features of research design pdf

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism. Run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, November 20). What Is a Research Design | Types, Guide & Examples. Scribbr. Retrieved June 12, 2024, from https://www.scribbr.com/methodology/research-design/

Is this article helpful?

Shona McCombes

Other students also liked, guide to experimental design | overview, steps, & examples, how to write a research proposal | examples & templates, ethical considerations in research | types & examples, what is your plagiarism score.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Grad Med Educ
• v.8(1); 2016 Feb

Research Design Considerations

Associated data.

Editor's Note: The online version of this article contains references and resources for further reading and the authors' professional information.

The Challenge

“I'd really like to do a survey” or “Let's conduct some interviews” might sound like reasonable starting points for a research project. However, it is crucial that researchers examine their philosophical assumptions and those underpinning their research questions before selecting data collection methods. Philosophical assumptions relate to ontology, or the nature of reality, and epistemology, the nature of knowledge. Alignment of the researcher's worldview (ie, ontology and epistemology) with methodology (research approach) and methods (specific data collection, analysis, and interpretation tools) is key to quality research design. This Rip Out will explain philosophical differences between quantitative and qualitative research designs and how they affect definitions of rigorous research.

What Is Known

Worldviews offer different beliefs about what can be known and how it can be known, thereby shaping the types of research questions that are asked, the research approach taken, and ultimately, the data collection and analytic methods used. Ontology refers to the question of “What can we know?” Ontological viewpoints can be placed on a continuum: researchers at one end believe that an observable reality exists independent of our knowledge of it, while at the other end, researchers believe that reality is subjective and constructed, with no universal “truth” to be discovered. 1,2 Epistemology refers to the question of “How can we know?” 3 Epistemological positions also can be placed on a continuum, influenced by the researcher's ontological viewpoint. For example, the positivist worldview is based on belief in an objective reality and a truth to be discovered. Therefore, knowledge is produced through objective measurements and the quantitative relationships between variables. 4 This might include measuring the difference in examination scores between groups of learners who have been exposed to 2 different teaching formats, in order to determine whether a particular teaching format influenced the resulting examination scores.

In contrast, subjectivists (also referred to as constructionists or constructivists ) are at the opposite end of the continuum, and believe there are multiple or situated realities that are constructed in particular social, cultural, institutional, and historical contexts. According to this view, knowledge is created through the exploration of beliefs, perceptions, and experiences of the world, often captured and interpreted through observation, interviews, and focus groups. A researcher with this worldview might be interested in exploring the perceptions of students exposed to the 2 teaching formats, to better understand how learning is experienced in the 2 settings. It is crucial that there is alignment between ontology (what can we know?), epistemology (how can we know it?), methodology (what approach should be used?), and data collection and analysis methods (what specific tools should be used?). 5

Key Differences in Qualitative and Quantitative Approaches

Use of theory.

Quantitative approaches generally test theory, while qualitative approaches either use theory as a lens that shapes the research design or generate new theories inductively from their data. 4

Use of Logic

Quantitative approaches often involve deductive logic, starting off with general arguments of theories and concepts that result in data points. 4 Qualitative approaches often use inductive logic or both inductive and deductive logic, start with the data, and build up to a description, theory, or explanatory model. 4

Purpose of Results

Quantitative approaches attempt to generalize findings; qualitative approaches pay specific attention to particular individuals, groups, contexts, or cultures to provide a deep understanding of a phenomenon in local context. 4

Establishing Rigor

Quantitative researchers must collect evidence of validity and reliability. Some qualitative researchers also aim to establish validity and reliability. They seek to be as objective as possible through techniques, including cross-checking and cross-validating sources during observations. 6 Other qualitative researchers have developed specific frameworks, terminology, and criteria on which qualitative research should be evaluated. 6,7 For example, the use of credibility, transferability, dependability, and confirmability as criteria for rigor seek to establish the accuracy, trustworthiness, and believability of the research, rather than its validity and reliability. 8 Thus, the framework of rigor you choose will depend on your chosen methodology (see “Choosing a Qualitative Research Approach” Rip Out).

