in depth research meaning

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Last Updated: Jun 27, 2023 Views: 2570

As researchers, it can be helpful to talk about different types of research with specific characteristics. There are many different types of research, but from a broad perspective, it can be helpful to think of research as falling into one of three categories.

Background Research

Background research is a kind of pre-research. Consulting tertiary or background sources like encyclopedias, dictionaries, or textbooks can help researchers gather basic or background information about a topic that they can leverage to design better searches later in their research. These sources are a great place to learn general information about a topic, including major movements or conversations happening in a discipline. Because a lot of information is summarized broadly in these sources, they are great for getting “caught up” on a topic but don’t include detailed or up-to-date information. Background research can help researchers narrow a topic and learn subject-specific keywords. Background resources often reference important scholars in a field.

Encyclopedias are valuable sources for pre-research, but usually shouldn’t be cited as evidence in your academic papers.

In-depth Research

After you have a good sense for your area of research and some context around your narrowed research, you can begin in-depth research for primary and secondary sources to find evidence to build your argument or thesis. In-depth research can look different depending on the kinds of resources you need. Some disciplines call for specific resources and techniques. For example, business research involves honed web research and specialized databases with financial data and analyst reports. Often, in-depth research includes searching article databases for scholarly journal articles on your topic. If you’re unsure where to start, you can always consult a reference librarian.

Remember that research isn’t a linear process: There’s nothing stopping you from going back to background research to fill in more information, then jumping back into in-depth research when you’re ready.

Original or Primary Research

Students and scholars conduct original research when they collect and analyze data. There are many categories of research within this broad category, including but not limited to: quantitative, qualitative, longitudinal, and experimental. These are the same studies researchers find as part of their in-depth research above- the difference is if you as a researcher are collecting and analyzing information, or finding the research done by others.

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Definition of in-depth

• all-embracing
• all-in [ chiefly British ]
• all-inclusive
• broad-gauge
• broad-gauged
• compendious
• comprehensive
• encyclopedic

Examples of in-depth in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'in-depth.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

1957, in the meaning defined above

Dictionary Entries Near in-depth

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Methodology

• Exploratory Research | Definition, Guide, & Examples

Exploratory Research | Definition, Guide, & Examples

Published on December 6, 2021 by Tegan George . Revised on November 20, 2023.

Exploratory research is a methodology approach that investigates research questions that have not previously been studied in depth.

Exploratory research is often qualitative and primary in nature. However, a study with a large sample conducted in an exploratory manner can be quantitative as well. It is also often referred to as interpretive research or a grounded theory approach due to its flexible and open-ended nature.

Table of contents

When to use exploratory research, exploratory research questions, exploratory research data collection, step-by-step example of exploratory research, exploratory vs. explanatory research, advantages and disadvantages of exploratory research, other interesting articles, frequently asked questions about exploratory research.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use this type of research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

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Exploratory research questions are designed to help you understand more about a particular topic of interest. They can help you connect ideas to understand the groundwork of your analysis without adding any preconceived notions or assumptions yet.

Here are some examples:

• What effect does using a digital notebook have on the attention span of middle schoolers?
• What factors influence mental health in undergraduates?
• What outcomes are associated with an authoritative parenting style?
• In what ways does the presence of a non-native accent affect intelligibility?
• How can the use of a grocery delivery service reduce food waste in single-person households?

Collecting information on a previously unexplored topic can be challenging. Exploratory research can help you narrow down your topic and formulate a clear hypothesis and problem statement , as well as giving you the “lay of the land” on your topic.

Data collection using exploratory research is often divided into primary and secondary research methods, with data analysis following the same model.

Primary research

In primary research, your data is collected directly from primary sources : your participants. There is a variety of ways to collect primary data.

Some examples include:

• Survey methodology: Sending a survey out to the student body asking them if they would eat vegan meals
• Focus groups: Compiling groups of 8–10 students and discussing what they think of vegan options for dining hall food
• Interviews: Interviewing students entering and exiting the dining hall, asking if they would eat vegan meals

Secondary research

In secondary research, your data is collected from preexisting primary research, such as experiments or surveys.

Some other examples include:

• Case studies : Health of an all-vegan diet
• Literature reviews : Preexisting research about students’ eating habits and how they have changed over time
• Online polls, surveys, blog posts, or interviews; social media: Have other schools done something similar?

For some subjects, it’s possible to use large- n government data, such as the decennial census or yearly American Community Survey (ACS) open-source data.

How you proceed with your exploratory research design depends on the research method you choose to collect your data. In most cases, you will follow five steps.

We’ll walk you through the steps using the following example.

Therefore, you would like to focus on improving intelligibility instead of reducing the learner’s accent.

Step 1: Identify your problem

The first step in conducting exploratory research is identifying what the problem is and whether this type of research is the right avenue for you to pursue. Remember that exploratory research is most advantageous when you are investigating a previously unexplored problem.

Step 2: Hypothesize a solution

The next step is to come up with a solution to the problem you’re investigating. Formulate a hypothetical statement to guide your research.

Step 3. Design your methodology

Next, conceptualize your data collection and data analysis methods and write them up in a research design.

Step 4: Collect and analyze data

Next, you proceed with collecting and analyzing your data so you can determine whether your preliminary results are in line with your hypothesis.

In most types of research, you should formulate your hypotheses a priori and refrain from changing them due to the increased risk of Type I errors and data integrity issues. However, in exploratory research, you are allowed to change your hypothesis based on your findings, since you are exploring a previously unexplained phenomenon that could have many explanations.

Step 5: Avenues for future research

Decide if you would like to continue studying your topic. If so, it is likely that you will need to change to another type of research. As exploratory research is often qualitative in nature, you may need to conduct quantitative research with a larger sample size to achieve more generalizable results.

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It can be easy to confuse exploratory research with explanatory research. To understand the relationship, it can help to remember that exploratory research lays the groundwork for later explanatory research.

Exploratory research investigates research questions that have not been studied in depth. The preliminary results often lay the groundwork for future analysis.

Explanatory research questions tend to start with “why” or “how”, and the goal is to explain why or how a previously studied phenomenon takes place.

Like any other research design , exploratory studies have their trade-offs: they provide a unique set of benefits but also come with downsides.

• It can be very helpful in narrowing down a challenging or nebulous problem that has not been previously studied.
• It can serve as a great guide for future research, whether your own or another researcher’s. With new and challenging research problems, adding to the body of research in the early stages can be very fulfilling.
• It is very flexible, cost-effective, and open-ended. You are free to proceed however you think is best.

Disadvantages

• It usually lacks conclusive results, and results can be biased or subjective due to a lack of preexisting knowledge on your topic.
• It’s typically not externally valid and generalizable, and it suffers from many of the challenges of qualitative research .
• Since you are not operating within an existing research paradigm, this type of research can be very labor-intensive.

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

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

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In-depth interviews in qualitative research: Not 'just a chat'

In-depth interview, that's just a chat', you might say. Well, no, it's not, and here's why, and when to use it.

Cathy Gibbons

What is an in-depth interview.

In-depth interviews are described by Fontana and Frey (2000) as a kind of interview that uses anything from structured questions to 'negotiated text', but they also describe it as open-ended and ethnographic. More helpfully, they say it is used as an attempt “to understand the complex behaviour of members of society without imposing any a-priori categorization that may limit the field of inquiry”. They also consider the establishment of a ‘human-to-human connection’, as fundamental to in-depth interviews.

