quickly. This framework is based on developing hypotheses about user behavior, needs, or solutions and then designing experiments to validate or disprove those hypotheses.

As a designer, you can learn through data-driven insights and adjust the design as needed. Throughout the design process, Lean UX emphasizes ongoing user research and testing. It encourages designers to consult with users early and often to gain insights and validate assumptions. Lean UX emphasizes achieving desired outcomes and measuring success based on key metrics and user behavior rather than focusing solely on delivering specific design outputs.

The advantages of this framework are that it is very data-driven, user-focused, and fast to deliver, but this can also have a shortcoming. Because Lean UX is iterative and experimental, it can take time to predict project timelines and outcomes. This can be difficult for teams or organizations that rely on strict deadlines or budgets.

Atomic design is a mental model that helps us think of our user interfaces as a complete unit and a collection of parts simultaneously. Begin by designing atoms and work up to templates and pages while keeping the building principle in mind. It’s always a good idea to start small.

Atomic design is simple to use. Once we’ve done the above, all that remains is for us to combine it and work with it. It is always beneficial to begin by mapping out the foundational elements, i.e., atoms, and then building your system around them. Atomic design is a methodology comprised of five distinct stages that work together to create more deliberate and hierarchical interface design systems.

The five stages of Atomic design are as follows:

• Atoms : atoms are the smallest and most indivisible components, such as buttons, inputs, or icons
• Molecules : these are atomic combinations that form functional units such as a search bar or a navigation menu
• Organisms : organisms are molecule groups that collaborate to create more complex components, such as a header or a sidebar
• Templates : high-level groupings of organisms used to create specific page or layout structures
• Pages : template instances with actual content populating them

Atomic design encourages the development of modular and reusable components, allowing designers and developers to efficiently build interfaces by assembling predesigned atoms and molecules. This increases consistency and decreases redundancy in design and development efforts.

A downside to this is that managing an Atomic design-based design system can take time, especially as the number of components and their variations grows. Careful documentation, versioning, and governance are required to ensure consistency and avoid inconsistencies or duplication.

Component-based design is a web design approach that begins with creating components suitable for your content to create a library of reusable content blocks that will always stay in style.

Designers have embraced open web technology and standards in recent years, and we have prioritized reusability in our work. This is accomplished by putting in place a component-based framework.

Component-based design involves creating a system from predefined components and given requirements. Building systems from components is essential in any engineering discipline.

The component-based page structure enables your marketing and communications teams to format their content in a very flexible and elegant manner that is specific to the content. When presenting a wide range of content, page templates tend to be more rigid and limiting — every case study is set up and structured the same way, every industry page is structured the same way, and so on.

A component-based system is far more adaptable. Any desired layout or component can be implemented on any page to ensure that the content shines through. Component-based design frameworks are methodologies or approaches that focus on designing and building user interfaces using modular components.

These frameworks encourage the reuse of predesigned, self-contained components to create consistent, scalable, and efficient user interfaces. Component-based design frameworks make the development process more manageable by separating interfaces into reusable building blocks that can be easily assembled and combined to create complex user interfaces. Designers can create style sheets or follow design systems with predesigned components.

Here are some existing examples of component-based design frameworks for developers:

• React is a well-known JavaScript library for creating user interfaces. It follows a component-based architecture where UI elements can be broken into reusable components
• Vue.js enables developers to create reusable components with custom logic, styles, and templates. Vue offers a scalable, flexible architecture for developing interactive and modular user interfaces
• Angular: Angular is a JavaScript framework with a component-based architecture. It allows for the creation of reusable components. Angular provides a solid framework for creating large-scale applications with reusable user interface components
• Web Components: A set of web platform APIs that allow developers to create reusable UI components using standard web technologies such as HTML, CSS, and JavaScript

Component-based design frameworks encourage the development of reusable components that can be used in multiple projects. This results in less redundancy and a more consistent design. Also, by leveraging prebuilt components, developers can accelerate the development process.

This framework’s initial setup and configuration are disadvantageous. Using a component-based framework might require additional initial configuration and setup steps. This includes the time-consuming tasks of installing dependencies, configuring build tools, and establishing project structures.

Another disadvantage is performance overload. A performance overhead may be associated with rendering and managing many parts, depending on how components are implemented and used. Careful optimization and performance profiling may be required to address any performance issues.

Google’s Material Design is a design system and visual language. It offers a set of guidelines, principles, and components for developing consistent and visually appealing user interfaces across multiple platforms and devices. Material Design aims to emulate the behavior and appearance of physical materials to create a tangible, tactile, and intuitive user experience.

These are some Material Design elements to consider:

• Material Design is inspired by the physical world, employing a paper and ink metaphor to create a sense of depth, hierarchy, and realistic motion in digital space. Light, shadow, and movement convey interaction and provide visual cues
• Material Design employs a vibrant, bold color palette to convey meaning, establish hierarchy, and evoke emotion
• Material is a design system created by Google to help teams build high-quality digital experiences for Android, iOS, Flutter, and the web

A disadvantage of this framework is that, due to the strict adherence to Material Design guidelines, the level of customization and uniqueness in the interface design may be limited. Predefined styles and components may be restrictive for projects requiring a highly customized or distinctive visual identity.

Also, Material Design was created for Android applications and has spread to other platforms. While adaptable to other operating systems, Material Design interfaces may have a more substantial visual association with Android, which may or may not align with the desired platform aesthetics.

The main advantage is the use of bold colors, typography, and visual hierarchy in Material Design. The emphasis on material-inspired motion and animations enhances the user experience by adding depth and interactivity. It also includes inbuilt elements and design patterns that allow designers and developers to create interfaces more quickly. The availability of ready-to-use components reduces UI development time and effort.

Choosing a framework requires understanding the problem’s complexity, people, resources, and the organization’s culture. Knowing the proper framework to use sets you on a path to success.

Here are a few things to consider while selecting a framework:

• Prepare the groundwork. The first tip is to research your company’s requirements. Learn more about the project’s goals and objectives, problem complexity, and organizational structure. There is no standard approach to choosing a design system framework
• You must consider your design constraints and your team’s skills, preferences, and workflows. It makes no sense to use a full-stack framework if all you need are routing capabilities. Choose a framework that is appropriate for the situation at hand rather than something familiar

Other key steps are to evaluate usability, performance, and aesthetics:

• The framework’s usability involves its ease of use and learnability as well as the clarity and comprehensiveness of its documentation and support
• The framework’s aesthetics include its design, style, and ability to match your brand identity and vision
• The framework’s performance includes speed, dependability, loading time, responsiveness, SEO clarity, and the comprehensiveness of its documentation and support

Careful planning, coordination, and attention to critical considerations are required to implement and integrate UX design frameworks. Here are some tips that can help you:

• Understand your needs : Begin by learning about your project’s requirements, goals, and constraints. Assess the suitability of various UX design frameworks based on project scope, team size, project timeline, and desired outcomes
• Conduct research and training : Before implementing a UX design framework, thoroughly research its principles, methodologies, and best practices. Provide your team members with adequate training and resources to ensure they are familiar with the chosen framework and its implementation process
• Establish clear guidelines and standards : Create clear guidelines and standards for using the UX design framework. Create defined documentation on the framework for building
• Create a design system : Design systems are essential to putting UX design frameworks into action. Create a centralized design system containing all design elements, guidelines, and assets. This serves as a centralized source of truth and promotes consistency in design across projects
• Work across disciplines : UX design frameworks necessitate collaboration among designers, developers, and other stakeholders. Encourage cross-functional cooperation and a shared understanding of the framework’s principles and processes. Establish channels of communication and collaboration throughout the design and development phases
• Begin small and iterate : Gradually introduce the UX design framework, beginning with smaller projects or components. This allows you to learn from the process and make changes. Collect feedback from team members and stakeholders to improve implementation

These examples show how various companies have used frameworks and design systems to deliver successful, user-centric UX design projects. Each framework has distinct features and capabilities, allowing organizations to design innovative and engaging user interfaces tailored to their specific requirements.

Google Material Design

Material UI is a popular React component library that adheres to Google’s Material Design principles. It provides a wide range of prebuilt UI components and the tools developers need to implement the Material Design aesthetic. Many successful projects have used Material UI to create visually appealing and use -friendly experiences, such as redesigning the Gmail interface.

Salesforce Lightning Design System

Salesforce, a leading customer relationship management platform, launched the Salesforce Lightning Design System . It is built with web components and includes a library of reusable components and design patterns. Thanks to the design system, which also allows for customization, Salesforce has maintained a consistent user experience across its suite of products.

IBM design language

IBM’s Carbon Design System incorporates an Atomic design framework. Carbon provides extensive guidelines, components, and patterns that adhere to the atomic structure. It enables IBM teams to design consistent and scalable user interfaces for their enterprise software products.

Funding is essential to implementing UX frameworks; UX projects require research and testing. The incorporation of these frameworks into design processes has the potential to accelerate innovation. Organizations can unlock the potential for streamlined workflows, improved collaboration, and the delivery of exceptional user experiences by embracing UX frameworks. Finally, the proper UX framework enables teams to create products and interfaces that meet user expectations and drive business success in an ever-changing digital landscape. Why not talk with your team about the framework you use?

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The Complete Guide to UX Research Methods

UX research provides invaluable insight into product users and what they need and value. Not only will research reduce the risk of a miscalculated guess, it will uncover new opportunities for innovation.

By Miklos Philips

Miklos is a UX designer, product design strategist, author, and speaker with more than 18 years of experience in the design field.

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“Empathy is at the heart of design. Without the understanding of what others see, feel, and experience, design is a pointless task.” —Tim Brown, CEO of the innovation and design firm IDEO

User experience (UX) design is the process of designing products that are useful, easy to use, and a pleasure to engage. It’s about enhancing the entire experience people have while interacting with a product and making sure they find value, satisfaction, and delight. If a mountain peak represents that goal, employing various types of UX research is the path UX designers use to get to the top of the mountain.

User experience research is one of the most misunderstood yet critical steps in UX design. Sometimes treated as an afterthought or an unaffordable luxury, UX research, and user testing should inform every design decision.

Every product, service, or user interface designers create in the safety and comfort of their workplaces has to survive and prosper in the real world. Countless people will engage our creations in an unpredictable environment over which designers have no control. UX research is the key to grounding ideas in reality and improving the odds of success, but research can be a scary word. It may sound like money we don’t have, time we can’t spare, and expertise we have to seek.

In order to do UX research effectively—to get a clear picture of what users think and why they do what they do—e.g., to “walk a mile in the user’s shoes” as a favorite UX maxim goes, it is essential that user experience designers and product teams conduct user research often and regularly. Contingent upon time, resources, and budget, the deeper they can dive the better.

What Is UX Research?

There is a long, comprehensive list of UX design research methods employed by user researchers , but at its center is the user and how they think and behave —their needs and motivations. Typically, UX research does this through observation techniques, task analysis, and other feedback methodologies.

There are two main types of user research: quantitative (statistics: can be calculated and computed; focuses on numbers and mathematical calculations) and qualitative (insights: concerned with descriptions, which can be observed but cannot be computed).

Quantitative research is primarily exploratory research and is used to quantify the problem by way of generating numerical data or data that can be transformed into usable statistics. Some common data collection methods include various forms of surveys – online surveys , paper surveys , mobile surveys and kiosk surveys , longitudinal studies, website interceptors, online polls, and systematic observations.

This user research method may also include analytics, such as Google Analytics .

Google Analytics is part of a suite of interconnected tools that help interpret data on your site’s visitors including Data Studio , a powerful data-visualization tool, and Google Optimize, for running and analyzing dynamic A/B testing.

Quantitative data from analytics platforms should ideally be balanced with qualitative insights gathered from other UX testing methods , such as focus groups or usability testing. The analytical data will show patterns that may be useful for deciding what assumptions to test further.

Qualitative user research is a direct assessment of behavior based on observation. It’s about understanding people’s beliefs and practices on their terms. It can involve several different methods including contextual observation, ethnographic studies, interviews, field studies, and moderated usability tests.

Jakob Nielsen of the Nielsen Norman Group feels that in the case of UX research, it is better to emphasize insights (qualitative research) and that although quant has some advantages, qualitative research breaks down complicated information so it’s easy to understand, and overall delivers better results more cost effectively—in other words, it is much cheaper to find and fix problems during the design phase before you start to build. Often the most important information is not quantifiable, and he goes on to suggest that “quantitative studies are often too narrow to be useful and are sometimes directly misleading.”

Not everything that can be counted counts, and not everything that counts can be counted. William Bruce Cameron

Design research is not typical of traditional science with ethnography being its closest equivalent—effective usability is contextual and depends on a broad understanding of human behavior if it is going to work.

Nevertheless, the types of user research you can or should perform will depend on the type of site, system or app you are developing, your timeline, and your environment.

Top UX Research Methods and When to Use Them

Here are some examples of the types of user research performed at each phase of a project.

Card Sorting : Allows users to group and sort a site’s information into a logical structure that will typically drive navigation and the site’s information architecture. This helps ensure that the site structure matches the way users think.

Contextual Interviews : Enables the observation of users in their natural environment, giving you a better understanding of the way users work.

First Click Testing : A testing method focused on navigation, which can be performed on a functioning website, a prototype, or a wireframe.

Focus Groups : Moderated discussion with a group of users, allowing insight into user attitudes, ideas, and desires.

Heuristic Evaluation/Expert Review : A group of usability experts evaluating a website against a list of established guidelines .

Interviews : One-on-one discussions with users show how a particular user works. They enable you to get detailed information about a user’s attitudes, desires, and experiences.

Parallel Design : A design methodology that involves several designers pursuing the same effort simultaneously but independently, with the intention to combine the best aspects of each for the ultimate solution.

Personas : The creation of a representative user based on available data and user interviews. Though the personal details of the persona may be fictional, the information used to create the user type is not.

Prototyping : Allows the design team to explore ideas before implementing them by creating a mock-up of the site. A prototype can range from a paper mock-up to interactive HTML pages.

Surveys : A series of questions asked to multiple users of your website that help you learn about the people who visit your site.

System Usability Scale (SUS) : SUS is a technology-independent ten-item scale for subjective evaluation of the usability.

Task Analysis : Involves learning about user goals, including what users want to do on your website, and helps you understand the tasks that users will perform on your site.

Usability Testing : Identifies user frustrations and problems with a site through one-on-one sessions where a “real-life” user performs tasks on the site being studied.

Use Cases : Provide a description of how users use a particular feature of your website. They provide a detailed look at how users interact with the site, including the steps users take to accomplish each task.

You can do user research at all stages or whatever stage you are in currently. However, the Nielsen Norman Group advises that most of it be done during the earlier phases when it will have the biggest impact. They also suggest it’s a good idea to save some of your budget for additional research that may become necessary (or helpful) later in the project.

Here is a diagram listing recommended options that can be done as a project moves through the design stages. The process will vary, and may only include a few things on the list during each phase. The most frequently used methods are shown in bold.

Reasons for Doing UX Research

Here are three great reasons for doing user research :

To create a product that is truly relevant to users

• If you don’t have a clear understanding of your users and their mental models, you have no way of knowing whether your design will be relevant. A design that is not relevant to its target audience will never be a success.

To create a product that is easy and pleasurable to use

• A favorite quote from Steve Jobs: “ If the user is having a problem, it’s our problem .” If your user experience is not optimal, chances are that people will move on to another product.

To have the return on investment (ROI) of user experience design validated and be able to show:

• An improvement in performance and credibility
• Increased exposure and sales—growth in customer base
• A reduced burden on resources—more efficient work processes

Aside from the reasons mentioned above, doing user research gives insight into which features to prioritize, and in general, helps develop clarity around a project.

What Results Can I Expect from UX Research?

In the words of Mike Kuniaysky, user research is “ the process of understanding the impact of design on an audience. ”

User research has been essential to the success of behemoths like USAA and Amazon ; Joe Gebbia, CEO of Airbnb is an enthusiastic proponent, testifying that its implementation helped turn things around for the company when it was floundering as an early startup.

Some of the results generated through UX research confirm that improving the usability of a site or app will:

• Increase conversion rates
• Increase sign-ups
• Increase NPS (net promoter score)
• Increase customer satisfaction
• Increase purchase rates
• Boost loyalty to the brand
• Reduce customer service calls

Additionally, and aside from benefiting the overall user experience, the integration of UX research into the development process can:

• Minimize development time
• Reduce production costs
• Uncover valuable insights about your audience
• Give an in-depth view into users’ mental models, pain points, and goals

User research is at the core of every exceptional user experience. As the name suggests, UX is subjective—the experience that a person goes through while using a product. Therefore, it is necessary to understand the needs and goals of potential users, the context, and their tasks which are unique for each product. By selecting appropriate UX research methods and applying them rigorously, designers can shape a product’s design and can come up with products that serve both customers and businesses more effectively.

Further Reading on the Toptal Blog:

• How to Conduct Effective UX Research: A Guide
• The Value of User Research
• UX Research Methods and the Path to User Empathy
• Design Talks: Research in Action with UX Researcher Caitria O'Neill
• Swipe Right: 3 Ways to Boost Safety in Dating App Design
• How to Avoid 5 Types of Cognitive Bias in User Research

Understanding the basics

How do you do user research in ux.

UX research includes two main types: quantitative (statistical data) and qualitative (insights that can be observed but not computed), done through observation techniques, task analysis, and other feedback methodologies. The UX research methods used depend on the type of site, system, or app being developed.

What are UX methods?

There is a long list of methods employed by user research, but at its center is the user and how they think, behave—their needs and motivations. Typically, UX research does this through observation techniques, task analysis, and other UX methodologies.

What is the best research methodology for user experience design?

The type of UX methodology depends on the type of site, system or app being developed, its timeline, and environment. There are 2 main types: quantitative (statistics) and qualitative (insights).

What does a UX researcher do?

A user researcher removes the need for false assumptions and guesswork by using observation techniques, task analysis, and other feedback methodologies to understand a user’s motivation, behavior, and needs.

Why is UX research important?

UX research will help create a product that is relevant to users and is easy and pleasurable to use while boosting a product’s ROI. Aside from these reasons, user research gives insight into which features to prioritize, and in general, helps develop clarity around a project.

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Miklos Philips

London, United Kingdom

Member since May 20, 2016

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UX Design Research Guide

A strategic framework with 20 methods..

Joshua Hoering

Why Conduct UX Design Research?

UX (user experience) design research is the systematic discourse of studying target users and their needs. Each method provides a different approach resulting in data and insights. UX researchers must be capable of performing a diverse set of methods to strategically discover problems and opportunities throughout the design process.

Conducting UX Design Research earlier in the design process and integrating the insights will ensure time and resources are utilized efficiently. Continuing to perform UX Design Research throughout the design process will increase the value of the final design, meaning the return on investment (ROI) of UX Design Research is significantly high.