View of Objectivity

A goal of quantitative research is to maintain objectivity, in other words, to reduce the influence of the researcher on data collection as much as possible. Some qualitative researchers also attempt to reduce their own influence on the research. However, others suggest that these approaches subscribe to positivistic ideals, which are inappropriate for qualitative research, 6,9,10 as researchers should not seek to eliminate the effects of their influence on the study but to understand them through reflexivity . 11 Reflexivity is an acknowledgement that, to make sense of the social world, a researcher will inevitably draw on his or her own values, norms, and concepts, which prevent a totally objective view of the social world. 12

Sampling Strategies

Quantitative research favors using large, randomly generated samples, especially if the intent of the research is to generalize to other populations. 6 Instead, qualitative research often focuses on participants who are likely to provide rich information about the study questions, known as purposive sampling . 6

How You Can Start TODAY

• Consider how you can best address your research problem and what philosophical assumptions you are making.
• Consider your ontological and epistemological stance by asking yourself: What can I know about the phenomenon of interest? How can I know what I want to know? W hat approach should I use and why? Answers to these questions might be relatively fixed but should be flexible enough to guide methodological choices that best suit different research problems under study. 5
• Select an appropriate sampling strategy. Purposive sampling is often used in qualitative research, with a goal of finding information-rich cases, not to generalize. 6
• Be reflexive: Examine the ways in which your history, education, experiences, and worldviews have affected the research questions you have selected and your data collection methods, analyses, and writing. 13

How You Can Start TODAY—An Example

Let's assume that you want to know about resident learning on a particular clinical rotation. Your initial thought is to use end-of-rotation assessment scores as a way to measure learning. However, these assessments cannot tell you how or why residents are learning. While you cannot know for sure that residents are learning, consider what you can know—resident perceptions of their learning experiences on this rotation.

Next, you consider how to go about collecting this data—you could ask residents about their experiences in interviews or watch them in their natural settings. Since you would like to develop a theory of resident learning in clinical settings, you decide to use grounded theory as a methodology, as you believe asking residents about their experience using in-depth interviews is the best way for you to elicit the information you are seeking. You should also do more research on grounded theory by consulting related resources, and you will discover that grounded theory requires theoretical sampling. 14,15 You also decide to use the end-of-rotation assessment scores to help select your sample.

Since you want to know how and why students learn, you decide to sample extreme cases of students who have performed well and poorly on the end-of-rotation assessments. You think about how your background influences your standpoint about the research question: Were you ever a resident? How did you score on your end-of-rotation assessments? Did you feel this was an accurate representation of your learning? Are you a clinical faculty member now? Did your rotations prepare you well for this role? How does your history shape the way you view the problem? Seek to challenge, elaborate, and refine your assumptions throughout the research.

As you proceed with the interviews, they trigger further questions, and you then decide to conduct interviews with faculty members to get a more complete picture of the process of learning in this particular resident clinical rotation.

What You Can Do LONG TERM

• Familiarize yourself with published guides on conducting and evaluating qualitative research. 5,16–18 There is no one-size-fits-all formula for qualitative research. However, there are techniques for conducting your research in a way that stays true to the traditions of qualitative research.
• Consider the reporting style of your results. For some research approaches, it would be inappropriate to quantify results through frequency or numerical counts. 19 In this case, instead of saying “5 respondents reported X,” you might consider “respondents who reported X described Y.”
• Review the conventions and writing styles of articles published with a methodological approach similar to the one you are considering. If appropriate, consider using a reflexive writing style to demonstrate understanding of your own role in shaping the research. 6

Supplementary Material

Comparing Types of Research Designs

• First Online: 10 November 2021

Cite this chapter

• Stefan Hunziker 3 &
• Michael Blankenagel 3  

3396 Accesses

Every researcher chooses the research design that is best suited to generate the envisioned conclusions they like to draw. There are several types of research designs. Each is especially well suited to generate a specific type of conclusion. Commonly used research designs in business and management are design science, action research, single case, multiple case, cross-sectional, longitudinal, experimental and literature review research. The specific characteristics depicting these research design’s idiosyncrasies, differences, and fields of application of these research designs are gathered in a synopsis. Also, we pose questions that guide researchers to the research design, matching their objectives and personal preferences. This chapter also addresses the popular terms “triangulation” and “mixed methods” and puts them into the context of research design.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Asenahabin, B. M. (2019). Basics of research design: A guide to selecting appropriate research design. International Journal of Contemporary Applied Researches, 6 (5), 76–89.

Google Scholar  

Burke-Johnson, R., Onwueegbuzie, A., & Turner, L. (2007). Towards a definition of mixed methods research. Journal of Mixed Methods Research, 1 (2), 112–133.

Article   Google Scholar  

Creswell, J. (2014). Research design: Qualitative, quantitative, and mixed methods approaches . SAGE.

Dresch, A., Lacerda, D., & Antunes, J. (2014). Design science research: A method for science and technology advancement . Retrieved June 10, 2021, from https://www.semanticscholar.org/paper/bf2a9807a0d9be8c5c11684786ae3129f3e8003e .

Gratton, C., & Jones, I. (2010). Research methods for sports studies (2nd ed.). Routledge.

Hakim, C. (2000). Research design: Successful designs in social and economic research . Routledge.

Jongbo, O. C. (2014). The role of research design in a purpose driven enquiry. Review of Public Administration and Management, 3 (6), 87–94.