Well, you might say, that’s still just chat, but a really long one, isn’t it? Well no.

According to Kvale and Brinkmann (2009), in-depth interviews are considered to be research conversations. As a genre of conversation, an in-depth interview has its own conventions and rules, distinct from a chat with a friend, a legal interrogation, a therapeutic session, or professional discussion. What makes them distinct is the purpose of the conversation. In qualitative research the purpose is to 'produce' knowledge, “is an interview where knowledge is constructed in the inter-action between the interviewer and the interviewee”. However there is much overlap and no hard and fast distinction between different forms of conversation.

So, ‘chatting’ around inconsequential topics (the state of traffic, whether you prefer tea or coffee) might genuinely be part of the forming and maintenance of rapport. However trust and genuine interview dialogue will be developed through human skills and behaviours that demonstrate that you are trustworthy, respectful of the knowledge and person(s) you are working with, genuinely want to hear what they have to say, see what they have to show you, and will be careful in your representation. These are skills that we all have at some level, but with practice can be honed to the point where you know when to ask a sensitive question, probe more deeply or return at a later point; can detect that there is more to be heard or you can move on; can select from a variety of questioning techniques; have sharp observation skills, and fundamentally, know how to actively listen.

It is probably apparent by now that in-depth interviews are time consuming and take some skill. However, as Guest, Namey & Mitchell say, “there is good reason for the pervasiveness of this method: it is versatile across a range of study topics, adaptable to challenging field conditions, and excellent for not just providing information but for generating understanding as well.” ( 2013 )

When do you use an in-depth interview?

Fontana and Frey (2020) call in-depth interviews ethnographic and open-ended. So in-depth interviews are suitable for the kind of topics where the researcher needs to be in the ‘field’ under examination and/or close to people the people who inhabit that field. Subjects that could require that kind of closeness include:

· socially sensitive topics, (such as bereavement, abuse of any kind, financial issues)

· marginalised and closed groups

· life-course or bibliographic accounts

· examining professional practice in detail

You may also choose to do in-depth interviews when access to field is limited, where there are elements of danger, such as gangs, criminal processes, dangerous or controlled workplaces with restricted access (diving, oil-rigs, operating theatres).

You might also choose to combine in-depth interviews with more traditional ethnographic techniques, such as observation, or with more creative and arts-based methods, where the co-construction of knowledge can be physically made manifest in ways beyond an academic report.

What’s the role of the researcher in an in-depth interview?

Acknowledging that subjective experience is valuable and that the researcher needs to be aware of their own subjectivities are givens in any qualitative research. The literature describes the involvement of the interviewer in research conversations in many ways, from ‘listen, don’t talk, (which might sit well with a more therapeutic approach), all the way to sharing personal opinions, likes/dislikes, which contribute to the co-construction of knowledge. Kvale and Brinkmann (2009) even discuss more challenging styles, where the interviewer freely expresses disagreement with interviewees. There is an element of personality and competence involved in this choice, but your particular research question should guide you across the spectrum of roles, from quiet researcher, to knowledgeable peer, or activist with a purpose of social change.

However there are four areas of consensus in researcher approach:

· Listen more than you talk

· Take time to develop genuine rapport

· Understand your purpose

· Don’t give advice

This is all probably good guidance for any kind of interview, but fail in the first of these two and you cannot claim to be using in-depth interviews in any methodological sense. As for not giving advice, you would need to have a good ethical and methodological rationale for why you might be asked for advice, and how you would handle that appropriately.

Do you need an interview guide for an in-depth interview?

Usually: as the Wallace foundation workbook suggests, you will need a guide with some sense of the questions you could ask, and the areas that you wish to cover (as well as a sampling strategy and thoughts on how you will make sense of your findings). However, that doesn’t mean you have to clutch it in your hand and read from it through-out your interviews.

Our blog on semi-structured interview guides recommends that you learn all of the questions in your topic guide/interview guide, and keep the guide near to hand. Certainly being able to glide seamlessly from question to question, topic to topic really helps keep interviews on track, when each participant may only cover different parts of the topic. However, it is knowing the purpose of your guide that is important, not the order of the questions or verbatim regurgitation of the questions. If you find forming questions difficult, why not have some generalised starters on your guide, along with purpose, and go from there? Our blog Talking naturally in qualitative research interviews has a whole section on questions to help you keep going with your in-depth interview.

What's the difference between in-depth, unstructured and structured interviews?

There are so many ways to describe interviews that it can appear a bit random, with authors like Flick (2015) , using labels that refer not just to the structure of the interview (e.g. semi-structured), but also to the people to be interviewed, their status relative to the context under discussion (e.g. expert, adult or child service user), and the linguistic form of the interview (e.g. narrative, and episodic). Then to add to the confusion, we throw in another term like ‘in-depth’.

In general, research interviews can be divided in to three kinds of structure:

· Structured

· Semi-structured

· Unstructured

In-depth interviews generally overlap the area between Unstructured and Semi-structured interviews. In Figure 1, the In-depth interviews circle barely skims the Structured interview circle. It is possible to use a structured interview instrument that is extremely detailed, wide-ranging and long. However, these are rare, as gathering such data is often better served by a questionnaire, and they are not in-depth in a qualitative methodological sense. When you find yourself choosing in-depth interviews, you are looking to generate a rich dialogue between you and your interviewee that will allow both of you to expore a topic in a free-flowing and informative way.

Whatever type of interviews you end up using for your qualitative research, Quirkos is a great way to transcribe them, with our automated transcription service , and analyse them with our simple qualitative coding and analysis tool . You can try both free of charge for 14 days, so register for a free trial and see if Quirkos can help you after your interviews!

References and Resources

Fontana, Andrea. and Frey, James H.  (2000) The interview; from structured questions to negotiated text. In Handbook of Qualitative Research , Eds. Norman K. Denzin , Yvonna S. Lincoln . Sage.

Flick, Uwe. (2015) Introducing Research Methodology: A Beginner's Guide to Doing a Research Project 2nd Ed. Sage.

Guest, G., Namey, E., & Mitchell, M. (2013). in-depth interviews. (Vols. 1-0). SAGE Publications, Ltd, https://doi.org/10.4135/9781506374680 [Accessed online 03 July 2023]

Kvale, Steinar (1996) InterViews: An introduction to research interviewing . Sage. Thousand Oaks. London.

Kvale, Steinar and Brinkmann, Svend (2009) ( 2014 ) InterViews: Learning the Craft of Qualitative Research Interviewing. Sage. Thousand Oaks. London.

Morris, A. (2015). A practical introduction to in-depth interviewing. SAGE Publications Ltd, https://doi.org/10.4135/9781473921344

The Wallace Foundation’s Knowledge Center, has useful material about many issues, including the arts, learning enrichment and school leadership. https://www.wallacefoundation.org/knowledge-center/pages/kc-results.aspx

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• Aug 22, 2023

In-depth Analysis: Explaining the advanced analysis tools and how to utilize them for deeper insight

Updated: Oct 15, 2023

In the realm of research, information is abundant, but extracting meaningful insights is the true challenge. This is where the power of in-depth analysis comes into play. In this article, we delve into the world of advanced analysis tools offered by Sourcely, designed to help researchers uncover hidden gems of knowledge and gain deeper insights from their sources. Join us as we demystify these tools and guide you on how to make the most of them for your research journey.