Overall, UX Design Research ensures designs are…

1. effective at meeting the needs of users. 2. ethically sound. 3. delightful for users. 4. efficient for users. 5. optimized for profitability.

Strategic Framework

While each method is unique and produces different insights, a strategic framework is always be followed to ensure the process is ethical and understood by all stakeholders. As with all research on human subjects, it’s important the research process is conducted with integrity.

Step 1: Research Matrix Creating a research matrix helps researchers determine which research method to use and why.¹ Step 2: Research Protocol Communicating a research protocol ensures the research process for is transparent and thorough for all stakeholders.² Step 3: Performing Research Collecting qualitative and quantitative data is prioritized at this stage and it’s important researchers are prepared to record anything, even the unexpected.³ Step 4: Data Analysis Analyzing collected data results in useful insights that can be clearly articulated to everyone in the design team.⁴ Step 5: Deliverables At the end of the process, useful deliverables (such as user journey maps or use case diagrams) are provided to stakeholders.

20 Methods of UX Design Research

Each research method is understood by whether it is producing qualitative or quantitative data, whether it studies attitudes or behaviors of participants, and whether the interaction between participants of the research and the design is natural or scripted .

• A/B Testing Testing designs by randomly assigning groups of users targeted assignments when interacting with parts of the design and measuring the results of user behavior. Quantitative Data | Behaviors of Users | Natural Interactions
• Card Sorting Analyzing how users organize individual labels written on notecards according to criteria that either make sense to users or into groups assigned by researchers. Quantitative & Qualitative Data | Attitudes of Users | No Interactions
• Clickstream Analysis Process of collecting, analyzing, and reporting aggregate data about which pages a website visitor visits on a site or digital product and in what order. Quantitative Data | Behaviors of Users | Natural Interactions
• Concept Testing Process of gathering user feedback of a developed idea or prototype. Quantiative & Qualitative Data | Attitudes of Users | Natural & Scripted Interactions
• Customer Feedback Feedback from a sample of users who answer open-ended and/or close-ended questions who volunteered to provide feedback through a survey discovered through a link. Quantitative & Qualitative Data | Attitudes of Users | Natural Interactions
• Desirability Studies Participants select different qualities of a prototype or potential aspects of a design to discover user preferences. Quantiative & Qualitative Data | Attitudes of Users | Natural & Scripted Interactions
• Diary/Camera Studies Participants are provided a mechanism (a diary or camera) to record and/or describe aspects of their lives relevant to a design in a longitudinal period of time. Quantitative & Qualitative Data | Attitudes of Users | Natural Interactions
• Email Surveys Participants receive a survey from an email that records responses to written questions. Quantitative & Qualitative Data | Attitudes of Users | No Interactions
• Ethnographic Field Studies Researchers meet with and participants in their natural environment where participants encounter the design being studied. Qualitative Data | Attitudes & Behaviors of Users | Natural Interactions
• Eyetracking The use of an eye-tracking device to measure where participants look as they perform tasks or interact with a design. Quantitative & Qualitative Data | Behaviors of Users | Natural & Scripted Interactions
• Focus Groups Small groups of participants are guided through a discussion about a set of topics so participants can provide verbal and written feedback through discussion and/or exercises. Qualitative Data | Attitudes of Users | Natural & Scripted Interactions
• Intercept Surveys Participants respond to a survey that is triggered during the use of a design. Quantitative Data | Attitudes of Users | Natural Interactions
• Interviews Participants meet one-on-one with researchers to discuss in-depth what the participant thinks about aspects of a design. Qualitative Data | Attitudes of Users | No Interactions
• Moderated Remote Usability Studies Participants use tools such as screen-sharing software or a camera during the use of a design. Quantitative & Qualitative Data | Behaviors of Users | Scripted Interactions
• Participatory Design Participants are given design elements or creative materials to construct their ideal experience to expresses what matters most to them. Qualitative Data | Attitudes of Users | Natural & Scripted Interactions
• True-Intent Studies Type of intercept survey that targets a live visitor to ask them questions once they are finished using a design to understand who is using the design and whether the design was successful for them. Quantitative Data | Behaviors of Users | Natural Interactions
• Unmoderated Remote Panel Studies A panel of trained participants have video recorded and data collection software installed on their own personal device to record their use of a design while participants verbalize their thinking aloud. Quantitative & Qualitative Data | Behaviors of Users | Scripted Interactions
• Unmoderated UX Studies A software application provides instructions to participants, records their actions, and asks participants predetermined follow-up questions. Quantitative & Qualitative Data | Behaviors of Users | Scripted Interactions
• Usability Benchmarking Evaluation of a design’s user experience with metrics that compare its performance to a meaningful standard. Quantitative & Qualitative Data | Behaviors of Users | Scripted or Natural Interactions
• Usability-Lab Studies Researchers meet one-on-one with participants to study how participants perform tasks with a design. Qualitative Data | Behaviors of Users | Scripted Interactions

7 Key Takeaways

• Researchers need to understand why they are conducting research in the first place for the design’s users and the company producing the design.
• Have a clear process for deciding which research methods to use and when to use them.
• Articulate a clear and transparent protocol for conducting research prior to conducting it so all stakeholders are aware and informed.
• Gather rich data in a sensitive manner.
• Present data analysis and insights so they can be understood by anyone and everyone.
• Build a library of research methods.
• Understand how each research method’s purpose, whether it collects qualitative or quantitative data, whether it studies attitudes or behaviors of participants, and whether interactions are scripted or natural.
• Cameli, Matteo et al. “How to Write a Research Protocol: Tips and Tricks.” Journal of cardiovascular echography vol. 28,3 (2018): 151–153. doi:10.4103/jcecho.jcecho_41_18.
• Choguill, Charles L. “The research design matrix: A tool for development planning research studies”. Habitat International. vol 29, Issue 4. (2005): 615–626. ISSN 0197–3975. https://www.sciencedirect.com/science/article/pii/S019739750500038X.
• LeCompte, Margaret D., and Judith Preissle Goetz. “Ethnographic Data Collection in Evaluation Research.” Educational Evaluation and Policy Analysis, vol. 4, no. 3, Sept. 1982, pp. 387–400, doi:10.3102/01623737004003387.
• Perer, Adam, and Ben Shneiderman. “Integrating statistics and visualization: case studies of gaining clarity during exploratory data analysis.” Proceedings of the SIGCHI Conference on Human Factors in computing systems. 2008.

Written by Joshua Hoering

Professor of design in Chicago. www.joshuahoering.com

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Use These Frameworks To Make Your UX Research Results Stick

A diagram is worth a thousand bullet points.

When we present UX research, we want people to talk about it. We want our insights to stay relevant in our organizations for a long time. And we want our peers to share and build on those insights.

One powerful way to get there is to use a visual framework.

Consider Maslow’s Hierarchy of Needs. This 1940s motivational theory, famously presented as a five-tier pyramid, has achieved pop-culture status. Few of us have actually read Maslow’s paper (I haven’t). But his five-tier chart of human needs is one of the most recognizable depictions of a psychological theory ever published.

When I started as a UX Researcher at Microsoft, I delivered each study’s results as a list of bullets on PowerPoint slides. And after each presentation, my manager urged me to deliver those results as frameworks instead.

He’d seen visual frameworks help his team present research and make an impression. Information shown in a framework travels further and has more impact than research presented strictly as text on a slide.

It took a few years for his advice to click. I wasn’t sure how to do it or where to start. I had learned to communicate through words, not images. But now I almost always present at least one key message of every research study as a framework.

If you haven’t tried frameworks in your own research presentations, here are three you can start with.

Research framework 1: Quartered box

This is just a rectangle split into four sections, but it’s a surprisingly flexible framework I often fall back to.

When to use

I rely on this four-section chart a lot at Indeed, where we study a diverse user base. I commonly segment users by multiple attitudes and behaviors to point out specific subsets of users we may want to pay special attention to.

Example: In one study, I discovered that employers who had stricter hiring criteria and managed higher volumes of job applications appeared most enthusiastic about a feature we had built. In contrast, employers with less-strict hiring criteria and fewer job applications appeared the least enthusiastic.

A framework like this helps readers see the contrast between groups and makes your research easier to understand. It also provides a natural launching board into what our teams often really want to know about each group: the why.

Research framework 2: Nested circles

Even a few simple concentric circles can make your research more memorable.

I sometimes discover multiple segments or behaviors in my research. This framework is handy when these segments aren’t mutually exclusive but instead build on each other.

Example: In a study of how job seekers responded to a lack of jobs during the pandemic, I saw three common approaches to job searching. Job seekers who expanded into the second (or third) approach didn’t abandon the first approach. They considered these less-desirable alternatives only as a matter of necessity.

You can present these in a single slide. Or you can add each circle, one at a time, as you introduce a segment and explain how they relate to each other.

Research framework 3: Pyramid

I’ve adapted the pyramid framework many times in my research. It’s useful when our work captures a prioritized hierarchy of needs.

That’s something we often do as user researchers: identify needs and evaluate how important those needs are relative to others. We use that information to help establish or alter the priorities of a product team.

The pyramid framework is valuable for presenting both user and organizational priorities:

Your users’ priorities. You might discover you misinterpreted initial assumptions about what your user base values.

Example: I once conducted mixed-method research on a community of independent website makers. We learned that this community’s highest-order priorities were the opposite of what we imagined: these website makers often valued their personal growth and work-life balance much more than their raw income.

Your organization’s priorities. Based on findings, you might make a hierarchy of features a product needs to succeed. The pyramid can help you answer which are essential and which are not.

Example: I once led an international research trip to interview current and prospective users of a newly-released analytics product. From these interviews, we identified a hierarchy of team priorities for success in that international market.

You can easily create your own pyramid in Google Slides (Insert > Diagram > Process), and in PowerPoint (Insert > SmartArt > Pyramid).

Give it a try!

Through frameworks, my research travels further and stays relevant longer. I hope these examples inspire you to try frameworks for a future project.

Once you’ve started using frameworks, you may find yourself coming up with ideas for more. And that’s where the real fun begins.

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UX Design Frameworks – What Are The Most Useful Ones?

UX design framework is a valuable tool that helps us create user-centered, consistent, and efficient digital experiences. It’s not a one-size-fits-all solution but rather a flexible guideline that can be adapted to different projects.

Many organizations and startups adopt one or more UX design frameworks to deliver successful projects. Design teams use these frameworks to guide decision-making and solve problems.

Key takeaways:

• A UX design framework is a structured approach that designers follow to create consistent and user-friendly digital products, websites, or applications.
• It helps designers make informed design decisions while ensuring a cohesive and enjoyable user experience.
• Design frameworks can help with project delivery, like Lean UX or Double Diamond, or achieve outcomes for a specific feature by applying the Fogg Behavior Model or Hooked Model.

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What is a Design Framework?

A design framework is a set of tools, workflows, protocols, and processes for design projects. Design frameworks provide teams with a systematic approach to solving problems and delivering projects.

Design frameworks help with onboarding new hires or handing over responsibilities. By following a familiar, structured process, new team members know where they are in the design process and how to carry the project to completion.

In large organizations, with multiple cross-functional teams working on the same product, a design framework ensures teams communicate and collaborate to maintain the highest quality and consistency in workflow and delivery.

Design frameworks guide teams rather than force everyone into a specific way of thinking and working. Instead of telling team members what to do, the framework provides a systematic path to finding a solution.

Why do we need design frameworks?

 Some of the core benefits of using a design framework include:

• Consistency : Ensures a uniform and recognizable design across different parts of a project.
• Efficiency : Saves time by providing established patterns of work.
• User-Centricity : Prioritizes the needs and expectations of users , leading to better products.
• Collaboration : Facilitates communication among design teams, developers, and stakeholders .
• Productivity : Teams deliver projects methodically and consistently.

9 Examples of UX Design Frameworks

UX design frameworks provide structure to the design process and product development. There are several frameworks design teams use, depending on the outcome they want to achieve.

User-Centered Design (UCD)

User-Centered Design (UCD for short) is a UX desig frameworksn that places the needs, preferences, and behaviors of the end-users at the forefront of the design process . The central premise of UCD is to create products, services, or systems that are intuitive, efficient, and enjoyable for the people who will use them.

Some key principles and aspects of User-Centered Design include:

• Empathy for Users: The design process begins with a deep understanding of the user. Designers conduct user research to gain insights into users’ needs, goals, pain points , and behaviors.
• Focus on Usability: Usability is a critical aspect of UCD. Designers aim to make products easy to learn and use, minimizing user errors and frustration. This involves creating clear navigation, logical
• Prototyping and Testing: Designers create prototypes early in the design process. These prototypes are tested with real users to identify issues before design handoff .
• Continuous Improvement: Even after the product is launched, this approach encourages ongoing monitoring and refinement based on user feedback and changing needs.

In essence, User-Centered Design is a holistic approach that aims to create products that not only meet business goals but, more importantly, meet the needs and expectations of the people who use them, resulting in a better user experience.

Design Thinking Process

The design thinking process is the basis for most UX frameworks and workflows. It’s the framework every UX designer learns when studying UX design worldwide.

The design thinking process is an iterative user-centered framework with five stages:

• Empathize: Discover what your users need
• Define: Determine the problem you want to solve
• Ideate: Develop possible solutions to users’ problems
• Prototype: Create prototypes
• Test: Test your prototypes with users & stakeholders

Read more about those five stages of the design thinking process .

Double Diamond

The double diamond is an outcomes-based design framework favored for design innovation. The framework encourages collaboration and creative thinking where team members develop and iterate on ideas.

There are two stages (diamonds) and four steps to the double diamond framework:

Stage One – Preparation:

• Discover: UX teams conduct UX research to understand user needs and problems. Researchers must engage with end-users through interviews and usability studies to empathize and find issues.
• Define: Teams use insights from discovery to define and prioritize the problems their project must solve.

Stage Two – Prototyping & Testing:

• Develop: UX teams use various ideation and prototyping methods to develop ideas and solutions to users’ problems.
• Deliver: Teams must test their solutions with end-users and stakeholders. They reject solutions that don’t work and iterate to improve those that do.

Nir Eyal developed the Hook Model as a UX design framework to “build habit-forming products.” The framework encourages designers to approach these projects ethically while delivering value to customers.

The Hook Model is a four-stage process, including:

• Trigger: Understand what external or internal triggers users to take a specific actions
• Action: Define the action you want users to take
• Variable reward: An unexpected, positive reward users get for completing an action
• Investment: Provide users with an incentive to invest more time in the product, thus repeating the cycle

 Further reading: 

• Hooked: How to Build Habit-Forming Products
• UX Design Psychology Tricks for Design Excellence

Lean UX is a collaborative UX design framework that prioritizes outcomes over deliverables. Designers must use data rather than assumptions to drive decisions. This methodology delivers leaner, problem-solving products because it eliminates features where there is no need.

There are three stages to the Lean UX framework:

• Think: Outcomes, assumptions, user research, ideate, mental models, sketches, storyboards
• Make: Wireframes, UI design, mockups, prototypes (minimum viable products), value propositions, hypotheses
• Check: Analyze data & analytics, usability testing, stakeholder and user feedback

Further reading: 

• Lean UX: Expert Tips to Maximize Efficiency in UX
• Lean UX vs. Agile UX – is there a difference?

Agile UX is a design framework created to align with agile software development. Like agile software development, agile UX has 12 guiding principles .

• Customer experience (CX)
• Harnessing technological and social change
• Development timelines that make good use of resources
• Adaptive collaboration
• Building projects around motivated individuals
• Effective communication across team channels
• Working applications and high-quality UX as success benchmarks
• Sustainable development
• Technical excellence is relative
• Cross-functional teams
• Adaptable, flexible teams

Further reading:

• How Agile Environments Revolutionize a Design Team’s Workflow?
• The 12 Realistic Principles of Agile UX
• Agile vs. Scrum vs. Kanban: Which Project Management Methodology is Right For Your Team?

BASIC Framework

BASIC UX is “a framework for usable products.” The relatively new design framework provides interaction design guidelines for modern product development.

The BASIC acronym follows five principles:

• A = Accessibility
• S = Simplicity
• I = Intuitiveness
• C = Consistency

Within each principle are a series of questions designers must ask themselves to achieve a successful outcome. 

• Is the visual design aesthetically pleasing?
• Does it follow the style guide ?
• Are high-quality visuals used?
• Is it properly aligned?

Accessibility:

• Can ‘everyone’ use it?
• Does it comply with standards?
• Is it cross-platform compatible?

Simplicity:

• Does it reduce the user’s workload?
• Is it free of clutter and repetitive text?
• Is its functionality necessary?

Intuitiveness:

• Is the functionality clear?
• Can the user achieve their goal with little or no initial instructions?
• Can the user easily repeat the task without further instruction?
• Can the user predict the outcome/output?

Consistency:

• Does the product reuse existing UI patterns ?
• Are the design language, images, and branding consistent with the design system?
• Does it appear in the right place at the right time?
• Does the product perform consistently every time?

Organizations can adapt these questions or add their own to ensure they’re relevant to the product and its users.

Further reading: BASIC UX – A Framework for Usable Products .

The UX Honeycomb

Peter Morville’s UX Honeycomb is a holistic UX design framework listing seven principles. These seven principles guide each design decision to deliver high-quality products and user experiences.

The UX Honeycomb’s seven principles include:

• Useful: Products must serve users and solve their problems
• Usable: Designs must be intuitive and easy to use
• Desirable: The user interface design must be aesthetically pleasing and deliver a positive user experience
• Findable: Search, and navigation must be clear and obvious
• Accessible: Designs must be accessible to all users, including those with disabilities
• Credible: Users must be able to trust the product and its content
• Valuable: The final product must deliver value to users and the business

The Fogg Behavior Model

The Fogg Behavior Model , developed by B J Fogg from Standford University, suggests behavior or action is the result of three elements converging:

Like the Hooked Model, the Fogg Behavior Model helps designers build products that increase usage and engagement over time. Fogg emphasizes that “baby steps” are the best way to develop long-term behaviors.

A fantastic example many of us have experienced is any digital game. The first level is easy, giving players a sense of accomplishment, thus triggering further engagement. The game gets incrementally more challenging as players spend more time engaging with the product.

• Fogg Behavior Model
• Tiny Habits by B J Fogg

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Meaningful Testing Feedback

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• Search in Operationalising research

How to build a UX research role & practice from scratch

A UXinsight by Ori Dar (he/him)

• Operationalising research
• Research process

Becoming the first UX researcher in an organization can be challenging. In order to be successful, we need to properly define our role, and implement research practices from scratch, while understanding what to do and how to do it. The challenge becomes even bigger if that’s also your first UX research role .