Trochim, W., Donnelly, J., & Arora, K. (2015). Research methods: The essential knowledge base. CENGAGE Learning.

Download references

Author information

Authors and affiliations.

Wirtschaft/IFZ – Campus Zug-Rotkreuz, Hochschule Luzern, Zug-Rotkreuz, Zug , Switzerland

Stefan Hunziker & Michael Blankenagel

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Stefan Hunziker .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature

About this chapter

Hunziker, S., Blankenagel, M. (2021). Comparing Types of Research Designs. In: Research Design in Business and Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-34357-6_5

Download citation

DOI : https://doi.org/10.1007/978-3-658-34357-6_5

Published : 10 November 2021

Publisher Name : Springer Gabler, Wiesbaden

Print ISBN : 978-3-658-34356-9

Online ISBN : 978-3-658-34357-6

eBook Packages : Business and Economics (German Language)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

CHAPTER FIVE RESEARCH DESIGN AND METHODOLOGY 5.1. Introduction Citation: Lelissa TB (2018); Research Methodology; University of South Africa, PHD Thesis

• December 2018

• University of South Africa

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations

• Chalchissa Amantie

• Abdul Rehman

• Asma Abdul Khaliq
• Engelica Abriam
• Joan Belvistre
• Alyssa Marie Denna
• Marilyn Gaoat

• Jeff B. Sagala

• Newman Wadesango
• Alice Nyandoro
• Lovemore Sitsha

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

Free AI Presentation Maker for Generating Projects in Minutes

• Generate ready-to-use presentations from a text prompt.
• Select a style and Visme’s AI Presentation Maker will generate text, images, and icon.
• Customize your presentation with a library of royalty-free photos, videos, & graphics.

Generate a presentation with AI

Brought to you by Visme

A leading visual communication platform empowering 27,500,000 users and top brands.

Presentations Engineered With Visme’s AI Presentation Maker

Ai presentation maker prompt 1.

Craft a presentation outlining a leading company’s cutting-edge innovations in AI-powered hardware, emphasizing their impact on enhancing workplace productivity and efficiency.

AI Presentation Maker Prompt 2

Generate a comprehensive presentation highlighting the latest digital marketing trends, focusing on strategies for enhancing brand visibility and customer engagement across diverse platforms.

AI Presentation Maker Prompt 3

Create a detailed presentation elucidating a company’s diversified investment portfolio, emphasizing its robust performance, risk mitigation strategies, and the potential for sustainable long-term growth.

AI Presentation Maker Prompt 4

Develop a compelling presentation showcasing a company’s groundbreaking medical devices and software solutions, emphasizing their role in revolutionizing patient care, treatment efficacy, and healthcare accessibility worldwide.

How it works

How to generate AI presentations with Visme

Save time and create beautiful designs quickly with Visme AI. Available inside the Visme template library, this AI Powerpoint generator is ready to receive your prompts and generate stunning ready-to-use presentations in minutes.

• Log in to the Visme dashboard, and open the template library by clicking on Create New button -> Project -> Presentations. Inside the template library, scroll down and click on the Generate with AI option.
• In the popup that opens, type in a prompt and describe in detail what aspects your presentation should feature. If you don’t provide enough information, chatbot will ask you follow-up questions.
• Visme Chatbot will suggest template styles; choose the most relevant for your presentation, and wait for the AI to create the design. Preview, regenerate or open your project in the Visme editor.
• Customize your project in Visme: Pick a color theme or create your own, edit text, and use assets from Visme’s royalty-free library of photos, videos, and graphics, or create your own with AI tools.

Features of the AI Presentations Maker

Ready-to-use presentations in minutes.

Starting is often the hardest part of a project. Visme’s free AI presentation maker helps you overcome this block and generates results within minutes. Create AI PowerPoint online presentations quickly with a good first draft that is ready to use with minimal or no customization.

Customize every part of your presentation

Visme editor is easy to use and offers you an array of customization options. Change the color theme of your AI-generated presentation, text, fonts, add images, videos and graphics from Visme royalty-free library of assets or generate new ones with AI image generator, AI image touchup tools, or add your own. For more advanced customization, add data visualizations, connect them to live data, or create your own visuals.

Add your branding

Stay on-brand even with AI-generated presentations. Quickly and easily set up your brand kit using AI-powered Visme Brand Wizard or set it up manually. Use your brand colors and fonts in AI-generated presentations. Add your logo and upload your brand assets to make a presentation match your company’s branding.

Download, share or schedule your presentation

Share your presentations generated with Visme AI Designer in many ways. Download them in various formats, including PPTX, PDF and HTML5, present online, share on social media or schedule them to be published as posts on your social media channels. Additionally, you can share your presentations as private projects with a password entry.