Understanding In-Depth Analysis: The Key to Unlocking Hidden Insights

In-depth analysis is the process of diving beneath the surface of information to extract deeper meaning, trends, patterns, and connections. With the exponential growth of data, the ability to analyze sources effectively becomes paramount, and this is where Sourcely's advanced analysis tools shine.

Exploring Advanced Analysis Tools: A Glimpse into Deeper Insights

Contextual Extraction: This tool allows you to extract relevant context from sources. It identifies keywords, phrases, and concepts, offering a snapshot of what the source covers. This feature is especially valuable when you need a quick overview of a source's main themes.

Sentiment Analysis: Understanding the sentiment of a source can be pivotal, especially in fields such as social sciences or market research. Sourcely's sentiment analysis tool gauges the emotional tone of a source, providing insights into its subjective stance.

Keyword Clustering: Often, sources cover multiple facets of a topic. Keyword clustering helps organize and group related terms, aiding in the identification of prevalent themes within a source.

Citation Analysis: Citation analysis sheds light on the influence and credibility of a source. By analyzing the citations a source has received, you can gauge its impact within the academic or professional community.

Utilizing Advanced Analysis Tools: A Step-by-Step Guide

Identify Your Objective: Define your research objective. Are you looking for trends, patterns, or sentiment analysis? Identifying your goal guides your use of specific tools.

Select the Source: Choose the source you wish to analyze. Sourcely's analysis tools can be applied to various types of sources, from research papers to news articles.

Apply the Tool: Depending on your objective, apply the appropriate analysis tool. For example, if you're interested in sentiment analysis, run the source through Sourcely's sentiment analysis tool.

Interpret the Results: Once the analysis is complete, review the results. Look for keywords, themes, or patterns that emerge. These insights can guide your research direction.

Combine Insights: In-depth analysis works best when combined with other research methods. Integrating the insights gained from analysis tools with your existing knowledge can lead to comprehensive conclusions.

Elevating Your Research with In-Depth Analysis

In-depth analysis isn't just about extracting data; it's about transforming data into knowledge. Sourcely's advanced analysis tools empower researchers to go beyond the surface and unearth insights that can drive impactful decisions, theories, and discoveries.

By incorporating in-depth analysis into your research workflow, you're adding a layer of depth and accuracy that can set your work apart. Whether you're a student, a professional, or a curious mind, Sourcely's advanced analysis tools are your companions in the quest for knowledge.

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In-Depth Interviewing

• First Online: 06 June 2021

Cite this chapter

• Natalie Osborne 3 &
• Deanna Grant-Smith 4  

Part of the book series: Cities Research Series ((CRS))

2746 Accesses

10 Citations

This chapter explores in-depth interviewing, a widely used method in qualitative research aimed at building a depth of understanding, rather than factual or abstract information. We give a brief account of structured interviews, but these have more in common with surveys and questionnaires than in-depth interviewing. Semi-structured interviews are interviews that follow a set of questions, allowing some flexibility in how questions are asked, and provide the researcher with the opportunity to ask clarifying and follow-up questions. Unstructured interviews are more flexible and open-ended. As such, they can be quite unpredictable and varied and are well suited to exploratory research and other research interested in meaning and experiences. There is a range of ethical considerations when using this method, including confidentiality establishing clear and reasonable expectations and offering appropriate reciprocity to research participants, and the potential of this method to cause harm, to both researcher and participants. In-depth interviewing is a powerful but demanding method for urban research; it is resource intensive and requires a lot of skills on the part of the researcher to design effective and ethical protocols and to generate meaning from complex, often messy, data.

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Osborne, N., Grant-Smith, D. (2021). In-Depth Interviewing. In: Baum, S. (eds) Methods in Urban Analysis. Cities Research Series. Springer, Singapore. https://doi.org/10.1007/978-981-16-1677-8_7

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Applying In-Depth Research and Analysis to Achieve Better Outcomes

Over the past 20 years, two of the domains to which I have applied my research and analysis skills are UX research and career exploration. I’ve noticed a lot of similarities between the approaches I use in these two domains to get the most desirable and effective outcomes.

• In UX research , the goal is to have the best possible impact on product design and innovation—to help product teams innovate, design, or improve a digital service or product that achieves the highest level of usability, usage, and user satisfaction.
• In career exploration , the goal is to identify the career that best suits a person, in which that person would thrive, excel, and achieve his or her full potential, maximizing personal fulfillment, and contributing to the benefit of the company, community, and the planet.

In both of these domains, the approach, methods, and tools you choose for research and analysis make a big difference in achieving the desired outcomes. My experience has taught me that in-depth research and analysis provide more optimal outcomes over the long term.

Unfortunately, research and analysis all too often just skim the surface. For example, a product manager might ask a researcher to evaluate an existing product that does not actually meet a user need. While doing this might seem more efficient in the short term, it tends to generate solutions that do not solve the real problem. Such solutions often require revision in the future, ultimately resulting in higher costs and wasting time, money, and energy.

In this article, I’ll share six keys to applying in-depth research and analysis to achieve better outcomes in User Experience and career exploration.

1. Dive deeply enough.

In both UX research and career exploration, it’s necessary to dive deep enough to gather foundational data and discover insights that can lead to truly innovative and effective long-term results—meaningful results that last instead of short-term patches that don’t solve a problem at a deep enough level. Short-term, quick approaches might initially seem more efficient. You might save time, energy, and money in the short term by doing a quicker evaluation. But the extra time, energy, and money you fail to invest up front often result in headaches, unsatisfactory solutions, and incessant adjustments in the future, leading to more wasted time, energy, and money.

Apply this adage: Go slow to go fast.

I would add: Go deep to go further.

In UX research —especially foundational research—it’s necessary to move beyond any current product or user-interface design. So, instead of evaluating the current user interface, you need to move past the existing solution to explore the underlying user needs that the product is trying to solve. To understand users’ underlying needs, take a step back and explore the problem more deeply. The current product may not address the user’s true needs. By investing some extra time and energy in foundational research, you can ensure that the product’s functionality and design meet users’ needs and are built on the right foundation.

Similarly, in career exploration , rather than evaluating a person’s current or past work—as most people or counselors tend to do—set the current work situation aside for the present so you can explore the underlying needs that work should meet for that person. What are the person’s values? What does that person love doing? What are his or her passions and interests? What are that person’s natural talents and strengths? What is that person’s unique operating manual—the person’s personality patterns.

When people do not like their work, that indicates their work is misaligned with their unique blueprint and operating manual. To help someone discover work they truly love, you must take the time to fully explore and understand the ingredients that would make a great career for that person— before considering the current or past careers. This is why, in my approach to career exploration, I don’t need to look at my clients’ resumes. Nor do I consider the types of careers that are out there before looking at what need the solution—that is, the career —is trying to solve.

This approach to discovering a person’s most fulfilling career is a bottom-up rather than a top-down approach, as the diagram in Figure 1 shows.

The process of discovering a person’s most fulfilling career comprises the following steps:

• Identify the person’s unique blueprint, or authentic self.
• Discover the person’s life purpose.
• Identify the career that is in alignment with your learnings from steps 1 and 2.

2. Expand the scope of research.

In the domains of both UX research and career exploration, you need to expand not only the depth, but also the scope of your research to reveal unforeseen data and opportunities that can have a significant impact on outcomes—whether on product and design strategy or on your career path. To get different, more effective, more innovative results that will stick, you need to think outside the box you’re currently in. If you limit the scope of your research to the current state and, thus, operate within the same box, you’ll get the same types of results.