In this article, I’d like to share the methodology and techniques I used in order to become the first UX researcher at my company, and how I implemented them. These tools can help you define your research role from scratch and build research processes by utilizing a research mindset that can be shared with those you work with. In the end you will find a list of the templates discussed in the article.

Apply a research mindset to your practice

As the first UX researcher, you may be wondering: Where do I start? You might be eager to run your first research project with users. Yet you might consider starting off with another research project. Apply your research mindset to define your role and share this mindset with your teams to establish the practice.

Research mindset for me includes three main things:

• Think like a researcher – challenge your assumptions, be methodical and organized
• Be aware of your initial intuition but also be critical of it
• Look for measurable proof of your ideas to help test your hypotheses

Your first UX research project: define your role

Treat this like any other research project. Taking advantage of our research mindset helps organize our goals, workflows, and desired outcomes.

Setting goals and planning ahead

Good research starts with planning and asking questions. It’s a way of inserting order into an otherwise unclear situation. And also, it’s what we do best.

• Define your goals. For me, it was to understand why am I doing this, and what value my UX research role can bring to the company. Understanding the value helps to communicate with stakeholders later on.
• Create your research plan. Start with your research questions: What are the main responsibilities of this role? Where does research fit in company workflows? How to promote user-centered and research-based deliverables? Don’t forget to outline your hypotheses.
• Consider what you’ll do next. For example, what you learn, and the findings you’ll collect can, later on, be translated into the specific job requirements and responsibilities that will help you get started as the first UX researcher.

Conducting research

While I used several methods, I would like to share two methods that, for me, provided the most valuable insights:

• Job description analysis. See what companies want, what they look for, and what skills or experience they ask for. Think broadly and try to find different companies from different domains that offer a wide range of products, both B2B and B2C. This can help see the bigger picture. I used a ‘Rainbow spreadsheet’ to organize my learnings 🌈. In it, each row represents a responsibility, skill , or requirement, and each column represents a company. This way, I ended up with a colored heatmap that highlighted key topics and recurring themes.
• In-depth interviews . Find people who you can learn from and ask them to share their experiences. What do they like or dislike, what’s hard to do vs. what’s easy to achieve, what a day in the life looks like, etc. I interviewed several UX researchers I contacted via social media to learn more about how they perceive the role, what they do, and what suggestions they have for me. It was a great experience and I learned a lot.

An unexpected outcome of my interviews was learning that I’m not alone and that everyone deals with similar issues.

Synthesizing

I placed everything I learned on the Miro board and identified the main themes that came up. These themes became my responsibilities and job description that I shared with the relevant stakeholders when I started my role. They include things such as:

• Creating diverse thinking using different research techniques
• Engage employees from all fields and on all levels by sharing research and key insights, in order to build consensus regarding our users’ voices
• Standardize a research protocol and contribute to a repository of user research tools
• Conduct research throughout all of the product phases – formative, iterative, and evaluative

Strengthen the research mindset in your teams

After defining your UX research role and aligning it with the relevant stakeholders , focus your next steps as the first UX researcher on building the practice itself. Create research workflows, enablement, and awareness.

Standardize your research process

Being the sole researcher meant I had to share knowledge and delegate responsibilities since I couldn’t be hands-on in every step of each project. This meant acting more as a research facilitator who empowers and helps others do more research more accurately .

A good starting point here is to invest in templates.

Be critical about what you find online (research mindset, remember?). Tweak it to make it your own, and act as a curator of knowledge to facilitate the right workflows. I created a Miro research template that covers all steps of the research, starting from research questions, hypotheses, choosing the appropriate methods , collecting data, and synthesizing it into insights and conclusions. It was built together with the team and we amend it according to usage and feedback.

If the steps of the research are laid out clearly, it’s easier to remember to think critically. And if the tools are right in front of us, it’s easier to use them and be more user-centered.

Align your teams around measurement goals

When we at Imperva started using the analytics tool Fullstory it created a huge spike in the amount of data we collect. In order to make sense of all of it and help the teams get aligned on their desired (user-centered) outcomes we had to organize it. To do that, I utilized Google’s HEART framework to create a predefined structure to define relevant metrics for each product in my organization, and a consistent language that everyone knows and understands.

Together with the designer, we created a dashboard for each product to track the relevant metrics for it (defined with HEART). This framework helped us organize our analytics data and create a place to track, analyze and investigate user patterns and behaviors to see how new features are accepted by our users and how they use existing ones.

Make research data accessible

Research can be done by different people on different products. This makes the data distributed and easily misplaced. Also, it’s hard to know if someone has insights on an issue close to or relevant to the one you are working on. Documentation is the way to preserve data and make it more accessible. You can document data from different perspectives:

• User feedback repository . I created the repository based on Tomer Sharon’s ‘Nuggets’ framework . A nugget is the atomic unit of research insight and consists of evidence, observation, and tags . This repository helped us group all the data together in a single place and made it easy to find user feedback that is either product-related or specific research question related. I built the repository using an Airtable template and adjusted it according to our needs. It helps prioritize research by surfacing issues that arise often. It also makes it easy to find previous insights that can be related to the current project at hand.

• Research projects repository. The second angle of documentation is documenting the projects themselves. Having a single place that stores all research projects increases visibility of research and also allows others to see if previous research can be applicable to the one they are currently conducting. The repository I created is a simple spreadsheet that includes the research topic, when it was done, key questions and findings, and links to the relevant assets such as findings, presentations, recordings, and more.

Final thoughts

By utilizing a research mindset I was able to manage being the first UX researcher at my company and handle the new responsibilities. It allowed me to increase the amount of research done, and be an advocate for user research. Being critical and methodical is what helps us perform our research role better and offer the best outcomes we can. Here are a few things that helped me during my journey:

• Work together. While doing it alone is completely possible, if you can, sync and brainstorm with others. Ask for help and feedback. Ask the community. This will help you focus your ideas and make sure they are the right ones for your problems.
• Start doing. Even if you’re not 100% sure, start doing and iterate as you go. It’s a lot easier to fine-tune something we have than to stare at a blank page.
• Start small. Work towards creating a simple habit that becomes automatic as time goes by and that helps increase the research mindset.

Here is an overview of the templates shared in this article that I created or modified with my team:

• Rainbow spreadsheet (in Google Sheets) for job description analysis
• Research planning and executing (in Miro)
• User feedback repository (in Airtable)
• Research projects repository (in Google Sheets)

Images in the article created with the help of Moshe Sabach and Sher Agami.

Cover photo by Silvia Brazzoduro on Unsplash

Get latest articles and templates from UXinsight in our monthly updates.

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About the author

Ori Dar (he/him)

Ori is a UX researcher and designer. Coming from the field of psychology, with an M.Sc. in cognitive psychology and human factors engineering, Ori believes that anything can be researched, including research itself.

Ori designed experiences for different products for a wide range of domains including banks, retail, cyber security, and more. For the past three years, Ori has been building and advancing the UX research function at Imperva. By working alongside a team of 10 amazing designers, he aims to make all design decisions more user-based.

https://www.linkedin.com/in/ori-dar/

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How to write a ux research plan that actually works: 7-step tutorial, saviour egbe, august 29, 2023.

A UX research plan is like a map that will help you navigate the complexity of running a research project. It will help you define your goals, choose the right methods, and collect the data you need to make informed design decisions.

But UX research plans don't have to be boring. In fact, they can be quite funny. For example, one UX researcher I know has a section in his plan called " The Things That Make Me Cry ." This is where he lists all the things that he's learned about his users that make him sad, such as the fact that they often have to deal with frustrating interfaces or unhelpful customer service.

But the primary use of a research plan of course is to make  sure that your research is effective. So, while it’s helpful to have a sense of humor, you also need to be serious about your research.

In this article, we'll consider:

• What a UX research plan is and why it's important
• How to create a UX research plan 
• An example of a well-structured UX research plan and
• A template for a UX research plan you can use to get started

So, whether you're a UX newbie or a seasoned pro, read on for everything you need to know about UX research plans!

What is a UX Research Plan?

A UX research plan is a document that outlines the goals, methods, and timeline for your research. It's a roadmap that will help you stay on track and ensure that your research is productive.

A good UX research plan should include the following:

• A clear statement of the research goals: What do you hope to learn from your research? What are the specific questions you're trying to answer?
• A description of the target audience: Who are the people you're designing for? What are their needs and pain points?
• A selection of research methods: There are many different research methods available, so it's important to choose the ones that are right for your goals and target audience.
• A timeline and budget: How long will your research take? How much money will it cost?
• A plan for data analysis and presentation: How will you analyze your data and communicate the findings to others?

Why is a UX Research Plan Important?

A UX research plan is important for several reasons. It helps you:

• Stay focused and avoids wasting time and resources.
• Ensures that your research is relevant to the needs of your users.
• Get buy-in from stakeholders & align on the goals for the project.
• Provides a framework for organizing and analyzing your data.
• Helps you communicate the findings of your research to others.

How to Create a UX Research Plan

Creating a UX research plan is an important step in ensuring that your product or service is user-friendly and meets the needs of your target audience. Here are the essential steps to create a research plan that drives meaningful insights and successful user experiences:

Step 1: Alignment & Requirements Gathering

Research rarely will happen in a vacuum. Usually you are working with a team—product, engineering, design, for example. 

When the need for a research study arises, the first thing you want to do is meet with your team to understand the questions they're trying to answer.

Depending on how formally set up your research practice is, you may even want to supplement this step with a Research Request document where stakeholders can explain the key questions they'd like to answer, why they're important, and any constraints (budgets, timelines) they're working with.

Step 2: Define Your Goals

Once you've gathered your data, the next step is to clearly define & write out your goals. What do you hope to learn from your research? What specific questions are you trying to answer?

Here are some things to consider when framing your goals:

• What are the business objectives for your product or service? Are you trying to grow active users? Or reduce churn? What should the final results of this research project help you do?
• Who are your target users? These are the people you’d like to learn more about.
• What do you want to learn about their behavior and preferences? This will help you determine your research questions. Ideally the answers to these questions should also tie to your business goals so there’s a clear line between what you’re trying to learn and what that learning will do for the company.

Once you’ve thought about and drafted the answers to these questions, make sure to follow the below steps before starting interviews:

i. Assess Internal Data and Identify Research Needs

Before you start collecting new data, take some time to assess any existing data you have. This could include analytics, customer feedback, or previous research findings. This will help you identify any gaps in your knowledge and determine what areas need to be explored further.

Sometimes you’ll find you already have the answer to your research question in-house—saving you weeks of research effort and thousands of dollars of investment!

If you’re trying to build a repository to help you do this more effectively, check out this definitive guide on research repositories .

ii. Link Research Goals to Business Objectives

It's also important to link your research goals to the business objectives of your organization. This will help you justify the time and resources that will be required for your research. By demonstrating how your research will help you achieve your business goals, you'll be more likely to get the support you need.

As a bonus, once your research is complete, you can go back and track its impact against these business goals. This will help you build a case for your own work and the research practice at your company.

As you proceed through Step 1, keep in mind that your research goals should be Specific, Measurable, Achievable, Relevant, and Time-bound (SMART). This framework will help you ensure that your goals are well-defined and actionable.

Step 3: Identify Your Target Audience & Plan a Recruiting Strategy

Knowing your audience is essential for creating a UX research plan that delivers relevant and actionable insights. In this step, we'll talk about how to define your target audience and plan a recruiting strategy for this set of users.

The target audience you’re considering this research study may overlap with your standard target users, or you may want to speak with a subset of this group.

For instance, if you’re doing a research study on why users churn, speaking to a regular active user won’t help. You’ll need to define and recruit users who can actually answer your questions well—in this case it could be “users who have churned in the last 2 weeks”.

When defining the audience for this study, think about whether your target user falls in a specific category based on one of these characteristics:

• Demographics:   This includes basic characteristics, such as age, gender, location, and occupation.
• Behaviors and habits: Are you interested in users who have or have not conducted certain actions on your product? For research on how well your Slack integration works, you may want to speak to users who have already installed it, for example.  
• Needs and use cases: Sometimes one product can have multiple use cases. For example, a transcription product could be used by researchers, or journalists, or students trying to capture their class notes. Which use case or needs are relevant to your research study?  
• Payment type: In today’s world products may have free, freemium / trial, or paid users and each of these groups may behave differently. Think about whether you need one or all of these user types as part of your research.

Now that you know who you need to reach, you also need to think about how to reach them.

Recruiting, as we all know, is a major pain point for (most) researchers. There are some ways to speed it up though.

If you’re running research for a B2C product or an easy to find B2B cohort, you may want to turn to an external recruiting software like UserInterview.com or Respondent.io. There are also local agencies to help you find more local audiences in international markets. 

If you are trying to recruit via an external paid channel like this, make sure to budget it in your research plan. These channels are very quick to set up research calls with, but they do come with an added cost.

If you’re running research with a niche B2B audience or are defining your audience based on behaviour on your product (e.g., user who churned in the last 2 weeks), you may need to use internal recruiting methods. This means reaching out to your own users via email, intercom, or via your sales / support team.

If you are recruiting existing customers, make sure to budget in the time it takes to recruit these users. It may take a few days to weeks to gather the relevant user emails and schedule calls, although paid incentives for research help this move much faster.

If you are planning to recruit your own customers, use our Ultimate Guide to Recruiting Your Users for Interviews and Usability Tests . This article has templates for outreach, incentive payment options, and many tactical tips to help you streamline internal recruiting.

Remember, the accuracy and relevance of your research findings depend on the quality of your participants. Take the time to identify and engage users who genuinely reflect your intended audience. This will help you create a research plan that generates insights that drive impactful design decisions.

Step 4: Choose Your Research Methods

Choosing the right research methods is necessary for getting the most out of your UX research plan. Before kicking off your study, make sure to review the possible ways you can answer your research question as well as any constraints you face regarding time, money, or tooling.

If you’re not sure which methods exist, read through this article on UX Research Methods . This article provides an overview of the different methods, so you can choose the ones that are right for your project. It covers everything from usability testing to card sorting, and it includes practical advice on how to conduct each UX research method effectively.

When you’re actually selecting the right method out of the available options, here are the key questions you need to ask yourself: 

• Your research goals: What do you hope to learn from your research? The methods you choose should be aligned with your specific goals. For example, if you need to deeply understand user motivations, a user interview is much better fit than a survey.
• Quantitative vs. qualitative: Do you want to collect quantitative data (numbers and statistics) or qualitative insights (in-depth understanding)? Different methods are better suited for different types of data. If you need to know the percentage of users using Zoom vs GoogleMeet, a 5-person user interview won’t get you that data but a 100 person survey with a representative sample might.
• Resources and time: How much time and money do you have to spend on your research? Some methods are more time-consuming or expensive than others. For instance, an ethnographic study where you travel to see your users is obviously more expensive and time-consuming than a 30-minute remote user interview.

By considering these factors, you can choose a combination of research methods that will help you understand your users better.

Step 5: Define your timelines & budgets

Now that you know your target audience (and therefore recruiting method) and your research methods, you can define the timelines and budgets your stakeholders care about.

• Timelines: How long will it take to conduct your research? This will depend on the methods you choose, the number of participants you need to recruit, and the amount of data you need to collect. For example, user interviews can typically be conducted within a few weeks, but usability testing can take anywhere from a few days to a few weeks, depending on the number of participants and the complexity of the product or service being tested.
• Budgets: How much money will you need to conduct your research? This will depend on the methods you choose, the number of participants you need to recruit, and the cost of data collection and analysis. For example, user interviews can be conducted for a few hundred dollars, but usability testing can cost several thousand dollars, depending on the number of participants and the complexity of the product or service being tested.

Step 6: Identify your assumptions

Sometimes without realising it, our research study comes packaged with a set of assumptions about who users are and what they want.

Before kicking off your study, it’s important to identify these assumptions in writing and align on them with your team.

For instance, if you’re running research on how to improve a Slack integration, your in-built assumptions may be:

• Users already use this integration
• It’s worth improving this integration further

Once you’ve laid out these assumptions in advance of your research, you can check them against existing data and keep them in mind when you’re reviewing your research findings.

For example, if analytics data shows that no users use your Slack integration, it may call into question the research you’re running today or change the audience you speak to about it.

Instead of speaking to existing Slack integration users, your audience may need to be companies that have Slack but have not downloaded your Slack integration.

Your research questions may also shift from “Why do you use the Slack integration?” to “Why not? ”

In general, taking a moment to review research assumptions helps you be more aware of them throughout your research study.

Step 7: Define the research questions

This is a pivotal phase in the UX research process. It's when you define the questions that will guide your data collection efforts. These questions will be your compass, directing your research toward meaningful insights that drive product improvements.

Here are some tips for crafting and structuring your research questions:

• Make sure each question is aligned with your overall research objectives. This will ensure that your findings address the core goals of your project.
• Make your questions clear, concise, and specific. Ambiguity can lead to varied interpretations and muddy insights.
• Frame your questions from the user's perspective. Use language that aligns with your target audience to ensure your questions are relatable.
• Avoid leading questions. These are questions that nudge participants towards a particular response. Aim for neutrality to get real insights.
• Use a mix of open-ended and closed-ended questions. Open-ended questions allow participants to provide detailed responses, while closed-ended questions offer predefined answer choices.
• Structure your questions logically, moving from broader inquiries to more specific ones. This will help participants to follow your thought process.
• Limit the number of questions. You want to get comprehensive insights but don't want to overwhelm participants with too many questions.
• Cover the core areas relevant to your project. This could include user pain points, needs, preferences, expectations, and perceptions.
• Pilot-test your questions with a small group of participants. Their feedback can help you to identify unclear or misleading questions.
• Make sure your questions are relevant to the research methods you will be using. For example, usability testing may focus on task-oriented questions, while interviews explore broader experiences.

Here are some examples of well-defined research questions:

1. Usability testing:

• How easily can users navigate the Looppanel account setup process?
• What challenges do users face when uploading their recorded calls to Looppanel?
• How intuitive is the process of setting up Calendar integration on Looppanel?

2. Interviews:

• Can you describe a recent experience you had with the Looppanel customer support?
• What motivated you to sign up for Looppanel for your user research needs instead of other platforms?
• In your view, how does the platform assist in taking your user interview notes effectively?

By carefully defining your research questions, you can ensure that your data collection efforts are focused and meaningful. This will help you to gather the insights you need to improve your product or service and deliver a better experience to your users.

Step 8: Align with your team

Now that you’ve thought through the basics, it's essential to get buy-in from your team and stakeholders on the final plan.

A lot may have happened between your first requirement-gathering meeting and when your plan is finalized. Take the final plan to stakeholders and make sure they are aligned:

• The research question you’re going to answer
• How your study ties to business goals
• Which users you’ll be engaging with
• Which method you’ll be using
• What your timelines look like
• What your budget looks like (if applicable)

This step is really important because if there’s a lack of alignment between you and your key stakeholder, you may end up with findings nobody is going to act on.