More than just an AI Presentation Maker

Beautify your content

Unique Elements & Graphics

Browse through our library of customizable, one-of-a-kind graphics, widgets and design assets like icons, shapes, illustrations and more to accompany your AI-generated presentations.

Visualize your data

Charts & Graphs

Choose from different chart types and create pie charts, bar charts, donut charts, pyramid charts, Mekko charts, radar charts and much more.

Make it engaging

Interactivity

Share AI-generated presentations online with animated and interactive elements to grab your audience’s attention and promote your business.

More AI tools in Visme

Ai image generator.

The Visme AI Image generator will automatically create any image or graphic. All you need to do is write a prompt and let AI magic do the rest.

Visme AI Writer helps you write, proofread, summarize and tone switch any type of text. If you’re missing content for a project, let AI Writer help you generate it.

Save yourself hours of work with AI Resize. This feature resizes your project canvas and adjusts all content to fit the new size within seconds.

AI TouchUp Tools

The Visme AI TouchUp Tools are a set of four image editing features that will help you change the appearance of your images inside any Visme project. Erase and replace objects that you don’t want in your photos.

The Brand Wizard

The AI-based Visme Brand Wizard populates your brand fonts and styles across a beautiful set of templates.

Make the most of Visme’s features

Choose the perfect visual from our extensive photo and video library . Search and find the ideal image or video using keywords relevant to the project. Drag and drop in your project and adjust as needed.

Incorporate 3D illustrations and icons into all sorts of content types to create amazing content for your business communication strategies. You won’t see these 3D designs anywhere else as they’re made by Visme designers.

When you share your Visme projects, they’ll display with a flipbook effect . Viewers can go from page to page by flipping the page like a digital magazine. If you don’t want the flipbook effect, you can disable it and share as a standard project.

Remove the background from an image to create a cutout and layer it over something else, maybe an AI-generated background. Erase elements of the image and swap them for other objects with AI-powered Erase & Replace feature.

Create scroll-stopping video and animation posts for social media and email communication. Embed projects with video and animation into your website landing page or create digital documents with multimedia resources.

With Visme, you can make, create and design hundreds of content types . We have templates for digital documents, infographics, social media graphics, posters, banners, wireframes, whiteboards, flowcharts.

Design and brainstorm collaboratively with your team on the Visme whiteboard . Build mind maps and flowcharts easily during online planning and strategy sessions. Save whiteboards as meeting minutes and ongoing notes for projects.

Edit your images , photos, and AI image-generated graphics with our integrated editing tools. On top of the regular editing features like saturation and blur, we have 3 AI-based editing features. With these tools, you can unblur an image, expand it without losing quality and erase an object from it.

Frequently Asked Questions (FAQs)

How can i get better results with the ai presentations maker.

Like any AI generator from a text tool, the prompt is everything. To get better results with the AI Presentation maker, you need better prompts. Write the prompt to be as detailed as possible. Include all the content topics you want the presentation to cover. As for style elements, there’s no need to include it in the prompt. Focus on choosing the style that you like from the Chatbot suggestions. Try to select the style that already features the color palette and shapes that you like. AI will change icons and photos based on text it generates.

How many AI Presentations can I generate?

Visme AI Presentation Maker is available in all plans and works on a per-credit basis. Every free account gets 10 credits, Starter accounts get 200, Pro gets 500 and Enterprise is unlimited. Every design generation costs 2 credits and usage of other AI tools costs 1 credit.

Is the Visme AI Designer a third-party API?

No, Visme AI Presentation maker was developed in-house and is a unique tool. However, it does use third-party APIs: ChatGPT and Unsplash.

Are the AI-generated presentations I make copyright-free?

All designs you create with AI Presentation are copyright and royalty-free. You can use them both for personal and commercial use without any problems.

What can Visme AI Designer do?

Visme’s AI design generator can:

• Generate full designs for various content types, including presentations, documents, printables, and social media graphics. Click here to view the full list of document, printable, and social media graphics subcategories.
• Follow your instructions for the text you want in your projects, although not word for word.
• Adapt photos and icons to complement the generated text.
• Create charts, graphs, and tables.
• Handle one project at a time.
• Include animations in projects only if the selected style features animation.
• Generate designs with a maximum length of 10 pages.

What can’t Visme AI Designer do?

Visme’s AI design generator can’t:

• Generate infographics, charts/graphs, whiteboards, web graphics, videos, or GIFs.
• Reproduce your text verbatim.
• Customize based on your specifications for color, shapes, graphics, and design style. Select a style that already resembles what you want in your project, and you can manually edit all design elements in the Visme editor.
• Create or modify diagrams, data widgets or infographics.
• Crawl external websites and gather information from them.
• Handle multiple projects at once.
• Generate designs more than 10 pages in length.