“We cannot solve our problems with the same level of thinking that created them.”— Albert Einstein

In UX research , if you want to create a product that people love and want to use, you need to do exploratory research that goes beyond the scope of the current product. If you just keep exploring how people are using the current product—or what works and doesn’t work with the current product—you’ll stay stuck in the same paradigm and limit the scope and impact of potential solutions. You should instead do exploratory research that goes beyond the use of the current product, as well as beyond the scope of the user needs the current product covers. Exploratory research—such as ethnographic research, field interviews, and shadowing, or observing people in their day-to-day life and context—is great for looking beyond the use of a specific product and the scope of the problem that the product is solving.

When I was at Yahoo!, working alongside the other Search UX researchers, we conducted shadow sessions and contextual inquiries in people’s homes to explore the broader context of information searching—how and when—beyond Internet searches. We observed what triggered an information search and what information sources people were using—both offline and online—to reveal unforeseen opportunities for search-product innovation.

Similarly, in career exploration , when I work with clients to discover the career they’ll love, I guide them in expanding the scope of data collection to include their whole life, not just their current or past work experience. We move beyond their field of work to reveal unforeseen opportunities that may lie outside it. Many career counselors and career explorers make the mistake of analyzing data only from the work context, thinking that other data wouldn’t be relevant to work. As a result, they keep operating from the same paradigm that created their problem in the first place and stay at the same level of thinking that isn’t working for them. No wonder they run in circles or find only temporary solutions that don’t solve the root of the problem.

The answers to finding the career that would be your best fit may lie outside your current work experience, especially if what you’ve done so far in your career has not been satisfying to you or doesn’t engage your interests and strengths. If your job is not the right fit for you, but you won’t find your answers by analyzing what you’re doing now. This is why it is essential that you look at your life more broadly. By broadening the scope of your exploration of your values, passions, and talents to your whole life—outside of work—you’ll find the answers you need. Otherwise, you’ll keep making quick, temporary careers fixes that won’t bring you true satisfaction over the long term.

3. Triangulate data from multiple methods and sources.

It’s important to know that no one input, method, or source can give us all the data we need—or even enough reliable data. Each method, source, or type of data has its own biases and limitations. By triangulating different data points, methods, and sources, you can ensure both the completeness and accuracy of your findings. Triangulated data not only supports solid recommendations and projections but also convinces stakeholders and clients of the validity and robustness of both your findings and recommendations. The more triangulation that occurs at different levels, the more robust your outcomes will be. Leave no stone unturned, so you can have the highest level of confidence possible in your results.

In UX research , triangulation can happen at different levels—from your overall research strategy to the individual research method you use—for example:

• By mixing quantitative and qualitative analysis and research methods, you can gather both quantitative and qualitative data. Collaboration between different specialists and teams is often key to getting optimal results—for example, UX researchers, market researchers, and data-mining analysts.
• You can also triangulate different evaluation methods—for example, by combining heuristic evaluation, benchmark testing, and usability testing.
• When using a particular research method such as field study or lab usability testing, it is essential to gather both observational and self-reported data, as I discuss in my article “ When Observing Users Is Not Enough .”

In career exploration , triangulation can happen at different levels—for example, by

• exploring different facets of a person’s unique blueprint, including values, strengths, personality patterns, and life purpose
• combining different sources of information to cover the whole Johari Window Model, which is shown in Figure 2, and to ensure you don’t fail to discover any major blind spots. Sources can be either self-discovered and self-reported—that is, known to the self—or other reported, other observed, or from assessments—that is, not known to the self. Others who could share what they’ve observed might be people who know the person—such as family, friends, and coworkers, as well as the career coach.
• combining different data-gathering approaches for these facets and sources—such as inquiries, coaching questions listening, visualizations, teaching and explaining, and reading

Image source: Communication Theory

4. Use the right tools and approaches to collect accurate data.

In addition to triangulating, you must ensure that you use the right approach or tool to gather the most accurate data possible. If you triangulate using tools or approaches that give you inaccurate or false data, you’ll lose the benefits of both the method and the triangulation. This inaccurate data would negatively impact your findings, predictions, and recommendations. One pitfall to avoid is choosing a tool just because it’s popular, taking it at face value, and failing to question its accuracy. Another is going too fast and choosing the easy route, without challenging the accuracy and validity of your data.

In UX research , one example of gathering inaccurate data would be doing usability testing with people who do not belong to the target audience for the product you’re testing or with people who are not passionate about the product. In my article “ When Role Playing Doesn’t Work ,” I quote Jared Spool, who said:

“Passion on a subject changes how participants invest in usability test tasks. That change can have profound effects on the results and the recommendations produced by the team.”

To get accurate results, you need to recruit participants who are actually involved in the process you’re testing and are passionate about it. This is especially true if you want to test how users respond to specific content or functionality, how they navigate and search for information, or whether certain content is useful and valuable to users. To collect accurate data in usability testing, you also need to have participants perform realistic tasks and task scenarios that are tailored to participants’ real tasks, as I discuss in my article “ When Role Playing Doesn’t Work .”

Otherwise, your recommendations won’t have dramatic impacts on use or sales. Jared Spool gives a striking example: “The design recommendation seemed solid, yet sales had dropped 23% immediately after the changes were made.”

In career exploration , an example is the use of the Myers-Briggs Type Indicator (MBTI) by many career coaches and counselors to help identify a client’s personality type. As much as I believe in the validity of the theory behind the sixteen personality types and that this is a great tool to use in career exploration, the instrument itself has many limitations. When I took my Myers-Briggs Type Indicator certification, I learned that, in about 40% of cases, the type the instrument indicates is not people’s best-fit type. There are also many limitations to using the letters representing types individually—for example, T versus F or S versus N . This is why I don’t use the instrument in my practice, and I don’t use the letters either. Instead, I use the InterStrength CORE Approach ™, a holistic approach that my mentor Linda Berens has developed, which triangulates two or three different data points to clarify personality type.

I guide my clients through Linda Berens’s CORE Self-Discovery Process ™, which is way more effective and accurate than taking the MTBI assessment alone. For many of my clients, the type we identify through Berens’s process is different and much more accurate than the type the MTBI assessment had identified. This is important because your best-fit personality type has a major impact on the type of work environment and tasks that would be the best fit for you. If the data you collect are inaccurate, the outcomes won’t be fully accurate either.

5. Optimize the accuracy of data collection during interviews.

To optimize the accuracy of the qualitative data that you collect—whether through observation or as self-reported data—just choosing the right approach or tool is not enough. You also need to make the most of your method by collecting data effectively. In particular, you must place thoughtful attention on truly hearing what people are saying and avoid erroneous interpretations or letting your own false assumptions color what you hear. Covering this subject fully would require an entire article in itself.

In UX research , the quality of your listening and observing skills can make a big difference in the accuracy of the data you collect. I talked about this at length in my article “ When Role Playing Doesn’t Work .” One key thing to be aware of is that you should not rely on any assumptions you might make about the meaning of what study participants are saying or doing. Avoiding this requires high-quality listening. It is so easy to read too quickly into what others are saying or doing and projecting our own meaning onto them. This happens a lot in personal and professional relationships because most people have not been taught the art of listening well. So check your assumptions. Here are some tips for accurately collecting data from my article “ When Role Playing Doesn’t Work ”:

• Make objective and precise observations. Reflect what you observe instead of making assumptions.
• Be aware of your assumptions or projections on the meaning of what the person is saying. You can learn more about this in my article “ When Observing Users Is Not Enough .”