Example UX Research Plan

Here is an example UX research plan for improving the onboarding experience of a mobile app. Use this example as a guide to help you create your own plan!

Psst… we also have a template below that you can copy and use!

Project Title: Research study to improve onboarding experience on DuoLingo 

Business Goal: We want to increase the activation rate of new users on the app.

Project Goal(s) :

• Identify key drop-off points on the onboarding flow
• Identify why users are dropping off at these points

Target Users: People from the 15-40 age group in North America who have not used Duolingo before.

• MixPanel analytics data to identify existing drop-off points for users
• Usability testing with the think aloud protocol to understand why users are dropping off at those points

Timelines: The study will run for 4 weeks:

• Week 1: Analyzing existing analytics data & recruiting participants
• Week 2: Running usability tests
• Week 3: Analyzing results
• Week 4: Presenting findings

Budget (if applicable): Anticipated spend of $500 on recruiting.

Key Research Questions These are the research questions we’ll be gathering data on :

• At which point(s) in the onboarding process are users most likely to drop off?
• What are the common reasons users cite for discontinuing the onboarding process?
• How do users perceive the clarity of instructions during the initial setup stages?
• Are there any specific usability issues that lead users to abandon the onboarding flow?
• How do users' prior experiences with language learning apps impact their expectations of DuoLingo's onboarding?

UX Research plan template

We’ve also created a UX Research plan template you can use easily duplicate and use for your own work.

Click here to get Looppanel's UX Research Plan template.

This template contains sections for:

• Project Title
• Business Goals
• Project Goals
• Target Users
• Research Methods
• Timelines & Budgets
• Key Research Questions

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February 12, 2017 2017-02-12

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User-experience research methods are great at producing data and insights, while ongoing activities help get the right things done. Alongside R&D, ongoing UX activities can make everyone’s efforts more effective and valuable. At every stage in the design process, different UX methods can keep product-development efforts on the right track, in agreement with true user needs and not imaginary ones.

In This Article:

When to conduct user research.

One of the questions we get the most is, “When should I do user research on my project?” There are three different answers:

• Do user research at whatever stage you’re in right now . The earlier the research, the more impact the findings will have on your product, and by definition, the earliest you can do something on your current project (absent a time machine) is today.
• Do user research at all the stages . As we show below, there’s something useful to learn in every single stage of any reasonable project plan, and each research step will increase the value of your product by more than the cost of the research.
• Do most user research early in the project (when it’ll have the most impact), but conserve some budget for a smaller amount of supplementary research later in the project. This advice applies in the common case that you can’t get budget for all the research steps that would be useful.

The chart below describes UX methods and activities available in various project stages.

Each project is different, so the stages are not always neatly compartmentalized. The end of one cycle is the beginning of the next.

The important thing is not to execute a giant list of activities in rigid order, but to start somewhere and learn more and more as you go along.

When deciding where to start or what to focus on first, use some of these top UX methods. Some methods may be more appropriate than others, depending on time constraints, system maturity, type of product or service, and the current top concerns. It’s a good idea to use different or alternating methods each product cycle because they are aimed at different goals and types of insight. The chart below shows how often UX practitioners reported engaging in these methods in our survey on UX careers.

If you can do only one activity and aim to improve an existing system, do qualitative (think-aloud) usability testing , which is the most effective method to improve usability . If you are unable to test with users, analyze as much user data as you can. Data (obtained, for instance, from call logs, searches, or analytics) is not a great substitute for people, however, because data usually tells you what , but you often need to know why . So use the questions your data brings up to continue to push for usability testing.

The discovery stage is when you try to illuminate what you don’t know and better understand what people need. It’s especially important to do discovery activities before making a new product or feature, so you can find out whether it makes sense to do the project at all .

An important goal at this stage is to validate and discard assumptions, and then bring the data and insights to the team. Ideally this research should be done before effort is wasted on building the wrong things or on building things for the wrong people, but it can also be used to get back on track when you’re working with an existing product or service.

Good things to do during discovery:

• Conduct field studies and interview users : Go where the users are, watch, ask, and listen. Observe people in context interacting with the system or solving the problems you’re trying to provide solutions for.
• Run diary studies to understand your users’ information needs and behaviors.
• Interview stakeholders to gather and understand business requirements and constraints.
• Interview sales, support, and training staff. What are the most frequent problems and questions they hear from users? What are the worst problems people have? What makes people angry?
• Listen to sales and support calls. What do people ask about? What do they have problems understanding? How do the sales and support staff explain and help? What is the vocabulary mismatch between users and staff?
• Do competitive testing . Find the strengths and weaknesses in your competitors’ products. Discover what users like best.

Exploration methods are for understanding the problem space and design scope and addressing user needs appropriately.

• Compare features against competitors.
• Do design reviews.
• Use research to build user personas and write user stories.
• Analyze user tasks to find ways to save people time and effort.
• Show stakeholders the user journey and where the risky areas are for losing customers along the way. Decide together what an ideal user journey would look like.
• Explore design possibilities by imagining many different approaches, brainstorming, and testing the best ideas in order to identify best-of-breed design components to retain.
• Obtain feedback on early-stage task flows by walking through designs with stakeholders and subject-matter experts. Ask for written reactions and questions (silent brainstorming), to avoid groupthink and to enable people who might not speak up in a group to tell you what concerns them.
• Iterate designs by testing paper prototypes with target users, and then test interactive prototypes by watching people use them. Don’t gather opinions. Instead, note how well designs work to help people complete tasks and avoid errors. Let people show you where the problem areas are, then redesign and test again.
• Use card sorting to find out how people group your information, to help inform your navigation and information organization scheme.

Testing and validation methods are for checking designs during development and beyond, to make sure systems work well for the people who use them.

• Do qualitative usability testing . Test early and often with a diverse range of people, alone and in groups. Conduct an accessibility evaluation to ensure universal access.
• Ask people to self-report their interactions and any interesting incidents while using the system over time, for example with diary studies .
• Audit training classes and note the topics, questions people ask, and answers given. Test instructions and help systems.
• Talk with user groups.
• Staff social-media accounts and talk with users online. Monitor social media for kudos and complaints.
• Analyze user-forum posts. User forums are sources for important questions to address and answers that solve problems. Bring that learning back to the design and development team.
• Do benchmark testing: If you’re planning a major redesign or measuring improvement, test to determine time on task, task completion, and error rates of your current system, so you can gauge progress over time.

Listen throughout the research and design cycle to help understand existing problems and to look for new issues. Analyze gathered data and monitor incoming information for patterns and trends.

• Survey customers and prospective users.
• Monitor analytics and metrics to discover trends and anomalies and to gauge your progress.
• Analyze search queries: What do people look for and what do they call it? Search logs are often overlooked, but they contain important information.
• Make it easy to send in comments, bug reports, and questions. Analyze incoming feedback channels periodically for top usability issues and trouble areas. Look for clues about what people can’t find, their misunderstandings, and any unintended effects.
• Collect frequently asked questions and try to solve the problems they represent.
• Run booths at conferences that your customers and users attend so that they can volunteer information and talk with you directly.
• Give talks and demos: capture questions and concerns.

Ongoing and strategic activities can help you get ahead of problems and make systemic improvements.

• Find allies . It takes a coordinated effort to achieve design improvement. You’ll need collaborators and champions.
• Talk with experts . Learn from others’ successes and mistakes. Get advice from people with more experience.
• Follow ethical guidelines . The UXPA Code of Professional Conduct is a good starting point.
• Involve stakeholders . Don’t just ask for opinions; get people onboard and contributing, even in small ways. Share your findings, invite them to observe and take notes during research sessions.
• Hunt for data sources . Be a UX detective. Who has the information you need, and how can you gather it?
• Determine UX metrics. Find ways to measure how well the system is working for its users.
• Follow Tog's principles of interaction design .
• Use evidence-based design guidelines , especially when you can’t conduct your own research. Usability heuristics are high-level principles to follow.
• Design for universal access . Accessibility can’t be tacked onto the end or tested in during QA. Access is becoming a legal imperative, and expert help is available. Accessibility improvements make systems easier for everyone.
• Give users control . Provide the controls people need. Choice but not infinite choice.
• Prevent errors . Whenever an error occurs, consider how it might be eliminated through design change. What may appear to be user errors are often system-design faults. Prevent errors by understanding how they occur and design to lessen their impact.
• Improve error messages . For remaining errors, don’t just report system state. Say what happened from a user standpoint and explain what to do in terms that are easy for users to understand.
• Provide helpful defaults . Be prescriptive with the default settings, because many people expect you to make the hard choices for them. Allow users to change the ones they might need or want to change.
• Check for inconsistencies . Work-alike is important for learnability. People tend to interpret differences as meaningful, so make use of that in your design intentionally rather than introducing arbitrary differences. Adhere to the principle of least astonishment . Meet expectations instead.
• Map features to needs . User research can be tied to features to show where requirements come from. Such a mapping can help preserve design rationale for the next round or the next team.
• When designing software, ensure that installation and updating is easy . Make installation quick and unobtrusive. Allow people to control updating if they want to.
• When designing devices, plan for repair and recycling . Sustainability and reuse are more important than ever. Design for conservation.
• Avoid waste . Reduce and eliminate nonessential packaging and disposable parts. Avoid wasting people’s time, also. Streamline.
• Consider system usability in different cultural contexts . You are not your user. Plan how to ensure that your systems work for people in other countries . Translation is only part of the challenge.
• Look for perverse incentives . Perverse incentives lead to negative unintended consequences. How can people game the system or exploit it? How might you be able to address that? Consider how a malicious user might use the system in unintended ways or to harm others.
• Consider social implications . How will the system be used in groups of people, by groups of people, or against groups of people? Which problems could emerge from that group activity?
• Protect personal information . Personal information is like money. You can spend it unwisely only once. Many want to rob the bank. Plan how to keep personal information secure over time. Avoid collecting information that isn’t required, and destroy older data routinely.
• Keep data safe . Limit access to both research data and the data entrusted to the company by customers. Advocate for encryption of data at rest and secure transport. A data breach is a terrible user experience.
• Deliver both good and bad news . It’s human nature to be reluctant to tell people what they don’t want to hear, but it’s essential that UX raise the tough issues. The future of the product, or even the company, may depend on decisionmakers knowing what you know or suspect.
• Track usability over time . Use indicators such as number and types of support issues, error rates and task completion in usability testing, and customer satisfaction ratings, to show the effectiveness of design improvements.
• Include diverse users . People can be very different culturally and physically. They also have a range of abilities and language skills. Personas are not enough to prevent serious problems, so be sure your testing includes as wide a variety of people as you can.
• Track usability bugs . If usability bugs don’t have a place in the bug database, start your own database to track important issues.
• Pay attention to user sentiment . Social media is a great place for monitoring user problems, successes, frustrations, and word-of-mouth advertising. When competitors emerge, social media posts may be the first indication.
• Reduce the need for training . Training is often a workaround for difficult user interfaces, and it’s expensive. Use training and help topics to look for areas ripe for design changes.
• Communicate future directions . Customers and users depend on what they are able to do and what they know how to do with the products and services they use. Change can be good, even when disruptive, but surprise changes are often poorly received because they can break things that people are already doing. Whenever possible, ask, tell, test with, and listen to the customers and users you have. Consult with them rather than just announcing changes. Discuss major changes early, so what you hear can help you do a better job, and what they hear can help them prepare for the changes needed.
• Recruit people for future research and testing . Actively encourage people to join your pool of volunteer testers. Offer incentives for participation and make signing up easy to do via your website, your newsletter, and other points of contact.

Use this cheat-sheet to choose appropriate UX methods and activities for your projects and to get the most out of those efforts. It’s not necessary to do everything on every project, but it’s often helpful to use a mix of methods and tend to some ongoing needs during each iteration.

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What is Interaction Design?

Interaction design is an important component within the giant umbrella of user experience (UX) design . In this article, we’ll explain what interaction design is, some useful models of interaction design, as well as briefly describe what an interaction designer usually does.

A simple and useful understanding of interaction design

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Interaction design can be understood in simple (but not simplified ) terms: it is the design of the interaction between users and products. Most often when people talk about interaction design, the products tend to be software products like apps or websites. The goal of interaction design is to create products that enable the user to achieve their objective(s) in the best way possible.

If this definition sounds broad, that’s because the field is rather broad: the interaction between a user and a product often involves elements like aesthetics , motion, sound, space, and many more. And of course, each of these elements can involve even more specialised fields, like sound design for the crafting of sounds used in user interactions.

As you might already realise, there’s a huge overlap between interaction design and UX design. After all, UX design is about shaping the experience of using a product, and most part of that experience involves some interaction between the user and the product. But UX design is more than interaction design: it also involves user research (finding out who the users are in the first place), creating user personas (why, and under what conditions, would they use the product), performing user testing and usability testing, etc.

The 5 dimensions of interaction design

The 5 dimensions of interaction design(1) is a useful model to understand what interaction design involves. Gillian Crampton Smith, an interaction design academic, first introduced the concept of four dimensions of an interaction design language, to which Kevin Silver, senior interaction designer at IDEXX Laboratories, added the fifth.

Words—especially those used in interactions, like button labels—should be meaningful and simple to understand. They should communicate information to users, but not too much information to overwhelm the user.

2D: Visual representations

This concerns graphical elements like images, typography and icons that users interact with. These usually supplement the words used to communicate information to users.

3D: Physical objects or space

Through what physical objects do users interact with the product? A laptop, with a mouse or touchpad? Or a smartphone, with the user’s fingers? And within what kind of physical space does the user do so? For instance, is the user standing in a crowded train while using the app on a smartphone, or sitting on a desk in the office surfing the website? These all affect the interaction between the user and the product.

While this dimension sounds a little abstract, it mostly refers to media that changes with time (animation, videos, sounds). Motion and sounds play a crucial role in giving visual and audio feedback to users’ interactions. Also of concern is the amount of time a user spends interacting with the product: can users track their progress, or resume their interaction some time later?

5D: Behaviour

This includes the mechanism of a product: how do users perform actions on the website? How do users operate the product? In other words, it’s how the previous dimensions define the interactions of a product. It also includes the reactions—for instance emotional responses or feedback—of users and the product.

See how 5 dimensions of interaction design come together in the animation below:

Important questions interaction designers ask

How do interaction designers work with the 5 dimensions above to create meaningful interactions? To get an understanding of that, we can look at some important questions interaction designers ask when designing for users, as provided by Usability.gov(2):

What can a user do with their mouse, finger, or stylus to directly interact with the interface? This helps us define the possible user interactions with the product.

What about the appearance ( colour , shape, size, etc.) gives the user a clue about how it may function? This helps us give users clues about what behaviours are possible.

Do error messages provide a way for the user to correct the problem or explain why the error occurred? This lets us anticipate and mitigate errors.

What feedback does a user get once an action is performed? This allows us to ensure that the system provides feedback in a reasonable time after user actions.

Are the interface elements a reasonable size to interact with? Questions like this helps us think strategically about each element used in the product.

Are familiar or standard formats used? Standard elements and formats are used to simplify and enhance the learnability of a product.

So what do interaction designers do?

Well, it depends.

For instance, if the company is large enough and has huge resources, it might have separate jobs for UX designers and interaction designers. In a large design team, there might be a UX researcher , an information architect, an interaction designer, and a visual designer , for instance. But for smaller companies and teams, most of the UX design job might be done by 1-2 people, who might or might not have the title of “Interaction Designer”. In any case, here are some of the tasks interaction designers handle in their daily work:

Design strategy

This is concerned with what the goal(s) of a user are, and in turn what interactions are necessary to achieve these goals. Depending on the company, interaction designers might have to conduct user research to find out what the goals of the users are before creating a strategy that translates that into interactions.

Wireframes and prototypes

This again depends on the job description of the company, but most interaction designers are tasked to create wireframes that lay out the interactions in the product. Sometimes, interaction designers might also create interactive prototypes and/or high-fidelity prototypes that look exactly like the actual app or website.

Diving deeper into interaction design

If you’re interested to find out more about interaction design, you can read Interaction Design – brief intro by Jonas Lowgren, which is part of our Encyclopedia of Human-Computer Interaction . It provides an authoritative introduction to the field, as well as other references where you can learn more.

References and Where to Learn More

Course: Interaction Design for Usability

Read more of our engaging literature and resources on interaction design

More about What Puts the Design in Interaction Design

Questions to consider when designing for interaction: The What & Why of Usability

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UI Vs. UX: Here’s What You Need to Know

• Written by Contributing Writer
• Updated on August 27, 2024

UI (user interface) and UX (user experience) are often used interchangeably, and some job descriptions, such as those for UI/UX designers, call for skills in both areas. But although UI and UX designers work closely to ensure that users have the best possible interactions with the products they buy, these two fields have different roles to play in designing and developing new products. Here’s a look at the key differences between UI and UX design, what skills you’ll need to find work in this fast-growing and lucrative space, and how online UI/UX design courses can help you gain those.

What Are UI and UX?

User interface and user experience design and research have the same focus: creating user interfaces that make it as easy as possible to use a product, digital or otherwise. They also require similar skills: empathy, communication, and an eye for design. But UI is just one aspect of the larger goal of delivering an optimal user experience.

UI: The “Nuts and Bolts” of the User Experience

User interface design arises from a major shift in the early days of computing when computers were almost exclusively the domain of programmers and coders. At that time, users interacted with computers via the command line interface, which required knowledge of programming languages, and commands were executed through strings of code. But in the 1980s, a very different model appeared: the graphical user interface, or GUI. This interface used graphic elements, such as icons and buttons, so that users could communicate with computers without programming or coding knowledge.

The development of the GUI meant that computer interfaces had to be designed with end users in mind—ordinary people who needed tools to interact quickly and easily with their devices. With that in mind, user interface design was born, a subspecialty focused exclusively on developing the many elements that create smooth interactions with computers.

Although UI design was originally applied only to computer interfaces, today, it extends to various digital devices, including mobile apps, wearable tech, and smart appliances. The UI design process is practical and strategic, and UI designers work to create interactive elements and responsive design that make the user’s journey as easy as possible, whether that involves navigating a website, using an app, or programming a home security system.

Also Read: What is UX UI Design? A Beginner’s Guide

UX: Building the Complete User Experience

If UI is dedicated to designing the visual interface elements that create a satisfactory user experience, UX designers focus on the many ways a user interacts with a product. That includes whether users can find the right navigational tools and how they feel about their overall interaction with the product and the brand that stands behind it. UX designers focus on ways to improve a user’s journey with products of all kinds, incorporating user research about every aspect of that journey.

UX design aims to eliminate barriers to user satisfaction and find better ways to offer solutions to the problems they’re seeking to solve. In that way, UX design operates on multiple levels to create a positive experience that includes more than practical functionality.