In career exploration , the same principle applies when you’re guiding someone through a career exploration. Active listening, getting other people’s worlds, and not projecting or assuming are key to gathering accurate data and helping people see themselves clearly. If you’re making assumptions, check your assumptions with your client to see whether they’re true. For example, you might say, “It sounds like independence in your work is very important to you. Is that true?” The great thing about asking is that your client will generally not only confirm or correct your assumption but extend your understanding by giving you more information. Another way to fully get other people’s worlds—and help them understand their own world—is to ask Why? Use the 5 Whys Method , which some people call the Root-Cause Analysis Tool .

6. Expand the richness of the data you collect by adapting on the fly.

When you’re collecting qualitative data about people through live interactions, it’s important to be willing to adapt your process to the person with whom you’re talking. Doing so greatly enriches the data you’ll collect—sometimes in unexpected ways. This is key and is an art more than a science.

In UX research , this adaptation can happen at different levels, as follows:

• at the study level —As you’re conducting a research study, it can be beneficial to make ad hoc additions or changes to respond to what’s happening during sessions with participants. For a concept research study at Yahoo!, I designed a research plan that included a comics storyboard walkthrough and paper prototyping. During the study, some participants wanted to draw what they imagined the user interface should look like. Adapting in the moment, I added some ad hoc participatory design to the session, which provided very rich findings to the team—much richer than if I had stuck to the original plan and gone by the book.
• changing a task or skipping it altogether —If, during usability testing, you realize that a participant cannot relate to a task at all, adapt it to that participant.
• going along with a user’s flow —Disregard the sequence of questions you’ve planned for a user interview. For example, perhaps a user starts talking about a topic you intended to address at the end of your interview. While much depends on the particular situation, I generally recommend letting users talk about the topic rather than telling them you’d prefer to go back to it at some point later on. If a user spontaneously raises a point you wanted to know about, it is golden.
• allowing unpredictability and flexibility —Don’t follow a test script by the book! Don’t be afraid of going off the beaten path! You might encounter an unexpected, enlightening, or rich insight that can help you have greater impact on the design.
• at the task level —Adapt to each participant’s context and tailor your tasks, your storytelling, and your examples to that participant’s passions, interests, and needs. For example, if you are researching the usage or usability of a search function and a participant tells you he’s passionate about cars, ask him to search for information about cars.

Similarly, in career exploration , adaptation can take place at different levels:

• at the whole-process level —With my clients, I follow a step-by-step process that has proven effective throughout my seven years of experience while working with hundreds of clients. Although each step is important and builds on the others, it is important to adapt to what is emerging during the process—for individual clients and what they need or what works for them. For example, after Step 1 or 2, some clients are not yet ready to move onto the following steps. Some inner blocks are being revealed that we need to address first—before we can move onto the following steps. Sometimes, we can address these blocks in just one or two sessions. But at other times, they’re so deep seated that it takes the rest of the process to address them. A release of past wounds or negative beliefs must happen before they’re ready to step into the career of their dreams.
• at the session level —During the first part of the process, there is a predefined agenda for each session that aligns with homework the client had to do to prepare for the session. However, it is important to adapt to what is emerging in the moment for each client. Sometimes, clients have an expected life challenge or situation that they’re facing that triggers emotions such as grief, fear, or sadness. When these emotions are alive and present, they require attention before a client can be ready to move onto something else. Processing these emotions or situations can take a few minutes or a whole session. Often, being with whatever is emerging allows a client to address, release, or transform some inner blocks, which is exactly what the client needs for the whole process to succeed. It is important to trust that this is what the client needs in the moment.
• at the activity level— It sometimes happens that certain exercises or activities do not align with what a client needs. If the client is not showing resistance to diving into something important, you should listen and adapt to whatever is in the best interests of the client. There is an art to distinguishing the clients’ growth edge versus what does not align with what the client needs.
• at the moment level —Another skill requires dancing in the moment , or adapting to what is emerging in the conversation with the client rather than following a strict agenda. This also requires following what is alive in a conversation, where the energy is the strongest.

In both UX research and career exploration, in-depth research and analysis can have profound impacts on outcomes, revealing unforeseen opportunities and solutions.

However, in UX research, rapid studies often overlook opportunities to create optimal solutions because they remain within the same scope or at the same level of thinking that created the problem in the first place. Plus, they often result in solutions that don’t get to the root of the problem, so fail to solve the problem over the long term, and require multiple revisions of a process in the future. This can be costly in time, energy, and money and cause headaches for both the people who use our products and services and the businesses who employ us.

Whether in UX research or career exploration, spending the extra time, energy, and money it takes to truly solve a problem is usually worthwhile. Truly solving a problem requires the right strategy, method, and tools, as well as the accurate collection and triangulation of data.

You can uncover insights that enable you to solve a problem effectively and achieve significant results. Plus, you can save time, energy, and money down the road. If you’re a UX researcher, your insights can lead to significant impacts on product and design strategy and innovation. If your goal is career exploration, you can identify a career or work environment that is the best fit for you.

To learn more about Isabelle Peyrichoux’s career-exploration process , check out the following content online.

• “The #1 Reason You Are Unhappy in Your Career and What to Do About It!” Download the free report (PDF).
• “ Career Shift: Find Work You Love ,” Isabelle’s workshop at General Assembly.
• “ Land the Career You Love ,” a career coaching program.
• Subscribe to Isabelle Peyrichoux’s YouTube channel.

And read her articles on UXmatters .

Bibliography

Berens, Linda. “ The Leading Edge of Psychological Type .” Whitepaper, 2002–2013. Retrieved May 12, 2020.

Berens, Linda. Understanding Yourself and Others: An Introduction to the 4 Temperaments, 4.0 . West Hollywood, CA: Radiance House, 2010.

Berens, Linda. Understanding Yourself and Others: An Introduction to Interaction Styles, 2.0 . Huntington Beach, CA: Telos Publications, 2008.

Berens, Linda, and Dario Nardi. The Sixteen Personality Types: Descriptions for Self-Discovery . Huntington Beach, CA: Telos Publications, 1999.

Peyrichoux, Isabelle. “ 3 Keys to Discovering the Career You Absolutely Love .” Webinar, Dominican University of California, September 10, 2015. Retrieved May 12, 2020.

Peyrichoux, Isabelle. “Type and Career Calling: Using Type, Temperament, Interaction Style to Transform Careers, Lives, and the Planet, One Person at a Time.” A forthcoming talk at APTi Conference 2021 .

Peyrichoux, Isabelle. “ When Observing Users Is Not Enough: 10 Guidelines for Getting More Out of Users’ Verbal Comments .” UXmatters , April 9, 2007. Retrieved May 12, 2020.

Peyrichoux, Isabelle. “ When Role Playing Doesn’t Work: Seven Guidelines for Grounding Usability Testing in Participants’ Real Lives .” UXmatters , September 8, 2008. Retrieved May 12, 2020.

Spool, Jared M. “ Interview-Based Tasks: Learning from Leonardo DiCaprio .” User Interface Engineering , March 7, 2006. Retrieved June 8, 2008.

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• Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters
• Part 1: In-depth Analysis: Research Method and Strategy

Table of Contents

• Part 2: Conversational Archetypes: Six Conversation and Group Network Structures in Twitter
• Appendix: How to analyze social media networks

To understand the nature of Twitter conversations, the Pew Research Center Internet Project joined with researchers at the Social Media Research Foundation , a group of scholars whose mission is to support the creation and application of open tools, open data, and open scholarship related to social media. The discovery of these six archetypical network structures emerged over several years as we examined thousands of Twitter networks on hundreds of topics. Some structures such as Polarized Crowds have been noted by other researchers and were anticipated in our exploration, but the other structures emerged by studying many maps. This kind of exploratory data analysis depends on effective visualization techniques. In our case, the key design advance was the Group-in-a-Box layout technique, which presents the results of clustering algorithms so as to clearly show the size of each cluster, connection density within each cluster, and the connection frequency between clusters.

As all exploratory data analysts do, we generated insights which we invite others to replicate with other tools, such as different visual layout techniques or statistical criteria. Our work is in the spirit of observational research that forms categories, like 17 th century botanists describing the variety of flowers on a newly discovered island or astronomers whose new telescopes that allow them to see different categories of galaxies. Our naming reflects conjectures about why different structures emerge. These categories and explanations are open to challenge by others who may have differing perspectives and more powerful tools.

Our tool was a software tool called NodeXL , a plug-in extension to Microsoft Excel spreadsheets that enables n etwork o verview, d iscovery, and e xploration. NodeXL allows users to import network data and perform analysis and visualization of networks. NodeXL permits anyone to connect to social media services (including Twitter, Facebook, YouTube, Flickr, Wikis, email, blogs and websites) and retrieve public data about the connections among users, pages, and documents. In the specific case of Twitter, the tool captures information about the content of each message (the “tweet”), which may contain usernames, hyperlinks and hashtags, along with information about each author’s connections to other Twitter users. In Twitter, these connections include relationships among users who follow one another, who mention one another, and reply to one another.

We performed Twitter keyword searches which returned a set of tweets that were then used as datasets for analysis. Network connections were extracted from the content of each tweet returned in Twitter Search results. A link was created for every reply or mention we observed. In addition, NodeXL captures information about the Twitter user’s connections to other Twitter members. 2  Data are also retrieved from each user’s public Twitter profile, which includes the number of tweets the user has posted, the number of other users that the user follows, and the number of other people who follow that user, among other things. Author statistics are combined with information about the connections among the people who shared the use of the same word, phrase, or term. For example, if Alice and Betty both posted a message in our dataset that includes the term “politics” and Alice follows Betty on Twitter, our data captured this relationship.

Only publicly available messages were analyzed in this study. No direct messages or other private content were collected or analyzed. Any message defined by its author as private (from, for example, “protected accounts”) was excluded from analysis.

There are clear limits to any dataset captured by NodeXL. The tweets we collect are snapshots of finite periods of conversation around a topic or phrase. The data here do not represent the sentiments of the full population of Twitter users or the larger period of discussion beyond the data collection window. Further, Twitter users are not representative of the full range of the population of the United States or even the population of the Internet or even of social media users generally. 3  Thus, we are not arguing that this analysis represents all that happens on Twitter or that it is a proxy for national sentiment on these topics. However, we believe these data sets contain useful snapshots of the structure of social media networks around topics that matter.

Taking “aerial photographs” of Twitter crowds

Our method is similar to taking aerial photographs or short videos of crowds in public spaces, particularly pictures of rallies, protests, political events, and other socially and culturally interesting phenomena. No one snapshot or video clip of a crowd completely captures the event, but taken together crowd images provide some insights into an event or gathering. Our method produces crowd photos from social media spaces; a domain that has not been widely pictured before. Like aerial crowd photographs, social media network maps show the size and structure of the crowd along with the key actors in that crowd.

These social media network maps can reveal information at the level of both individuals and groups. Social media networks often have just a few people who stand out in terms of the unique ways they connect to others. Some networks are composed of just a single group, while others are divided into sub-groups. Each group can be more or less connected to other groups. These structures tell a story about the kinds of interactions that take place in Twitter.

Networks, group density, and diversity of connections

Twitter social media network maps show how interconnected people become when they engage in conversations. People often “clump” into groups. Each network and its sub-groups can be measured in terms of the density of its internal connections. A group of people with many connections among its members is more “dense” than a group that has few connections among the same number of participants. Density is measured as the ratio of the number of relationships among a population over the total number of possible relationships. The density can vary between zero (i.e.: no connections among nodes) and 1 (i.e.: all nodes in a network are connected to all other nodes). As groups grow in size it is harder to interact with all other participants, so as a rule, the larger the numbers of people in a social network the lower the density of their connections. As a result, no one value is a specific threshold for separating high or low density groups. Generally, though, networks are considered to be loosely-knit, low density networks when only a few of the participants are connected to one another.

Some people within a sub-group connect to people outside their group. The amount of internal and external connection in a sub-group is an important indicator of how much people in that group are exposed to people with differing points of view in different groups. If there are few ties between groups, people may not be exposed to content from users in other groups. If there are many ties between groups there is likely to be a larger amount of information flowing between them.

More on network hubs and bridges

Social network maps created from collections of Twitter relationships often highlight a few individual users who occupy key positions in the network. We refer to the relatively rare highly connected users as “hubs.” Many other users follow these hub users; far more follow the majority of other people in the network. Hubs are important because they have large audiences. Some people who have fewer connections can be equally important if their links are rare, connecting across the network to otherwise disconnected groups, acting as “bridges.” While big hubs can also occupy the important position of “bridge,” a user with just a few relatively unique connections may also be an important bridge. 

• Twitter has subsequently reduced the accessibility of the Followers network data, see: http://www.connectedaction.net/2013/06/11/over-the-edge-twitter-api-1-1-makes-follows-edges-hard-to-get/ ↩
• Pew Internet Report on Twitter Demographics: https://www.pewresearch.org/internet/Series/Twitter.aspx ↩

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

Qualitative research is a type of research methodology that focuses on exploring and understanding people’s beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.

Qualitative research aims to uncover the meaning and significance of social phenomena, and it typically involves a more flexible and iterative approach to data collection and analysis compared to quantitative research. Qualitative research is often used in fields such as sociology, anthropology, psychology, and education.

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

This method involves conducting an interview with a single participant to gain a detailed understanding of their experiences, attitudes, and beliefs. One-to-one interviews can be conducted in-person, over the phone, or through video conferencing. The interviewer typically uses open-ended questions to encourage the participant to share their thoughts and feelings. One-to-one interviews are useful for gaining detailed insights into individual experiences.

Focus Groups

This method involves bringing together a group of people to discuss a specific topic in a structured setting. The focus group is led by a moderator who guides the discussion and encourages participants to share their thoughts and opinions. Focus groups are useful for generating ideas and insights, exploring social norms and attitudes, and understanding group dynamics.

Ethnographic Studies

This method involves immersing oneself in a culture or community to gain a deep understanding of its norms, beliefs, and practices. Ethnographic studies typically involve long-term fieldwork and observation, as well as interviews and document analysis. Ethnographic studies are useful for understanding the cultural context of social phenomena and for gaining a holistic understanding of complex social processes.

Text Analysis

This method involves analyzing written or spoken language to identify patterns and themes. Text analysis can be quantitative or qualitative. Qualitative text analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Text analysis is useful for understanding media messages, public discourse, and cultural trends.

This method involves an in-depth examination of a single person, group, or event to gain an understanding of complex phenomena. Case studies typically involve a combination of data collection methods, such as interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are useful for exploring unique or rare cases, and for generating hypotheses for further research.