UX researchers gather concrete data (numbers and statistics) and users’ impressions about a product using surveys, interviews, and observation of people performing specific tasks. UX designers then use this research as a guide to create products that meet users’ expectations.

UI and UX: Complementary Paths to User Satisfaction

For years, designers have debated the difference between UI and UX design, trying to find a framework for understanding their relationship. Adding to the confusion are the many job titles for professionals in the UI/UX design space, such as content designer, UI/UX designer, interaction designer, and user experience architect.

But UI design is simply one component of creating an overall user experience. For a simple analogy, think about building a house. UX design is the foundation and the four walls, while UI is the paint and furnishings that make it convenient for living.

That relationship between UX and UI design is clear in the familiar home screen of Google, with its clean interface designed to do just one thing: make it easy for anyone to search for information. The streamlined, minimal UI and uncluttered space create a UX that makes Google the go-to name for web searching, one so familiar that it’s even become a verb.

Tasks and Responsibilities: What Do UI and UX Designers Do?

Both UX and UI designers share many skills and duties, but their work takes place at different places in the product development process. In this respect, let’s dig into the difference between UI and UX design.

UI Design: Visual Elements for Easy Interactivity

Originally, UI design was applied exclusively to the graphic elements on the screens of digital devices. Today, that definition has extended to the visual design of interfaces for other devices. But, in all its forms, UI designers work on creating the visual elements that allow a user to access and navigate the properties of products ranging from laptops to smart thermostats.

UI designers aim to create a user experience so intuitive and natural that it’s hardly noticed and that gets users the outcome they want quickly and smoothly. To create those elements, UI designers need some knowledge of graphic design, such as typography, color theory, and white space. Working with the insights revealed by the “big picture” of UX research, UI designers put themselves in the place of a potential user, imagining what elements will make the product easy to use, such as placing a button in a prominent place on a webpage.

UI designers collaborate with other design team members, particularly the UX designer, if those jobs are separate. Their work begins with insights from UX research and continues as design prototypes are tested and refined. The work of UI designers centers on understanding and applying the principles of visual design to every element users will encounter when interacting with the product. That could include designing individual screens and pages for websites and apps and all the visual elements they contain, such as sliders, icons, and buttons.

Because UI designers create all the visual elements in user interfaces, their work includes developing color palettes, choosing fonts, and establishing a consistent style across all product parts. After making those decisions, the UI designer will create a mockup or wireframe to share with developers and UX designers and work with them to get to a final design.

Also Read: A 2023 Guide to UX UI Design Companies

UX Design: Putting It All Together

UX designers work with UX researchers, UI designers, and other members of the design and development teams to create products that meet user needs and expectations. UX design informs a product’s life cycle, from concept to finished product. The UX design process may also include research that reveals what users want and need in a product.

Guided by the insights of UX research, UX designers develop prototypes for testing product designs and continue to refine them through repeated trials until the best version is ready for release. UX designer responsibilities include working with UX research data, collaborating with other teams to create prototypes and models for testing, and communicating with people, including end users, developers, and other stakeholders in the organization, at all stages of the design process.

What Skills Are Required for a Career in UI/UX Design?

Whether you’re interested in becoming a UI or UX design specialist through online UI/UX training or your ideal position combines the differences between UI and UX design, you’ll need a broad combination of “soft” skills and technical knowledge to succeed. These can include:

Empathy and Imagination

UI/UX designers need to be able to put themselves into the position of users and imagine what features would make it easy to use a product. They must be sensitive to users’ “pain points” and needs and follow users through their journey.

Communication Skills

Both UI and UX designers need to be able to communicate with other design and development teams through all the stages of the design process, as well as with other stakeholders in the company, including decision-makers and marketing and sales teams.

Design Skills

UI/UX designers need to know design basics, including color theory, typography, and layout, for creating mockups and prototypes. That can include basic graphic design skills and some knowledge of visual arts as well as website and webpage design.

Software and Computer Skills

To create design prototypes, UI/UX designers need some familiarity with design and modeling software. Experience with wireframing, animation, 3D modeling, and web design can also be helpful.

Are You Interested in a Career in UI and UX Design?

UI/UX design is a broad field with subspecialties that include research, writing, and data management, and it offers opportunities in industries of all kinds. Today, specialized bootcamps and professional certification programs target the skills you need to find work in this fast-growing field. With the UI UX Online Bootcamp delivered by Simplilearn in collaboration with the University of Massachusetts, you can become a certified UI/UX designer and build your portfolio in just five months, with additional job assistance to find the right position.

You might also like to read:

What is a UI Developer? A Comprehensive Guide

Tips on How to Improve the UI/UX of a Website

How to Become a UI/UX Designer? Responsibilities, Skills & Everything You Should Know in 2023

A Comprehensive Guide to UI UX Interview Questions

UI UX Designer Job Description: What Does UI UX Designer Do?

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What is UX Research: The Ultimate Guide for UX Researchers

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Essential elements of an effective UX research plan (examples + templates)

Conducting UX research without a plan is like moving to another country without knowing the language—confusing and exhausting.

To avoid wasting time and resources, it’s crucial to set achievable research goals and work on developing a research plan that’s clear, comprehensive, and aligned with your overarching business goals and research strategy.

A good UX research plan sets out the parameters for your research, and guides how you’ll gather insights to inform product development. In this chapter, we share a step-by-step guide to creating a research plan, including templates and tactics for you to try. You’ll also find expert tips from Paige Bennett, Senior User Research Manager at Affirm, and Sinéad Davis Cochrane, Research Manager at Workday.

What is a UX research plan?

A UX research plan—not to be confused with a UX research strategy or research design—is a plan to guide individual user experience (UX) research projects.

It's a living document that includes a detailed explanation of tactics, methods, timeline, scope, and task owners. It should be co-created and shared with key stakeholders, so everyone is familiar with the project plan, and product teams can meet strategic goals.

A UX research plan is different to a research strategy and research design in both its purpose and contents. Let’s take a look.

Research plan vs. research design vs. research strategy: What’s the difference?

While your UX research plan should be based on strategy, it’s not the same thing. Your UX strategy is a high-level document that contains goals, budget, vision, and expectations. Meanwhile, a plan is a detailed document explaining how the team will achieve those strategic goals. Research design is the form your research itself takes.

In short, a strategy is a guide, a plan is what drives action, and design is the action itself.

What are the benefits of using a UX research plan?

Conducting research without goals and parameters is aimless. A UX research plan is beneficial for your product, user, and business—by building a plan for conducting UX research, you can:

Streamline processes and add structure

Work toward specific, measurable goals, align and engage stakeholders, save time by avoiding rework.

The structure of a research plan allows you to set timelines, expectations, and task owners, so everyone on your team is aligned and empowered to make decisions. Since there’s no second guessing what to do next or which methods to use, you’ll find your process becomes simpler and more efficient. It’s also worth standardizing your process to turn your plan into a template that you can reuse for future projects.

When you set research goals based on strategy, you’ll find it easier to track your team’s progress and keep the project in scope, on time, and on budget. With a solid, strategy-based UX research plan you can also track metrics at different stages of the project and adjust future tactics to get better research findings.

“It’s important to make sure your stakeholders are on the same page with regards to scope, timeline, and goals before you start," explains Paige Bennett, Senior User Research Manager at Affirm. That's because, when stakeholders are aligned, they're much more likely to sign off on product changes that result from UX research.

A written plan is a collaborative way to involve stakeholders in your research and turn them into active participants rather than passive observers. As they get involved, they'll make useful contributions and get a better understanding of your goals.

A UX research plan helps you save time and money quite simply because it’s easier and less expensive to make design or prototype changes than it is to fix usability issues once the product is coded or fully launched. Additionally, having a plan gives your team direction, which means they won’t be conducting research and talking to users without motive, and you’ll be making better use of your resources. What’s more, when everyone is aligned on goals, they’re empowered to make informed decisions instead of waiting for their managers’ approval.

What should a UX research plan include?

In French cuisine, the concept of mise en place—putting in place—allows chefs to plan and set up their workspace with all the required ingredients before cooking. Think of your research plan like this—laying out the key steps you need to go through during research, to help you run a successful and more efficient study.

Here’s what you should include in a UX research plan:

• A brief reminder of the strategy and goals
• An outline of the research objectives
• The purpose of the plan and studies
• A short description of the target audience, sample size, scope, and demographics
• A detailed list of expectations including deliverables, timings, and type of results
• An overview of the test methods and a short explanation of why you chose them
• The test set up or guidelines to outline everything that needs to happen before the study: scenarios, screening questions, and duration of pilot tests
• Your test scripts, questions to ask, or samples to follow
• When and how you’ll present the results
• Cost estimations or requests to go over budget

Collect all UX research findings in one place

Use Maze to run quantitative and qualitative research, influence product design, and shape user-centered products.

How to create a UX research plan

Now we’ve talked through why you need a research plan, let’s get into the how. Here’s a short step-by-step guide on how to write a research plan that will drive results.

• Define the problem statement
• Get stakeholders’ buy-in
• Identify your objectives
• Choose the right research method
• Recruit participants
• Prepare the brief
• Establish the timeline
• Decide how you’ll present your findings

1. Define the problem statement

One of the most important purposes of a research plan is to identify what you’re trying to achieve with the research, and clarify the problem statement. For Paige Bennett , Senior User Research Manager at Affirm, this process begins by sitting together with stakeholders and looking at the problem space.

“We do an exercise called FOG, which stands for ‘Fact, Observation, Guess’, to identify large gaps in knowledge,” says Paige. “Evaluating what you know illuminates questions you still have, which then serves as the foundation of the UX research project.”

You can use different techniques to identify the problem statement, such as stakeholder interviews, team sessions, or analysis of customer feedback. The problem statement should explain what the project is about—helping to define the research scope with clear deliverables and objectives.

2. Identify your objectives

Research objectives need to align with the UX strategy and broader business goals, but you also need to define specific targets to achieve within the research itself—whether that’s understanding a specific problem, or measuring usability metrics . So, before you get into a room with your users and customers, “Think about the research objectives: what you’re doing, why you’re doing it, and what you expect from the UX research process ,” explains Sinéad Davis Cochrane , Research Manager at Workday.

Examples of research objectives might be:

• Learn at what times users interact with your product
• Understand why users return (or not) to your website/app
• Discover what competitor products your users are using
• Uncover any pain points or challenges users find when navigating with your product
• Gauge user interest in and prioritize potential new features

A valuable purpose of setting objectives is ensuring your project doesn't suffer from scope creep. This can happen when stakeholders see your research as an opportunity to ask any question. As a researcher , Sinéad believes your objectives can guide the type of research questions you ask and give your research more focus. Otherwise, anything and everything becomes a research question—which will confuse your findings and be overwhelming to manage.

Sinéad shares a list of questions you should ask yourself and the research team to help set objectives:

• What are you going to do with this information?
• What decisions is it going to inform?
• How are you going to leverage these insights?

Another useful exercise to help identify research objectives is by asking questions that help you get to the core of a problem. Ask these types of questions before starting the planning process:

• Who are the users you’re designing this for?
• What problems and needs do they have?
• What are the pain points of using the product?
• Why are they not using a product like yours?

3. Get stakeholders buy-in

It’s good practice to involve stakeholders at early stages of plan creation to get everyone on board. Sharing your UX research plan with relevant stakeholders means you can gather context, adjust based on comments, and gauge what’s truly important to them. When you present the research plan to key stakeholders, remember to align on the scope of research, and how and when you’ll get back to them with results.

Stakeholders usually have a unique vision of the product, and it’s crucial that you’re able to capture it early on—this doesn’t mean saying yes to everything, but listening to their ideas and having a conversation. Seeing the UX research plan as a living document makes it much easier to edit based on team comments. Plus, the more you listen to other ideas, the easier it will be to evangelize research and get stakeholder buy-in by helping them see the value behind it.

I expect my stakeholders to be participants, and I outline how I expect that to happen. That includes observing interviews, participating in synthesis exercises, or co-presenting research recommendations.

Paige Bennett , Senior User Research Manager at Affirm

4. Choose the right research method

Choose between the different UX research methods to capture different insights from users.

To define the research methods you’ll use, circle back to your research objectives, what stage of the product development process you’re in, and the constraints, resources, and timeline of the project. It’s good research practice to use a mix of different methods to get a more complete perspective of users’ struggles.

For example, if you’re at the start of the design process, a generative research method such as user interviews or field studies will help you generate new insights about the target audience. Or, if you need to evaluate how a new design performs with users, you can run usability tests to get actionable feedback.

It’s also good practice to mix methods that drive quantitative and qualitative results so you can understand context, and catch the user sentiment behind a metric. For instance, if during a remote usability test, you hear a user go ‘Ugh! Where’s the sign up button?’ you’ll get a broader perspective than if you were just reviewing the number of clicks on the same test task.

Examples of UX research methods to consider include:

• Five-second testing
• User interviews
• Field studies
• Card sorting
• Tree testing
• Focus groups
• Usability testing
• Diary studies
• Live website testing

Check out our top UX research templates . Use them as a shortcut to get started on your research.

5. Determine how to recruit participants

Every research plan should include information about the participants you need for your study, and how you’ll recruit them. To identify your perfect candidate, revisit your goals and the questions that need answering, then build a target user persona including key demographics and use cases. Consider the resources you have available already, by asking yourself:

• Do you have a user base you can tap into to collect customer insights ?
• Do you need to hire external participants?
• What’s your budget to recruit users?
• How many users do you need to interact with?

When selecting participants, make sure they represent all your target personas. If different types of people will be using a certain product, you need to make sure that the people you research represent these personas. This means not just being inclusive in your recruitment, but considering secondary personas—the people who may not be your target user base, but interact with your product incidentally.

You should also consider recruiting research participants to test the product on different devices. Paige explains: “If prior research has shown that behavior differs greatly between those who use a product on their phone versus their tablet, I need to better understand those differences—so I’m going to make sure my participants include people who have used a product on both devices.”

During this step, make sure to include information about the required number of participants, how you’ll get them to participate, and how much time you need per user. The main ways to recruit testers are:

• Using an online participant recruitment tool like Maze Panel
• Putting out physical or digital adverts in spaces that are relevant to your product and user
• Reaching out to existing users
• Using participants from previous research
• Recruiting directly from your website or app with a tool like In-Product Prompts

5.1. Determine how you’ll pay them

You should always reward your test participants for their time and insights. Not only because it’s the right thing to do, but also because if they have an incentive they’re more likely to give you complete and insightful answers. If you’re hosting the studies in person, you’ll also need to cover your participants' travel expenses and secure a research space. Running remote moderated or unmoderated research is often considered to be less expensive and faster to complete.

If you’re testing an international audience, remember to check your proposed payment system works worldwide—this might be an Amazon gift card or prepaid Visa cards.

6. Prepare the brief

The next component of a research plan is to create a brief or guide for your research sessions. The kind of brief you need will vary depending on your research method, but for moderated methods like user interviews, field studies, or focus groups, you’ll need a detailed guide and script. The brief is there to remind you which questions to ask and keep the sessions on track.

Your script should cover:

• Introduction: A short message you’ll say to participants before the session begins. This works as a starting point for conversations and helps set the tone for the meeting. If you’re testing without a moderator, you should also include an introductory message to explain what the research is about and the type of answers they should give (in terms of length and specificity).
• Interview questions: Include your list of questions you’ll ask participants during the sessions. These could be examples to help guide the interviews, specific pre-planned questions, or test tasks you’ll ask participants to perform during unmoderated sessions.
• Outro message: Outline what you'll say at the end of the session, including the next steps, asking participants if they are open to future research, and thanking them for their time. This can be a form you share at the end of asynchronous sessions.

It’s crucial you remember to ask participants for their consent. You should do this at the beginning of the test by asking if they’re okay with you recording the session. Use this space to lay out any compensation agreements as well. Then, ask again at the end of the session if they agree with you keeping the results and using the data for research purposes. If possible, explain exactly what you’ll do with their data. Double check and get your legal team’s sign-off on these forms.

7. Establish the timeline

Next in your plan, estimate how long the research project will take and when you should expect to review the findings. Even if not exact, determining an approximate timeline (e.g., two-three weeks) will enable you to manage stakeholders’ expectations of the process and results.

Many people believe UX research is a lengthy process, so they skip it. When you set up a timeline and get stakeholders aligned with it, you can debunk assumptions and put stakeholders’ minds at ease. Plus, if you’re using a product discovery tool like Maze, you can get answers to your tests within days.

8. Decide how you’ll present your findings

When it comes to sharing your findings with your team, presentation matters. You need to make a clear presentation and demonstrate how user insights will influence design and development. If you’ve conducted UX research in the past, share data that proves how implementing user insights has improved product adoption.

Examples of ways you can present your results include:

• A physical or digital PDF report with key statistics and takeaways
• An interactive online report of the individual research questions and their results
• A presentation explaining the results and your findings
• A digital whiteboard, like Miro, to display the results

In your plan, mention how you’ll share insights with the product team. For example, if you’re using Maze, you can start by emailing everyone the ready-to-share report and setting up a meeting with the team to identify how to bring those insights to life. This is key, because your research should be the guiding light for new products or updates, if you want to keep development user-centric. Taking care over how you present your findings will impact whether they’re taken seriously and implemented by other stakeholders.

Your UX research plan template: Free template + example

Whether you’re creating the plan yourself or delegating to your team, a clear UX research plan template cuts your prep time in half.

Find our customizable free UX research plan template here , and keep reading for a filled-in example.

Example: Improving user adoption of a project management tool called Flows

Now, let’s go through how to fill out this template and create a UX research plan with an example.

Executive summary:

Flows aims to increase user adoption and tool engagement by 30% within the next 12 months. Our B2B project management software has been on the market for 3 years and has 25,000 active users across various industries.

By researching the current product experience with existing users, we’ll learn what works and what doesn’t in order to make adjustments to the product and experience.

Research objectives:

Purpose of the plan and studies:

The purpose is to gather actionable insights into user needs, behaviors, and challenges to inform updates that will drive increased adoption and engagement of 30% for the B2B project management tool within 12 months.

Target audience, sample size, scope, and demographics:

Expectations, deliverables, timings, and type of results:

Research methodologies:

*Some teams will take part in more than one research session.

Research analysis methods:

We are doing a mixed methods study.

User interviews are our primary method for gathering qualitative data, and will be analyzed using thematic analysis .

• Quantitative data will be pulled from usability tests to evaluate the effectiveness of our current design.
• Research set up and guidelines:
• Create baselines surveys to gauge current usage and pain points
• Develop interview/discussion guides and usability testing scenarios
• Pilot test materials with two teams
• User interviews: 60 mins, semi-structured; usability tests: 90 mins
• Findings will be presented in a research report for all stakeholders

Research scripts, questions, and samples:

User interview questions:

• What’s your experience with Flows?
• How does Flows fit into your workflow?
• What is your understanding of Flows’ features?
• What do you wish Flows could do that it currently doesn’t?