Process of Observation

This method involves systematically observing and recording behaviors and interactions in natural settings. The observer may take notes, use audio or video recordings, or use other methods to document what they see. Process of observation is useful for understanding social interactions, cultural practices, and the context in which behaviors occur.

Record Keeping

This method involves keeping detailed records of observations, interviews, and other data collected during the research process. Record keeping is essential for ensuring the accuracy and reliability of the data, and for providing a basis for analysis and interpretation.

This method involves collecting data from a large sample of participants through a structured questionnaire. Surveys can be conducted in person, over the phone, through mail, or online. Surveys are useful for collecting data on attitudes, beliefs, and behaviors, and for identifying patterns and trends in a population.

Qualitative data analysis is a process of turning unstructured data into meaningful insights. It involves extracting and organizing information from sources like interviews, focus groups, and surveys. The goal is to understand people’s attitudes, behaviors, and motivations

Qualitative Research Analysis Methods

Qualitative Research analysis methods involve a systematic approach to interpreting and making sense of the data collected in qualitative research. Here are some common qualitative data analysis methods:

Thematic Analysis

This method involves identifying patterns or themes in the data that are relevant to the research question. The researcher reviews the data, identifies keywords or phrases, and groups them into categories or themes. Thematic analysis is useful for identifying patterns across multiple data sources and for generating new insights into the research topic.

Content Analysis

This method involves analyzing the content of written or spoken language to identify key themes or concepts. Content analysis can be quantitative or qualitative. Qualitative content analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Content analysis is useful for identifying patterns in media messages, public discourse, and cultural trends.

Discourse Analysis

This method involves analyzing language to understand how it constructs meaning and shapes social interactions. Discourse analysis can involve a variety of methods, such as conversation analysis, critical discourse analysis, and narrative analysis. Discourse analysis is useful for understanding how language shapes social interactions, cultural norms, and power relationships.

Grounded Theory Analysis

This method involves developing a theory or explanation based on the data collected. Grounded theory analysis starts with the data and uses an iterative process of coding and analysis to identify patterns and themes in the data. The theory or explanation that emerges is grounded in the data, rather than preconceived hypotheses. Grounded theory analysis is useful for understanding complex social phenomena and for generating new theoretical insights.

Narrative Analysis

This method involves analyzing the stories or narratives that participants share to gain insights into their experiences, attitudes, and beliefs. Narrative analysis can involve a variety of methods, such as structural analysis, thematic analysis, and discourse analysis. Narrative analysis is useful for understanding how individuals construct their identities, make sense of their experiences, and communicate their values and beliefs.

Phenomenological Analysis

This method involves analyzing how individuals make sense of their experiences and the meanings they attach to them. Phenomenological analysis typically involves in-depth interviews with participants to explore their experiences in detail. Phenomenological analysis is useful for understanding subjective experiences and for developing a rich understanding of human consciousness.

Comparative Analysis

This method involves comparing and contrasting data across different cases or groups to identify similarities and differences. Comparative analysis can be used to identify patterns or themes that are common across multiple cases, as well as to identify unique or distinctive features of individual cases. Comparative analysis is useful for understanding how social phenomena vary across different contexts and groups.

Applications of Qualitative Research

Qualitative research has many applications across different fields and industries. Here are some examples of how qualitative research is used:

• Market Research: Qualitative research is often used in market research to understand consumer attitudes, behaviors, and preferences. Researchers conduct focus groups and one-on-one interviews with consumers to gather insights into their experiences and perceptions of products and services.
• Health Care: Qualitative research is used in health care to explore patient experiences and perspectives on health and illness. Researchers conduct in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education: Qualitative research is used in education to understand student experiences and to develop effective teaching strategies. Researchers conduct classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work : Qualitative research is used in social work to explore social problems and to develop interventions to address them. Researchers conduct in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : Qualitative research is used in anthropology to understand different cultures and societies. Researchers conduct ethnographic studies and observe and interview members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : Qualitative research is used in psychology to understand human behavior and mental processes. Researchers conduct in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy : Qualitative research is used in public policy to explore public attitudes and to inform policy decisions. Researchers conduct focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

• Identify your research question: Qualitative research starts with a research question or set of questions that you want to explore. This question should be focused and specific, but also broad enough to allow for exploration and discovery.
• Select your research design: There are different types of qualitative research designs, including ethnography, case study, grounded theory, and phenomenology. You should select a design that aligns with your research question and that will allow you to gather the data you need to answer your research question.
• Recruit participants: Once you have your research question and design, you need to recruit participants. The number of participants you need will depend on your research design and the scope of your research. You can recruit participants through advertisements, social media, or through personal networks.
• Collect data: There are different methods for collecting qualitative data, including interviews, focus groups, observation, and document analysis. You should select the method or methods that align with your research design and that will allow you to gather the data you need to answer your research question.
• Analyze data: Once you have collected your data, you need to analyze it. This involves reviewing your data, identifying patterns and themes, and developing codes to organize your data. You can use different software programs to help you analyze your data, or you can do it manually.
• Interpret data: Once you have analyzed your data, you need to interpret it. This involves making sense of the patterns and themes you have identified, and developing insights and conclusions that answer your research question. You should be guided by your research question and use your data to support your conclusions.
• Communicate results: Once you have interpreted your data, you need to communicate your results. This can be done through academic papers, presentations, or reports. You should be clear and concise in your communication, and use examples and quotes from your data to support your findings.

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

• Customer Feedback: A company may conduct qualitative research to understand the feedback and experiences of its customers. This may involve conducting focus groups or one-on-one interviews with customers to gather insights into their attitudes, behaviors, and preferences.
• Healthcare : A healthcare provider may conduct qualitative research to explore patient experiences and perspectives on health and illness. This may involve conducting in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education : An educational institution may conduct qualitative research to understand student experiences and to develop effective teaching strategies. This may involve conducting classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work: A social worker may conduct qualitative research to explore social problems and to develop interventions to address them. This may involve conducting in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : An anthropologist may conduct qualitative research to understand different cultures and societies. This may involve conducting ethnographic studies and observing and interviewing members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : A psychologist may conduct qualitative research to understand human behavior and mental processes. This may involve conducting in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy: A government agency or non-profit organization may conduct qualitative research to explore public attitudes and to inform policy decisions. This may involve conducting focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

Purpose of Qualitative Research

The purpose of qualitative research is to explore and understand the subjective experiences, behaviors, and perspectives of individuals or groups in a particular context. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research aims to provide in-depth, descriptive information that can help researchers develop insights and theories about complex social phenomena.

Qualitative research can serve multiple purposes, including:

• Exploring new or emerging phenomena : Qualitative research can be useful for exploring new or emerging phenomena, such as new technologies or social trends. This type of research can help researchers develop a deeper understanding of these phenomena and identify potential areas for further study.
• Understanding complex social phenomena : Qualitative research can be useful for exploring complex social phenomena, such as cultural beliefs, social norms, or political processes. This type of research can help researchers develop a more nuanced understanding of these phenomena and identify factors that may influence them.
• Generating new theories or hypotheses: Qualitative research can be useful for generating new theories or hypotheses about social phenomena. By gathering rich, detailed data about individuals’ experiences and perspectives, researchers can develop insights that may challenge existing theories or lead to new lines of inquiry.
• Providing context for quantitative data: Qualitative research can be useful for providing context for quantitative data. By gathering qualitative data alongside quantitative data, researchers can develop a more complete understanding of complex social phenomena and identify potential explanations for quantitative findings.