Usability test sample with Maze:

Cost estimations or budget requests/pricing:

Total estimated budget: $8,000

More free customizable templates for UX research

Whether you’re creating the plan yourself or are delegating this responsibility to your team, here are six research templates to get started:

• UX research plan template : This editable Miro research project plan example helps you brainstorm user and business-facing problems, objectives, and questions
• UX research brief : You need a clear brief before you conduct UX research—Milanote shares a template that will help you simplify the writing process
• User testing synthesis : Trello put together a sample board to organize user testing notes—you can use this as a guide, but change the titles to fit your UX research purposes
• Usability testing templates : At Maze, we’ve created multiple templates for conducting specific UX research methods—this list will help you create different remote usability tests
• Information architecture (IA) tests template : The way you organize the information in your website or app can improve or damage the user experience—use this template to run IA tests easily
• Feedback survey templates : Ask users anything through a survey, and use these templates to get creative and simplify creation

Everything you need to know about UX research plans

We all know that a robust plan is essential for conducting successful UX research. But, in case you want a quick refresher on what we’ve covered:

• Using a UX research strategy as a starting point will make your plan more likely to succeed
• Determine your research objectives before anything else
• Use a mix of qualitative and quantitative research methods
• Come up with clear personas so you can recruit and test a group of individuals that’s representative of your real end users
• Involve stakeholders from the beginning to get buy-in
• Be vocal about timelines, budget, and expected research findings
• Use the insights to power your product decisions and wow your users; building the solution they genuinely want and need

UX research can happen at any stage of the development lifecycle. When you build products with and for users, you need to include them continuously at various stages of the process.

It’s helpful to explore the need for continuous discovery in your UX research plan and look for a tool like Maze that simplifies the process for you. We’ll cover more about the different research methods and UX research tools in the upcoming chapters—ready to go?

Elevate your UX research workflow

Discover how Maze can streamline and operationalize your research plans to drive real product innovation while saving on costs.

Frequently asked questions

What’s the difference between a UX research plan and a UX research strategy?

The difference between a UX research plan and a UX research strategy is that they cover different levels of scope and detail. A UX research plan is a document that guides individual user experience (UX) research projects. UX research plans are shared documents that everyone on the product team can and should be familiar with. A UX research strategy, on the other hand, outlines the high-level goals, expectations, and demographics of the organization’s approach to research.

What should you include in a user research plan?

Here’s what to include in a user research plan:

• Problem statement
• Research objectives
• Research methods
• Participants' demographics
• Recruitment plan
• User research brief
• Expected timeline
• How to present findings

How do you write a research plan for UX design?

Creating a research plan for user experience (UX) requires a clear problem statement and objectives, choosing the right research method, recruiting participants and briefing them, and establishing a timeline for your project. You'll also need to plan how you'll analyze and present your findings.

How do you plan a UX research roadmap?

To plan a UX research roadmap, start by identifying key business goals and user needs. Align research activities with product milestones to ensure timely insights. Prioritize research methods—like surveys, interviews, and usability tests—based on the project phase and objectives. Set clear timelines and allocate resources accordingly. Regularly update stakeholders on progress and integrate feedback to refine the roadmap continuously.

Generative Research: Definition, Methods, and Examples

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• Open access
• Published: 31 August 2024

Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023

• Xianru Shang   ORCID: orcid.org/0009-0000-8906-3216 1 ,
• Zijian Liu 1 ,
• Chen Gong 1 ,
• Zhigang Hu 1 ,
• Yuexuan Wu 1 &
• Chengliang Wang   ORCID: orcid.org/0000-0003-2208-3508 2  

Humanities and Social Sciences Communications volume  11 , Article number:  1115 ( 2024 ) Cite this article

Metrics details

• Science, technology and society

The rapid expansion of information technology and the intensification of population aging are two prominent features of contemporary societal development. Investigating older adults’ acceptance and use of technology is key to facilitating their integration into an information-driven society. Given this context, the technology acceptance of older adults has emerged as a prioritized research topic, attracting widespread attention in the academic community. However, existing research remains fragmented and lacks a systematic framework. To address this gap, we employed bibliometric methods, utilizing the Web of Science Core Collection to conduct a comprehensive review of literature on older adults’ technology acceptance from 2013 to 2023. Utilizing VOSviewer and CiteSpace for data assessment and visualization, we created knowledge mappings of research on older adults’ technology acceptance. Our study employed multidimensional methods such as co-occurrence analysis, clustering, and burst analysis to: (1) reveal research dynamics, key journals, and domains in this field; (2) identify leading countries, their collaborative networks, and core research institutions and authors; (3) recognize the foundational knowledge system centered on theoretical model deepening, emerging technology applications, and research methods and evaluation, uncovering seminal literature and observing a shift from early theoretical and influential factor analyses to empirical studies focusing on individual factors and emerging technologies; (4) moreover, current research hotspots are primarily in the areas of factors influencing technology adoption, human-robot interaction experiences, mobile health management, and aging-in-place technology, highlighting the evolutionary context and quality distribution of research themes. Finally, we recommend that future research should deeply explore improvements in theoretical models, long-term usage, and user experience evaluation. Overall, this study presents a clear framework of existing research in the field of older adults’ technology acceptance, providing an important reference for future theoretical exploration and innovative applications.

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Introduction.

In contemporary society, the rapid development of information technology has been intricately intertwined with the intensifying trend of population aging. According to the latest United Nations forecast, by 2050, the global population aged 65 and above is expected to reach 1.6 billion, representing about 16% of the total global population (UN 2023 ). Given the significant challenges of global aging, there is increasing evidence that emerging technologies have significant potential to maintain health and independence for older adults in their home and healthcare environments (Barnard et al. 2013 ; Soar 2010 ; Vancea and Solé-Casals 2016 ). This includes, but is not limited to, enhancing residential safety with smart home technologies (Touqeer et al. 2021 ; Wang et al. 2022 ), improving living independence through wearable technologies (Perez et al. 2023 ), and increasing medical accessibility via telehealth services (Kruse et al. 2020 ). Technological innovations are redefining the lifestyles of older adults, encouraging a shift from passive to active participation (González et al. 2012 ; Mostaghel 2016 ). Nevertheless, the effective application and dissemination of technology still depends on user acceptance and usage intentions (Naseri et al. 2023 ; Wang et al. 2023a ; Xia et al. 2024 ; Yu et al. 2023 ). Particularly, older adults face numerous challenges in accepting and using new technologies. These challenges include not only physical and cognitive limitations but also a lack of technological experience, along with the influences of social and economic factors (Valk et al. 2018 ; Wilson et al. 2021 ).

User acceptance of technology is a significant focus within information systems (IS) research (Dai et al. 2024 ), with several models developed to explain and predict user behavior towards technology usage, including the Technology Acceptance Model (TAM) (Davis 1989 ), TAM2, TAM3, and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al. 2003 ). Older adults, as a group with unique needs, exhibit different behavioral patterns during technology acceptance than other user groups, and these uniquenesses include changes in cognitive abilities, as well as motivations, attitudes, and perceptions of the use of new technologies (Chen and Chan 2011 ). The continual expansion of technology introduces considerable challenges for older adults, rendering the understanding of their technology acceptance a research priority. Thus, conducting in-depth research into older adults’ acceptance of technology is critically important for enhancing their integration into the information society and improving their quality of life through technological advancements.

Reviewing relevant literature to identify research gaps helps further solidify the theoretical foundation of the research topic. However, many existing literature reviews primarily focus on the factors influencing older adults’ acceptance or intentions to use technology. For instance, Ma et al. ( 2021 ) conducted a comprehensive analysis of the determinants of older adults’ behavioral intentions to use technology; Liu et al. ( 2022 ) categorized key variables in studies of older adults’ technology acceptance, noting a shift in focus towards social and emotional factors; Yap et al. ( 2022 ) identified seven categories of antecedents affecting older adults’ use of technology from an analysis of 26 articles, including technological, psychological, social, personal, cost, behavioral, and environmental factors; Schroeder et al. ( 2023 ) extracted 119 influencing factors from 59 articles and further categorized these into six themes covering demographics, health status, and emotional awareness. Additionally, some studies focus on the application of specific technologies, such as Ferguson et al. ( 2021 ), who explored barriers and facilitators to older adults using wearable devices for heart monitoring, and He et al. ( 2022 ) and Baer et al. ( 2022 ), who each conducted in-depth investigations into the acceptance of social assistive robots and mobile nutrition and fitness apps, respectively. In summary, current literature reviews on older adults’ technology acceptance exhibit certain limitations. Due to the interdisciplinary nature and complex knowledge structure of this field, traditional literature reviews often rely on qualitative analysis, based on literature analysis and periodic summaries, which lack sufficient objectivity and comprehensiveness. Additionally, systematic research is relatively limited, lacking a macroscopic description of the research trajectory from a holistic perspective. Over the past decade, research on older adults’ technology acceptance has experienced rapid growth, with a significant increase in literature, necessitating the adoption of new methods to review and examine the developmental trends in this field (Chen 2006 ; Van Eck and Waltman 2010 ). Bibliometric analysis, as an effective quantitative research method, analyzes published literature through visualization, offering a viable approach to extracting patterns and insights from a large volume of papers, and has been widely applied in numerous scientific research fields (Achuthan et al. 2023 ; Liu and Duffy 2023 ). Therefore, this study will employ bibliometric methods to systematically analyze research articles related to older adults’ technology acceptance published in the Web of Science Core Collection from 2013 to 2023, aiming to understand the core issues and evolutionary trends in the field, and to provide valuable references for future related research. Specifically, this study aims to explore and answer the following questions:

RQ1: What are the research dynamics in the field of older adults’ technology acceptance over the past decade? What are the main academic journals and fields that publish studies related to older adults’ technology acceptance?

RQ2: How is the productivity in older adults’ technology acceptance research distributed among countries, institutions, and authors?

RQ3: What are the knowledge base and seminal literature in older adults’ technology acceptance research? How has the research theme progressed?

RQ4: What are the current hot topics and their evolutionary trajectories in older adults’ technology acceptance research? How is the quality of research distributed?

Methodology and materials

Research method.

In recent years, bibliometrics has become one of the crucial methods for analyzing literature reviews and is widely used in disciplinary and industrial intelligence analysis (Jing et al. 2023 ; Lin and Yu 2024a ; Wang et al. 2024a ; Xu et al. 2021 ). Bibliometric software facilitates the visualization analysis of extensive literature data, intuitively displaying the network relationships and evolutionary processes between knowledge units, and revealing the underlying knowledge structure and potential information (Chen et al. 2024 ; López-Robles et al. 2018 ; Wang et al. 2024c ). This method provides new insights into the current status and trends of specific research areas, along with quantitative evidence, thereby enhancing the objectivity and scientific validity of the research conclusions (Chen et al. 2023 ; Geng et al. 2024 ). VOSviewer and CiteSpace are two widely used bibliometric software tools in academia (Pan et al. 2018 ), recognized for their robust functionalities based on the JAVA platform. Although each has its unique features, combining these two software tools effectively constructs mapping relationships between literature knowledge units and clearly displays the macrostructure of the knowledge domains. Particularly, VOSviewer, with its excellent graphical representation capabilities, serves as an ideal tool for handling large datasets and precisely identifying the focal points and hotspots of research topics. Therefore, this study utilizes VOSviewer (version 1.6.19) and CiteSpace (version 6.1.R6), combined with in-depth literature analysis, to comprehensively examine and interpret the research theme of older adults’ technology acceptance through an integrated application of quantitative and qualitative methods.

Data source

Web of Science is a comprehensively recognized database in academia, featuring literature that has undergone rigorous peer review and editorial scrutiny (Lin and Yu 2024b ; Mongeon and Paul-Hus 2016 ; Pranckutė 2021 ). This study utilizes the Web of Science Core Collection as its data source, specifically including three major citation indices: Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). These indices encompass high-quality research literature in the fields of science, social sciences, and arts and humanities, ensuring the comprehensiveness and reliability of the data. We combined “older adults” with “technology acceptance” through thematic search, with the specific search strategy being: TS = (elder OR elderly OR aging OR ageing OR senile OR senior OR old people OR “older adult*”) AND TS = (“technology acceptance” OR “user acceptance” OR “consumer acceptance”). The time span of literature search is from 2013 to 2023, with the types limited to “Article” and “Review” and the language to “English”. Additionally, the search was completed by October 27, 2023, to avoid data discrepancies caused by database updates. The initial search yielded 764 journal articles. Given that searches often retrieve articles that are superficially relevant but actually non-compliant, manual screening post-search was essential to ensure the relevance of the literature (Chen et al. 2024 ). Through manual screening, articles significantly deviating from the research theme were eliminated and rigorously reviewed. Ultimately, this study obtained 500 valid sample articles from the Web of Science Core Collection. The complete PRISMA screening process is illustrated in Fig. 1 .

Presentation of the data culling process in detail.

Data standardization

Raw data exported from databases often contain multiple expressions of the same terminology (Nguyen and Hallinger 2020 ). To ensure the accuracy and consistency of data, it is necessary to standardize the raw data (Strotmann and Zhao 2012 ). This study follows the data standardization process proposed by Taskin and Al ( 2019 ), mainly executing the following operations:

(1) Standardization of author and institution names is conducted to address different name expressions for the same author. For instance, “Chan, Alan Hoi Shou” and “Chan, Alan H. S.” are considered the same author, and distinct authors with the same name are differentiated by adding identifiers. Diverse forms of institutional names are unified to address variations caused by name changes or abbreviations, such as standardizing “FRANKFURT UNIV APPL SCI” and “Frankfurt University of Applied Sciences,” as well as “Chinese University of Hong Kong” and “University of Hong Kong” to consistent names.

(2) Different expressions of journal names are unified. For example, “International Journal of Human-Computer Interaction” and “Int J Hum Comput Interact” are standardized to a single name. This ensures consistency in journal names and prevents misclassification of literature due to differing journal names. Additionally, it involves checking if the journals have undergone name changes in the past decade to prevent any impact on the analysis due to such changes.

(3) Keywords data are cleansed by removing words that do not directly pertain to specific research content (e.g., people, review), merging synonyms (e.g., “UX” and “User Experience,” “aging-in-place” and “aging in place”), and standardizing plural forms of keywords (e.g., “assistive technologies” and “assistive technology,” “social robots” and “social robot”). This reduces redundant information in knowledge mapping.

Bibliometric results and analysis

Distribution power (rq1), literature descriptive statistical analysis.

Table 1 presents a detailed descriptive statistical overview of the literature in the field of older adults’ technology acceptance. After deduplication using the CiteSpace software, this study confirmed a valid sample size of 500 articles. Authored by 1839 researchers, the documents encompass 792 research institutions across 54 countries and are published in 217 different academic journals. As of the search cutoff date, these articles have accumulated 13,829 citations, with an annual average of 1156 citations, and an average of 27.66 citations per article. The h-index, a composite metric of quantity and quality of scientific output (Kamrani et al. 2021 ), reached 60 in this study.

Trends in publications and disciplinary distribution

The number of publications and citations are significant indicators of the research field’s development, reflecting its continuity, attention, and impact (Ale Ebrahim et al. 2014 ). The ranking of annual publications and citations in the field of older adults’ technology acceptance studies is presented chronologically in Fig. 2A . The figure shows a clear upward trend in the amount of literature in this field. Between 2013 and 2017, the number of publications increased slowly and decreased in 2018. However, in 2019, the number of publications increased rapidly to 52 and reached a peak of 108 in 2022, which is 6.75 times higher than in 2013. In 2022, the frequency of document citations reached its highest point with 3466 citations, reflecting the widespread recognition and citation of research in this field. Moreover, the curve of the annual number of publications fits a quadratic function, with a goodness-of-fit R 2 of 0.9661, indicating that the number of future publications is expected to increase even more rapidly.

A Trends in trends in annual publications and citations (2013–2023). B Overlay analysis of the distribution of discipline fields.

Figure 2B shows that research on older adults’ technology acceptance involves the integration of multidisciplinary knowledge. According to Web of Science Categories, these 500 articles are distributed across 85 different disciplines. We have tabulated the top ten disciplines by publication volume (Table 2 ), which include Medical Informatics (75 articles, 15.00%), Health Care Sciences & Services (71 articles, 14.20%), Gerontology (61 articles, 12.20%), Public Environmental & Occupational Health (57 articles, 11.40%), and Geriatrics & Gerontology (52 articles, 10.40%), among others. The high output in these disciplines reflects the concentrated global academic interest in this comprehensive research topic. Additionally, interdisciplinary research approaches provide diverse perspectives and a solid theoretical foundation for studies on older adults’ technology acceptance, also paving the way for new research directions.

Knowledge flow analysis

A dual-map overlay is a CiteSpace map superimposed on top of a base map, which shows the interrelationships between journals in different domains, representing the publication and citation activities in each domain (Chen and Leydesdorff 2014 ). The overlay map reveals the link between the citing domain (on the left side) and the cited domain (on the right side), reflecting the knowledge flow of the discipline at the journal level (Leydesdorff and Rafols 2012 ). We utilize the in-built Z-score algorithm of the software to cluster the graph, as shown in Fig. 3 .

The left side shows the citing journal, and the right side shows the cited journal.

Figure 3 shows the distribution of citing journals clusters for older adults’ technology acceptance on the left side, while the right side refers to the main cited journals clusters. Two knowledge flow citation trajectories were obtained; they are presented by the color of the cited regions, and the thickness of these trajectories is proportional to the Z-score scaled frequency of citations (Chen et al. 2014 ). Within the cited regions, the most popular fields with the most records covered are “HEALTH, NURSING, MEDICINE” and “PSYCHOLOGY, EDUCATION, SOCIAL”, and the elliptical aspect ratio of these two fields stands out. Fields have prominent elliptical aspect ratios, highlighting their significant influence on older adults’ technology acceptance research. Additionally, the major citation trajectories originate in these two areas and progress to the frontier research area of “PSYCHOLOGY, EDUCATION, HEALTH”. It is worth noting that the citation trajectory from “PSYCHOLOGY, EDUCATION, SOCIAL” has a significant Z-value (z = 6.81), emphasizing the significance and impact of this development path. In the future, “MATHEMATICS, SYSTEMS, MATHEMATICAL”, “MOLECULAR, BIOLOGY, IMMUNOLOGY”, and “NEUROLOGY, SPORTS, OPHTHALMOLOGY” may become emerging fields. The fields of “MEDICINE, MEDICAL, CLINICAL” may be emerging areas of cutting-edge research.

Main research journals analysis

Table 3 provides statistics for the top ten journals by publication volume in the field of older adults’ technology acceptance. Together, these journals have published 137 articles, accounting for 27.40% of the total publications, indicating that there is no highly concentrated core group of journals in this field, with publications being relatively dispersed. Notably, Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction each lead with 15 publications. In terms of citation metrics, International Journal of Medical Informatics and Computers in Human Behavior stand out significantly, with the former accumulating a total of 1,904 citations, averaging 211.56 citations per article, and the latter totaling 1,449 citations, with an average of 96.60 citations per article. These figures emphasize the academic authority and widespread impact of these journals within the research field.

Research power (RQ2)

Countries and collaborations analysis.

The analysis revealed the global research pattern for country distribution and collaboration (Chen et al. 2019 ). Figure 4A shows the network of national collaborations on older adults’ technology acceptance research. The size of the bubbles represents the amount of publications in each country, while the thickness of the connecting lines expresses the closeness of the collaboration among countries. Generally, this research subject has received extensive international attention, with China and the USA publishing far more than any other countries. China has established notable research collaborations with the USA, UK and Malaysia in this field, while other countries have collaborations, but the closeness is relatively low and scattered. Figure 4B shows the annual publication volume dynamics of the top ten countries in terms of total publications. Since 2017, China has consistently increased its annual publications, while the USA has remained relatively stable. In 2019, the volume of publications in each country increased significantly, this was largely due to the global outbreak of the COVID-19 pandemic, which has led to increased reliance on information technology among the elderly for medical consultations, online socialization, and health management (Sinha et al. 2021 ). This phenomenon has led to research advances in technology acceptance among older adults in various countries. Table 4 shows that the top ten countries account for 93.20% of the total cumulative number of publications, with each country having published more than 20 papers. Among these ten countries, all of them except China are developed countries, indicating that the research field of older adults’ technology acceptance has received general attention from developed countries. Currently, China and the USA were the leading countries in terms of publications with 111 and 104 respectively, accounting for 22.20% and 20.80%. The UK, Germany, Italy, and the Netherlands also made significant contributions. The USA and China ranked first and second in terms of the number of citations, while the Netherlands had the highest average citations, indicating the high impact and quality of its research. The UK has shown outstanding performance in international cooperation, while the USA highlights its significant academic influence in this field with the highest h-index value.

A National collaboration network. B Annual volume of publications in the top 10 countries.

Institutions and authors analysis

Analyzing the number of publications and citations can reveal an institution’s or author’s research strength and influence in a particular research area (Kwiek 2021 ). Tables 5 and 6 show the statistics of the institutions and authors whose publication counts are in the top ten, respectively. As shown in Table 5 , higher education institutions hold the main position in this research field. Among the top ten institutions, City University of Hong Kong and The University of Hong Kong from China lead with 14 and 9 publications, respectively. City University of Hong Kong has the highest h-index, highlighting its significant influence in the field. It is worth noting that Tilburg University in the Netherlands is not among the top five in terms of publications, but the high average citation count (130.14) of its literature demonstrates the high quality of its research.

After analyzing the authors’ output using Price’s Law (Redner 1998 ), the highest number of publications among the authors counted ( n  = 10) defines a publication threshold of 3 for core authors in this research area. As a result of quantitative screening, a total of 63 core authors were identified. Table 6 shows that Chen from Zhejiang University, China, Ziefle from RWTH Aachen University, Germany, and Rogers from Macquarie University, Australia, were the top three authors in terms of the number of publications, with 10, 9, and 8 articles, respectively. In terms of average citation rate, Peek and Wouters, both scholars from the Netherlands, have significantly higher rates than other scholars, with 183.2 and 152.67 respectively. This suggests that their research is of high quality and widely recognized. Additionally, Chen and Rogers have high h-indices in this field.

Knowledge base and theme progress (RQ3)

Research knowledge base.

Co-citation relationships occur when two documents are cited together (Zhang and Zhu 2022 ). Co-citation mapping uses references as nodes to represent the knowledge base of a subject area (Min et al. 2021). Figure 5A illustrates co-occurrence mapping in older adults’ technology acceptance research, where larger nodes signify higher co-citation frequencies. Co-citation cluster analysis can be used to explore knowledge structure and research boundaries (Hota et al. 2020 ; Shiau et al. 2023 ). The co-citation clustering mapping of older adults’ technology acceptance research literature (Fig. 5B ) shows that the Q value of the clustering result is 0.8129 (>0.3), and the average value of the weight S is 0.9391 (>0.7), indicating that the clusters are uniformly distributed with a significant and credible structure. This further proves that the boundaries of the research field are clear and there is significant differentiation in the field. The figure features 18 cluster labels, each associated with thematic color blocks corresponding to different time slices. Highlighted emerging research themes include #2 Smart Home Technology, #7 Social Live, and #10 Customer Service. Furthermore, the clustering labels extracted are primarily classified into three categories: theoretical model deepening, emerging technology applications, research methods and evaluation, as detailed in Table 7 .

A Co-citation analysis of references. B Clustering network analysis of references.

Seminal literature analysis

The top ten nodes in terms of co-citation frequency were selected for further analysis. Table 8 displays the corresponding node information. Studies were categorized into four main groups based on content analysis. (1) Research focusing on specific technology usage by older adults includes studies by Peek et al. ( 2014 ), Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ), who investigated the factors influencing the use of e-technology, smartphones, mHealth, and smart wearables, respectively. (2) Concerning the development of theoretical models of technology acceptance, Chen and Chan ( 2014 ) introduced the Senior Technology Acceptance Model (STAM), and Macedo ( 2017 ) analyzed the predictive power of UTAUT2 in explaining older adults’ intentional behaviors and information technology usage. (3) In exploring older adults’ information technology adoption and behavior, Lee and Coughlin ( 2015 ) emphasized that the adoption of technology by older adults is a multifactorial process that includes performance, price, value, usability, affordability, accessibility, technical support, social support, emotion, independence, experience, and confidence. Yusif et al. ( 2016 ) conducted a literature review examining the key barriers affecting older adults’ adoption of assistive technology, including factors such as privacy, trust, functionality/added value, cost, and stigma. (4) From the perspective of research into older adults’ technology acceptance, Mitzner et al. ( 2019 ) assessed the long-term usage of computer systems designed for the elderly, whereas Guner and Acarturk ( 2020 ) compared information technology usage and acceptance between older and younger adults. The breadth and prevalence of this literature make it a vital reference for researchers in the field, also providing new perspectives and inspiration for future research directions.

Research thematic progress

Burst citation is a node of literature that guides the sudden change in dosage, which usually represents a prominent development or major change in a particular field, with innovative and forward-looking qualities. By analyzing the emergent literature, it is often easy to understand the dynamics of the subject area, mapping the emerging thematic change (Chen et al. 2022 ). Figure 6 shows the burst citation mapping in the field of older adults’ technology acceptance research, with burst citations represented by red nodes (Fig. 6A ). For the ten papers with the highest burst intensity (Fig. 6B ), this study will conduct further analysis in conjunction with literature review.

A Burst detection of co-citation. B The top 10 references with the strongest citation bursts.

As shown in Fig. 6 , Mitzner et al. ( 2010 ) broke the stereotype that older adults are fearful of technology, found that they actually have positive attitudes toward technology, and emphasized the centrality of ease of use and usefulness in the process of technology acceptance. This finding provides an important foundation for subsequent research. During the same period, Wagner et al. ( 2010 ) conducted theory-deepening and applied research on technology acceptance among older adults. The research focused on older adults’ interactions with computers from the perspective of Social Cognitive Theory (SCT). This expanded the understanding of technology acceptance, particularly regarding the relationship between behavior, environment, and other SCT elements. In addition, Pan and Jordan-Marsh ( 2010 ) extended the TAM to examine the interactions among predictors of perceived usefulness, perceived ease of use, subjective norm, and convenience conditions when older adults use the Internet, taking into account the moderating roles of gender and age. Heerink et al. ( 2010 ) adapted and extended the UTAUT, constructed a technology acceptance model specifically designed for older users’ acceptance of assistive social agents, and validated it using controlled experiments and longitudinal data, explaining intention to use by combining functional assessment and social interaction variables.

Then the research theme shifted to an in-depth analysis of the factors influencing technology acceptance among older adults. Two papers with high burst strengths emerged during this period: Peek et al. ( 2014 ) (Strength = 12.04), Chen and Chan ( 2014 ) (Strength = 9.81). Through a systematic literature review and empirical study, Peek STM and Chen K, among others, identified multidimensional factors that influence older adults’ technology acceptance. Peek et al. ( 2014 ) analyzed literature on the acceptance of in-home care technology among older adults and identified six factors that influence their acceptance: concerns about technology, expected benefits, technology needs, technology alternatives, social influences, and older adult characteristics, with a focus on differences between pre- and post-implementation factors. Chen and Chan ( 2014 ) constructed the STAM by administering a questionnaire to 1012 older adults and adding eight important factors, including technology anxiety, self-efficacy, cognitive ability, and physical function, based on the TAM. This enriches the theoretical foundation of the field. In addition, Braun ( 2013 ) highlighted the role of perceived usefulness, trust in social networks, and frequency of Internet use in older adults’ use of social networks, while ease of use and social pressure were not significant influences. These findings contribute to the study of older adults’ technology acceptance within specific technology application domains.

Recent research has focused on empirical studies of personal factors and emerging technologies. Ma et al. ( 2016 ) identified key personal factors affecting smartphone acceptance among older adults through structured questionnaires and face-to-face interviews with 120 participants. The study found that cost, self-satisfaction, and convenience were important factors influencing perceived usefulness and ease of use. This study offers empirical evidence to comprehend the main factors that drive smartphone acceptance among Chinese older adults. Additionally, Yusif et al. ( 2016 ) presented an overview of the obstacles that hinder older adults’ acceptance of assistive technologies, focusing on privacy, trust, and functionality.

In summary, research on older adults’ technology acceptance has shifted from early theoretical deepening and analysis of influencing factors to empirical studies in the areas of personal factors and emerging technologies, which have greatly enriched the theoretical basis of older adults’ technology acceptance and provided practical guidance for the design of emerging technology products.

Research hotspots, evolutionary trends, and quality distribution (RQ4)

Core keywords analysis.

Keywords concise the main idea and core of the literature, and are a refined summary of the research content (Huang et al. 2021 ). In CiteSpace, nodes with a centrality value greater than 0.1 are considered to be critical nodes. Analyzing keywords with high frequency and centrality helps to visualize the hot topics in the research field (Park et al. 2018 ). The merged keywords were imported into CiteSpace, and the top 10 keywords were counted and sorted by frequency and centrality respectively, as shown in Table 9 . The results show that the keyword “TAM” has the highest frequency (92), followed by “UTAUT” (24), which reflects that the in-depth study of the existing technology acceptance model and its theoretical expansion occupy a central position in research related to older adults’ technology acceptance. Furthermore, the terms ‘assistive technology’ and ‘virtual reality’ are both high-frequency and high-centrality terms (frequency = 17, centrality = 0.10), indicating that the research on assistive technology and virtual reality for older adults is the focus of current academic attention.

Research hotspots analysis

Using VOSviewer for keyword co-occurrence analysis organizes keywords into groups or clusters based on their intrinsic connections and frequencies, clearly highlighting the research field’s hot topics. The connectivity among keywords reveals correlations between different topics. To ensure accuracy, the analysis only considered the authors’ keywords. Subsequently, the keywords were filtered by setting the keyword frequency to 5 to obtain the keyword clustering map of the research on older adults’ technology acceptance research keyword clustering mapping (Fig. 7 ), combined with the keyword co-occurrence clustering network (Fig. 7A ) and the corresponding density situation (Fig. 7B ) to make a detailed analysis of the following four groups of clustered themes.

A Co-occurrence clustering network. B Keyword density.

Cluster #1—Research on the factors influencing technology adoption among older adults is a prominent topic, covering age, gender, self-efficacy, attitude, and and intention to use (Berkowsky et al. 2017 ; Wang et al. 2017 ). It also examined older adults’ attitudes towards and acceptance of digital health technologies (Ahmad and Mozelius, 2022 ). Moreover, the COVID-19 pandemic, significantly impacting older adults’ technology attitudes and usage, has underscored the study’s importance and urgency. Therefore, it is crucial to conduct in-depth studies on how older adults accept, adopt, and effectively use new technologies, to address their needs and help them overcome the digital divide within digital inclusion. This will improve their quality of life and healthcare experiences.

Cluster #2—Research focuses on how older adults interact with assistive technologies, especially assistive robots and health monitoring devices, emphasizing trust, usability, and user experience as crucial factors (Halim et al. 2022 ). Moreover, health monitoring technologies effectively track and manage health issues common in older adults, like dementia and mild cognitive impairment (Lussier et al. 2018 ; Piau et al. 2019 ). Interactive exercise games and virtual reality have been deployed to encourage more physical and cognitive engagement among older adults (Campo-Prieto et al. 2021 ). Personalized and innovative technology significantly enhances older adults’ participation, improving their health and well-being.

Cluster #3—Optimizing health management for older adults using mobile technology. With the development of mobile health (mHealth) and health information technology, mobile applications, smartphones, and smart wearable devices have become effective tools to help older users better manage chronic conditions, conduct real-time health monitoring, and even receive telehealth services (Dupuis and Tsotsos 2018 ; Olmedo-Aguirre et al. 2022 ; Kim et al. 2014 ). Additionally, these technologies can mitigate the problem of healthcare resource inequality, especially in developing countries. Older adults’ acceptance and use of these technologies are significantly influenced by their behavioral intentions, motivational factors, and self-management skills. These internal motivational factors, along with external factors, jointly affect older adults’ performance in health management and quality of life.

Cluster #4—Research on technology-assisted home care for older adults is gaining popularity. Environmentally assisted living enhances older adults’ independence and comfort at home, offering essential support and security. This has a crucial impact on promoting healthy aging (Friesen et al. 2016 ; Wahlroos et al. 2023 ). The smart home is a core application in this field, providing a range of solutions that facilitate independent living for the elderly in a highly integrated and user-friendly manner. This fulfills different dimensions of living and health needs (Majumder et al. 2017 ). Moreover, eHealth offers accurate and personalized health management and healthcare services for older adults (Delmastro et al. 2018 ), ensuring their needs are met at home. Research in this field often employs qualitative methods and structural equation modeling to fully understand older adults’ needs and experiences at home and analyze factors influencing technology adoption.

Evolutionary trends analysis

To gain a deeper understanding of the evolutionary trends in research hotspots within the field of older adults’ technology acceptance, we conducted a statistical analysis of the average appearance times of keywords, using CiteSpace to generate the time-zone evolution mapping (Fig. 8 ) and burst keywords. The time-zone mapping visually displays the evolution of keywords over time, intuitively reflecting the frequency and initial appearance of keywords in research, commonly used to identify trends in research topics (Jing et al. 2024a ; Kumar et al. 2021 ). Table 10 lists the top 15 keywords by burst strength, with the red sections indicating high-frequency citations and their burst strength in specific years. These burst keywords reveal the focus and trends of research themes over different periods (Kleinberg 2002 ). Combining insights from the time-zone mapping and burst keywords provides more objective and accurate research insights (Wang et al. 2023b ).

Reflecting the frequency and time of first appearance of keywords in the study.

An integrated analysis of Fig. 8 and Table 10 shows that early research on older adults’ technology acceptance primarily focused on factors such as perceived usefulness, ease of use, and attitudes towards information technology, including their use of computers and the internet (Pan and Jordan-Marsh 2010 ), as well as differences in technology use between older adults and other age groups (Guner and Acarturk 2020 ). Subsequently, the research focus expanded to improving the quality of life for older adults, exploring how technology can optimize health management and enhance the possibility of independent living, emphasizing the significant role of technology in improving the quality of life for the elderly. With ongoing technological advancements, recent research has shifted towards areas such as “virtual reality,” “telehealth,” and “human-robot interaction,” with a focus on the user experience of older adults (Halim et al. 2022 ). The appearance of keywords such as “physical activity” and “exercise” highlights the value of technology in promoting physical activity and health among older adults. This phase of research tends to make cutting-edge technology genuinely serve the practical needs of older adults, achieving its widespread application in daily life. Additionally, research has focused on expanding and quantifying theoretical models of older adults’ technology acceptance, involving keywords such as “perceived risk”, “validation” and “UTAUT”.

In summary, from 2013 to 2023, the field of older adults’ technology acceptance has evolved from initial explorations of influencing factors, to comprehensive enhancements in quality of life and health management, and further to the application and deepening of theoretical models and cutting-edge technologies. This research not only reflects the diversity and complexity of the field but also demonstrates a comprehensive and in-depth understanding of older adults’ interactions with technology across various life scenarios and needs.

Research quality distribution

To reveal the distribution of research quality in the field of older adults’ technology acceptance, a strategic diagram analysis is employed to calculate and illustrate the internal development and interrelationships among various research themes (Xie et al. 2020 ). The strategic diagram uses Centrality as the X-axis and Density as the Y-axis to divide into four quadrants, where the X-axis represents the strength of the connection between thematic clusters and other themes, with higher values indicating a central position in the research field; the Y-axis indicates the level of development within the thematic clusters, with higher values denoting a more mature and widely recognized field (Li and Zhou 2020 ).

Through cluster analysis and manual verification, this study categorized 61 core keywords (Frequency ≥5) into 11 thematic clusters. Subsequently, based on the keywords covered by each thematic cluster, the research themes and their directions for each cluster were summarized (Table 11 ), and the centrality and density coordinates for each cluster were precisely calculated (Table 12 ). Finally, a strategic diagram of the older adults’ technology acceptance research field was constructed (Fig. 9 ). Based on the distribution of thematic clusters across the quadrants in the strategic diagram, the structure and developmental trends of the field were interpreted.

Classification and visualization of theme clusters based on density and centrality.

As illustrated in Fig. 9 , (1) the theme clusters of #3 Usage Experience and #4 Assisted Living Technology are in the first quadrant, characterized by high centrality and density. Their internal cohesion and close links with other themes indicate their mature development, systematic research content or directions have been formed, and they have a significant influence on other themes. These themes play a central role in the field of older adults’ technology acceptance and have promising prospects. (2) The theme clusters of #6 Smart Devices, #9 Theoretical Models, and #10 Mobile Health Applications are in the second quadrant, with higher density but lower centrality. These themes have strong internal connections but weaker external links, indicating that these three themes have received widespread attention from researchers and have been the subject of related research, but more as self-contained systems and exhibit independence. Therefore, future research should further explore in-depth cooperation and cross-application with other themes. (3) The theme clusters of #7 Human-Robot Interaction, #8 Characteristics of the Elderly, and #11 Research Methods are in the third quadrant, with lower centrality and density. These themes are loosely connected internally and have weak links with others, indicating their developmental immaturity. Compared to other topics, they belong to the lower attention edge and niche themes, and there is a need for further investigation. (4) The theme clusters of #1 Digital Healthcare Technology, #2 Psychological Factors, and #5 Socio-Cultural Factors are located in the fourth quadrant, with high centrality but low density. Although closely associated with other research themes, the internal cohesion within these clusters is relatively weak. This suggests that while these themes are closely linked to other research areas, their own development remains underdeveloped, indicating a core immaturity. Nevertheless, these themes are crucial within the research domain of elderly technology acceptance and possess significant potential for future exploration.

Discussion on distribution power (RQ1)

Over the past decade, academic interest and influence in the area of older adults’ technology acceptance have significantly increased. This trend is evidenced by a quantitative analysis of publication and citation volumes, particularly noticeable in 2019 and 2022, where there was a substantial rise in both metrics. The rise is closely linked to the widespread adoption of emerging technologies such as smart homes, wearable devices, and telemedicine among older adults. While these technologies have enhanced their quality of life, they also pose numerous challenges, sparking extensive research into their acceptance, usage behaviors, and influencing factors among the older adults (Pirzada et al. 2022 ; Garcia Reyes et al. 2023 ). Furthermore, the COVID-19 pandemic led to a surge in technology demand among older adults, especially in areas like medical consultation, online socialization, and health management, further highlighting the importance and challenges of technology. Health risks and social isolation have compelled older adults to rely on technology for daily activities, accelerating its adoption and application within this demographic. This phenomenon has made technology acceptance a critical issue, driving societal and academic focus on the study of technology acceptance among older adults.

The flow of knowledge at the level of high-output disciplines and journals, along with the primary publishing outlets, indicates the highly interdisciplinary nature of research into older adults’ technology acceptance. This reflects the complexity and breadth of issues related to older adults’ technology acceptance, necessitating the integration of multidisciplinary knowledge and approaches. Currently, research is primarily focused on medical health and human-computer interaction, demonstrating academic interest in improving health and quality of life for older adults and addressing the urgent needs related to their interactions with technology. In the field of medical health, research aims to provide advanced and innovative healthcare technologies and services to meet the challenges of an aging population while improving the quality of life for older adults (Abdi et al. 2020 ; Wilson et al. 2021 ). In the field of human-computer interaction, research is focused on developing smarter and more user-friendly interaction models to meet the needs of older adults in the digital age, enabling them to actively participate in social activities and enjoy a higher quality of life (Sayago, 2019 ). These studies are crucial for addressing the challenges faced by aging societies, providing increased support and opportunities for the health, welfare, and social participation of older adults.

Discussion on research power (RQ2)

This study analyzes leading countries and collaboration networks, core institutions and authors, revealing the global research landscape and distribution of research strength in the field of older adults’ technology acceptance, and presents quantitative data on global research trends. From the analysis of country distribution and collaborations, China and the USA hold dominant positions in this field, with developed countries like the UK, Germany, Italy, and the Netherlands also excelling in international cooperation and research influence. The significant investment in technological research and the focus on the technological needs of older adults by many developed countries reflect their rapidly aging societies, policy support, and resource allocation.

China is the only developing country that has become a major contributor in this field, indicating its growing research capabilities and high priority given to aging societies and technological innovation. Additionally, China has close collaborations with countries such as USA, the UK, and Malaysia, driven not only by technological research needs but also by shared challenges and complementarities in aging issues among these nations. For instance, the UK has extensive experience in social welfare and aging research, providing valuable theoretical guidance and practical experience. International collaborations, aimed at addressing the challenges of aging, integrate the strengths of various countries, advancing in-depth and widespread development in the research of technology acceptance among older adults.

At the institutional and author level, City University of Hong Kong leads in publication volume, with research teams led by Chan and Chen demonstrating significant academic activity and contributions. Their research primarily focuses on older adults’ acceptance and usage behaviors of various technologies, including smartphones, smart wearables, and social robots (Chen et al. 2015 ; Li et al. 2019 ; Ma et al. 2016 ). These studies, targeting specific needs and product characteristics of older adults, have developed new models of technology acceptance based on existing frameworks, enhancing the integration of these technologies into their daily lives and laying a foundation for further advancements in the field. Although Tilburg University has a smaller publication output, it holds significant influence in the field of older adults’ technology acceptance. Particularly, the high citation rate of Peek’s studies highlights their excellence in research. Peek extensively explored older adults’ acceptance and usage of home care technologies, revealing the complexity and dynamics of their technology use behaviors. His research spans from identifying systemic influencing factors (Peek et al. 2014 ; Peek et al. 2016 ), emphasizing familial impacts (Luijkx et al. 2015 ), to constructing comprehensive models (Peek et al. 2017 ), and examining the dynamics of long-term usage (Peek et al. 2019 ), fully reflecting the evolving technology landscape and the changing needs of older adults. Additionally, the ongoing contributions of researchers like Ziefle, Rogers, and Wouters in the field of older adults’ technology acceptance demonstrate their research influence and leadership. These researchers have significantly enriched the knowledge base in this area with their diverse perspectives. For instance, Ziefle has uncovered the complex attitudes of older adults towards technology usage, especially the trade-offs between privacy and security, and how different types of activities affect their privacy needs (Maidhof et al. 2023 ; Mujirishvili et al. 2023 ; Schomakers and Ziefle 2023 ; Wilkowska et al. 2022 ), reflecting a deep exploration and ongoing innovation in the field of older adults’ technology acceptance.

Discussion on knowledge base and thematic progress (RQ3)

Through co-citation analysis and systematic review of seminal literature, this study reveals the knowledge foundation and thematic progress in the field of older adults’ technology acceptance. Co-citation networks and cluster analyses illustrate the structural themes of the research, delineating the differentiation and boundaries within this field. Additionally, burst detection analysis offers a valuable perspective for understanding the thematic evolution in the field of technology acceptance among older adults. The development and innovation of theoretical models are foundational to this research. Researchers enhance the explanatory power of constructed models by deepening and expanding existing technology acceptance theories to address theoretical limitations. For instance, Heerink et al. ( 2010 ) modified and expanded the UTAUT model by integrating functional assessment and social interaction variables to create the almere model. This model significantly enhances the ability to explain the intentions of older users in utilizing assistive social agents and improves the explanation of actual usage behaviors. Additionally, Chen and Chan ( 2014 ) extended the TAM to include age-related health and capability features of older adults, creating the STAM, which substantially improves predictions of older adults’ technology usage behaviors. Personal attributes, health and capability features, and facilitating conditions have a direct impact on technology acceptance. These factors more effectively predict older adults’ technology usage behaviors than traditional attitudinal factors.

With the advancement of technology and the application of emerging technologies, new research topics have emerged, increasingly focusing on older adults’ acceptance and use of these technologies. Prior to this, the study by Mitzner et al. ( 2010 ) challenged the stereotype of older adults’ conservative attitudes towards technology, highlighting the central roles of usability and usefulness in the technology acceptance process. This discovery laid an important foundation for subsequent research. Research fields such as “smart home technology,” “social life,” and “customer service” are emerging, indicating a shift in focus towards the practical and social applications of technology in older adults’ lives. Research not only focuses on the technology itself but also on how these technologies integrate into older adults’ daily lives and how they can improve the quality of life through technology. For instance, studies such as those by Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ) have explored factors influencing older adults’ use of smartphones, mHealth, and smart wearable devices.

Furthermore, the diversification of research methodologies and innovation in evaluation techniques, such as the use of mixed methods, structural equation modeling (SEM), and neural network (NN) approaches, have enhanced the rigor and reliability of the findings, enabling more precise identification of the factors and mechanisms influencing technology acceptance. Talukder et al. ( 2020 ) employed an effective multimethodological strategy by integrating SEM and NN to leverage the complementary strengths of both approaches, thus overcoming their individual limitations and more accurately analyzing and predicting older adults’ acceptance of wearable health technologies (WHT). SEM is utilized to assess the determinants’ impact on the adoption of WHT, while neural network models validate SEM outcomes and predict the significance of key determinants. This combined approach not only boosts the models’ reliability and explanatory power but also provides a nuanced understanding of the motivations and barriers behind older adults’ acceptance of WHT, offering deep research insights.

Overall, co-citation analysis of the literature in the field of older adults’ technology acceptance has uncovered deeper theoretical modeling and empirical studies on emerging technologies, while emphasizing the importance of research methodological and evaluation innovations in understanding complex social science issues. These findings are crucial for guiding the design and marketing strategies of future technology products, especially in the rapidly growing market of older adults.

Discussion on research hotspots and evolutionary trends (RQ4)

By analyzing core keywords, we can gain deep insights into the hot topics, evolutionary trends, and quality distribution of research in the field of older adults’ technology acceptance. The frequent occurrence of the keywords “TAM” and “UTAUT” indicates that the applicability and theoretical extension of existing technology acceptance models among older adults remain a focal point in academia. This phenomenon underscores the enduring influence of the studies by Davis ( 1989 ) and Venkatesh et al. ( 2003 ), whose models provide a robust theoretical framework for explaining and predicting older adults’ acceptance and usage of emerging technologies. With the widespread application of artificial intelligence (AI) and big data technologies, these theoretical models have incorporated new variables such as perceived risk, trust, and privacy issues (Amin et al. 2024 ; Chen et al. 2024 ; Jing et al. 2024b ; Seibert et al. 2021 ; Wang et al. 2024b ), advancing the theoretical depth and empirical research in this field.

Keyword co-occurrence cluster analysis has revealed multiple research hotspots in the field, including factors influencing technology adoption, interactive experiences between older adults and assistive technologies, the application of mobile health technology in health management, and technology-assisted home care. These studies primarily focus on enhancing the quality of life and health management of older adults through emerging technologies, particularly in the areas of ambient assisted living, smart health monitoring, and intelligent medical care. In these domains, the role of AI technology is increasingly significant (Qian et al. 2021 ; Ho 2020 ). With the evolution of next-generation information technologies, AI is increasingly integrated into elder care systems, offering intelligent, efficient, and personalized service solutions by analyzing the lifestyles and health conditions of older adults. This integration aims to enhance older adults’ quality of life in aspects such as health monitoring and alerts, rehabilitation assistance, daily health management, and emotional support (Lee et al. 2023 ). A survey indicates that 83% of older adults prefer AI-driven solutions when selecting smart products, demonstrating the increasing acceptance of AI in elder care (Zhao and Li 2024 ). Integrating AI into elder care presents both opportunities and challenges, particularly in terms of user acceptance, trust, and long-term usage effects, which warrant further exploration (Mhlanga 2023 ). These studies will help better understand the profound impact of AI technology on the lifestyles of older adults and provide critical references for optimizing AI-driven elder care services.

The Time-zone evolution mapping and burst keyword analysis further reveal the evolutionary trends of research hotspots. Early studies focused on basic technology acceptance models and user perceptions, later expanding to include quality of life and health management. In recent years, research has increasingly focused on cutting-edge technologies such as virtual reality, telehealth, and human-robot interaction, with a concurrent emphasis on the user experience of older adults. This evolutionary process demonstrates a deepening shift from theoretical models to practical applications, underscoring the significant role of technology in enhancing the quality of life for older adults. Furthermore, the strategic coordinate mapping analysis clearly demonstrates the development and mutual influence of different research themes. High centrality and density in the themes of Usage Experience and Assisted Living Technology indicate their mature research status and significant impact on other themes. The themes of Smart Devices, Theoretical Models, and Mobile Health Applications demonstrate self-contained research trends. The themes of Human-Robot Interaction, Characteristics of the Elderly, and Research Methods are not yet mature, but they hold potential for development. Themes of Digital Healthcare Technology, Psychological Factors, and Socio-Cultural Factors are closely related to other themes, displaying core immaturity but significant potential.

In summary, the research hotspots in the field of older adults’ technology acceptance are diverse and dynamic, demonstrating the academic community’s profound understanding of how older adults interact with technology across various life contexts and needs. Under the influence of AI and big data, research should continue to focus on the application of emerging technologies among older adults, exploring in depth how they adapt to and effectively use these technologies. This not only enhances the quality of life and healthcare experiences for older adults but also drives ongoing innovation and development in this field.

Research agenda

Based on the above research findings, to further understand and promote technology acceptance and usage among older adults, we recommend future studies focus on refining theoretical models, exploring long-term usage, and assessing user experience in the following detailed aspects:

Refinement and validation of specific technology acceptance models for older adults: Future research should focus on developing and validating technology acceptance models based on individual characteristics, particularly considering variations in technology acceptance among older adults across different educational levels and cultural backgrounds. This includes factors such as age, gender, educational background, and cultural differences. Additionally, research should examine how well specific technologies, such as wearable devices and mobile health applications, meet the needs of older adults. Building on existing theoretical models, this research should integrate insights from multiple disciplines such as psychology, sociology, design, and engineering through interdisciplinary collaboration to create more accurate and comprehensive models, which should then be validated in relevant contexts.

Deepening the exploration of the relationship between long-term technology use and quality of life among older adults: The acceptance and use of technology by users is a complex and dynamic process (Seuwou et al. 2016 ). Existing research predominantly focuses on older adults’ initial acceptance or short-term use of new technologies; however, the impact of long-term use on their quality of life and health is more significant. Future research should focus on the evolution of older adults’ experiences and needs during long-term technology usage, and the enduring effects of technology on their social interactions, mental health, and life satisfaction. Through longitudinal studies and qualitative analysis, this research reveals the specific needs and challenges of older adults in long-term technology use, providing a basis for developing technologies and strategies that better meet their requirements. This understanding aids in comprehensively assessing the impact of technology on older adults’ quality of life and guiding the optimization and improvement of technological products.

Evaluating the Importance of User Experience in Research on Older Adults’ Technology Acceptance: Understanding the mechanisms of information technology acceptance and use is central to human-computer interaction research. Although technology acceptance models and user experience models differ in objectives, they share many potential intersections. Technology acceptance research focuses on structured prediction and assessment, while user experience research concentrates on interpreting design impacts and new frameworks. Integrating user experience to assess older adults’ acceptance of technology products and systems is crucial (Codfrey et al. 2022 ; Wang et al. 2019 ), particularly for older users, where specific product designs should emphasize practicality and usability (Fisk et al. 2020 ). Researchers need to explore innovative age-appropriate design methods to enhance older adults’ usage experience. This includes studying older users’ actual usage preferences and behaviors, optimizing user interfaces, and interaction designs. Integrating feedback from older adults to tailor products to their needs can further promote their acceptance and continued use of technology products.

Conclusions

This study conducted a systematic review of the literature on older adults’ technology acceptance over the past decade through bibliometric analysis, focusing on the distribution power, research power, knowledge base and theme progress, research hotspots, evolutionary trends, and quality distribution. Using a combination of quantitative and qualitative methods, this study has reached the following conclusions:

Technology acceptance among older adults has become a hot topic in the international academic community, involving the integration of knowledge across multiple disciplines, including Medical Informatics, Health Care Sciences Services, and Ergonomics. In terms of journals, “PSYCHOLOGY, EDUCATION, HEALTH” represents a leading field, with key publications including Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction . These journals possess significant academic authority and extensive influence in the field.

Research on technology acceptance among older adults is particularly active in developed countries, with China and USA publishing significantly more than other nations. The Netherlands leads in high average citation rates, indicating the depth and impact of its research. Meanwhile, the UK stands out in terms of international collaboration. At the institutional level, City University of Hong Kong and The University of Hong Kong in China are in leading positions. Tilburg University in the Netherlands demonstrates exceptional research quality through its high average citation count. At the author level, Chen from China has the highest number of publications, while Peek from the Netherlands has the highest average citation count.

Co-citation analysis of references indicates that the knowledge base in this field is divided into three main categories: theoretical model deepening, emerging technology applications, and research methods and evaluation. Seminal literature focuses on four areas: specific technology use by older adults, expansion of theoretical models of technology acceptance, information technology adoption behavior, and research perspectives. Research themes have evolved from initial theoretical deepening and analysis of influencing factors to empirical studies on individual factors and emerging technologies.

Keyword analysis indicates that TAM and UTAUT are the most frequently occurring terms, while “assistive technology” and “virtual reality” are focal points with high frequency and centrality. Keyword clustering analysis reveals that research hotspots are concentrated on the influencing factors of technology adoption, human-robot interaction experiences, mobile health management, and technology for aging in place. Time-zone evolution mapping and burst keyword analysis have revealed the research evolution from preliminary exploration of influencing factors, to enhancements in quality of life and health management, and onto advanced technology applications and deepening of theoretical models. Furthermore, analysis of research quality distribution indicates that Usage Experience and Assisted Living Technology have become core topics, while Smart Devices, Theoretical Models, and Mobile Health Applications point towards future research directions.

Through this study, we have systematically reviewed the dynamics, core issues, and evolutionary trends in the field of older adults’ technology acceptance, constructing a comprehensive Knowledge Mapping of the domain and presenting a clear framework of existing research. This not only lays the foundation for subsequent theoretical discussions and innovative applications in the field but also provides an important reference for relevant scholars.

Limitations

To our knowledge, this is the first bibliometric analysis concerning technology acceptance among older adults, and we adhered strictly to bibliometric standards throughout our research. However, this study relies on the Web of Science Core Collection, and while its authority and breadth are widely recognized, this choice may have missed relevant literature published in other significant databases such as PubMed, Scopus, and Google Scholar, potentially overlooking some critical academic contributions. Moreover, given that our analysis was confined to literature in English, it may not reflect studies published in other languages, somewhat limiting the global representativeness of our data sample.

It is noteworthy that with the rapid development of AI technology, its increasingly widespread application in elderly care services is significantly transforming traditional care models. AI is profoundly altering the lifestyles of the elderly, from health monitoring and smart diagnostics to intelligent home systems and personalized care, significantly enhancing their quality of life and health care standards. The potential for AI technology within the elderly population is immense, and research in this area is rapidly expanding. However, due to the restrictive nature of the search terms used in this study, it did not fully cover research in this critical area, particularly in addressing key issues such as trust, privacy, and ethics.

Consequently, future research should not only expand data sources, incorporating multilingual and multidatabase literature, but also particularly focus on exploring older adults’ acceptance of AI technology and its applications, in order to construct a more comprehensive academic landscape of older adults’ technology acceptance, thereby enriching and extending the knowledge system and academic trends in this field.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/6K0GJH .

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This research was supported by the Social Science Foundation of Shaanxi Province in China (Grant No. 2023J014).

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Xianru Shang, Zijian Liu, Chen Gong, Zhigang Hu & Yuexuan Wu

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Shang, X., Liu, Z., Gong, C. et al. Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023. Humanit Soc Sci Commun 11 , 1115 (2024). https://doi.org/10.1057/s41599-024-03658-2

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