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

• Exploring a new area: If little is known about a particular topic, qualitative research can help to identify key issues, generate hypotheses, and develop new theories.
• Understanding complex phenomena: Qualitative research can be used to investigate complex social, cultural, or organizational phenomena that are difficult to measure quantitatively.
• Investigating subjective experiences: Qualitative research is particularly useful for investigating the subjective experiences of individuals or groups, such as their attitudes, beliefs, values, or emotions.
• Conducting formative research: Qualitative research can be used in the early stages of a research project to develop research questions, identify potential research participants, and refine research methods.
• Evaluating interventions or programs: Qualitative research can be used to evaluate the effectiveness of interventions or programs by collecting data on participants’ experiences, attitudes, and behaviors.

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

• Focus on subjective experience: Qualitative research is concerned with understanding the subjective experiences, beliefs, and perspectives of individuals or groups in a particular context. Researchers aim to explore the meanings that people attach to their experiences and to understand the social and cultural factors that shape these meanings.
• Use of open-ended questions: Qualitative research relies on open-ended questions that allow participants to provide detailed, in-depth responses. Researchers seek to elicit rich, descriptive data that can provide insights into participants’ experiences and perspectives.
• Sampling-based on purpose and diversity: Qualitative research often involves purposive sampling, in which participants are selected based on specific criteria related to the research question. Researchers may also seek to include participants with diverse experiences and perspectives to capture a range of viewpoints.
• Data collection through multiple methods: Qualitative research typically involves the use of multiple data collection methods, such as in-depth interviews, focus groups, and observation. This allows researchers to gather rich, detailed data from multiple sources, which can provide a more complete picture of participants’ experiences and perspectives.
• Inductive data analysis: Qualitative research relies on inductive data analysis, in which researchers develop theories and insights based on the data rather than testing pre-existing hypotheses. Researchers use coding and thematic analysis to identify patterns and themes in the data and to develop theories and explanations based on these patterns.
• Emphasis on researcher reflexivity: Qualitative research recognizes the importance of the researcher’s role in shaping the research process and outcomes. Researchers are encouraged to reflect on their own biases and assumptions and to be transparent about their role in the research process.

Advantages of Qualitative Research

Qualitative research offers several advantages over other research methods, including:

• Depth and detail: Qualitative research allows researchers to gather rich, detailed data that provides a deeper understanding of complex social phenomena. Through in-depth interviews, focus groups, and observation, researchers can gather detailed information about participants’ experiences and perspectives that may be missed by other research methods.
• Flexibility : Qualitative research is a flexible approach that allows researchers to adapt their methods to the research question and context. Researchers can adjust their research methods in real-time to gather more information or explore unexpected findings.
• Contextual understanding: Qualitative research is well-suited to exploring the social and cultural context in which individuals or groups are situated. Researchers can gather information about cultural norms, social structures, and historical events that may influence participants’ experiences and perspectives.
• Participant perspective : Qualitative research prioritizes the perspective of participants, allowing researchers to explore subjective experiences and understand the meanings that participants attach to their experiences.
• Theory development: Qualitative research can contribute to the development of new theories and insights about complex social phenomena. By gathering rich, detailed data and using inductive data analysis, researchers can develop new theories and explanations that may challenge existing understandings.
• Validity : Qualitative research can offer high validity by using multiple data collection methods, purposive and diverse sampling, and researcher reflexivity. This can help ensure that findings are credible and trustworthy.

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

• Subjectivity : Qualitative research relies on the subjective interpretation of researchers, which can introduce bias into the research process. The researcher’s perspective, beliefs, and experiences can influence the way data is collected, analyzed, and interpreted.
• Limited generalizability: Qualitative research typically involves small, purposive samples that may not be representative of larger populations. This limits the generalizability of findings to other contexts or populations.
• Time-consuming: Qualitative research can be a time-consuming process, requiring significant resources for data collection, analysis, and interpretation.
• Resource-intensive: Qualitative research may require more resources than other research methods, including specialized training for researchers, specialized software for data analysis, and transcription services.
• Limited reliability: Qualitative research may be less reliable than quantitative research, as it relies on the subjective interpretation of researchers. This can make it difficult to replicate findings or compare results across different studies.
• Ethics and confidentiality: Qualitative research involves collecting sensitive information from participants, which raises ethical concerns about confidentiality and informed consent. Researchers must take care to protect the privacy and confidentiality of participants and obtain informed consent.

Also see Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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In-depth Interviews: Definition and how to conduct them

Online surveys, user review sites and focus groups can be great methods for collecting data. However, another method of gathering data that is sometimes overlooked are the in-depth interviews.

All of these methods can be used in your comprehensive customer experience management strategy, but in-depth interviews can help you collect data that can offer rich insights into your target audience’s experience and preferences from a broad sample.

In this article you will discover the main characteristics of in-depth interviews as a great tool for your qualitative research and gather better insights from your objects of study.

LEARN ABOUT: Behavioral Research

What are in-depth interviews?

In-depth interviews are a qualitative data collection method that allows for the collection of a large amount of information about the behavior, attitude and perception of the interviewees.

LEARN ABOUT: Best Data Collection Tools

During in-depth interviews, researchers and participants have the freedom to explore additional points and change the direction of the process when necessary. It is an independent research method that can adopt multiple strategies according to the needs of the research.

Characteristics of in-depth interviews

There are many types of interviews , each with its particularities, in this case the most important characteristics of in-depth interviews are:

• Flexible structure: Although it is not very structured, it covers a few topics based on a guide, which allows the interviewer to cover areas appropriate for the interviewee.
• Interactive: The interviewer processes the material that is produced during the interview. During the interaction the interviewer poses initial questions in a positive manner, so that the respondent is encouraged to answer. The complete process is very human, and so less mundane and dull.
• Deep: Many probing techniques are used in in-depth interviews, so that results are understood through exploration and explanation. The interviewer asks follow-up questions to gain a deeper perspective and understand the participant’s viewpoint.
• Generative: Often interacting with your target audience creates new knowledge. For instance, if you are talking to your customers, you learn more about the purchase behavior. Researchers and participants present ideas for a specific topic and solutions to the problems posed.

To learn more about the characteristics of in-depth interviews, check out our blog on interview questions .

Importance of conducting in-depth interviews

As an in-depth interview is a one-on-one conversation, you get enough opportunities to get to the root causes of likes/dislikes, perceptions, or beliefs. 

Generally, questions are open-ended questions and can be customized as per the particular situation. You can use single ease questions . A single-ease question is a straightforward query that elicits a concise and uncomplicated response. The interviewer gets an opportunity to develop a rapport with the participant, thereby making them feel comfortable. Thus, they can bring out honest feedback and also note their expressions and body language. Such cues can amount to rich qualitative data.

LEARN ABOUT: Selection Bias

With surveys, there are chances that the respondents may select answers in a rush, but in case of in-depth interviews it’s hardly the worry of researchers. 

Conversations can prove to be an excellent method to collect data. In fact, people might be reluctant to answer questions in written format, but given the nature of an interview, participants might agree giving information verbally. You can also discuss with the interviewees if they want to keep their identity confidential.

In-depth interviews are aimed at uncovering the issues in order to obtain detailed results. This method allows you to gain insight into the experiences, feelings and perspectives of the interviewees.

When conducting the initial stage of a large research project, in-depth interviews prove to be useful to narrow down and focus on important research details.

When you want to have the context of a problem, in-depth interviews allow you to evaluate different solutions to manage the research process while assisting in in-depth data analysis .

LEARN ABOUT: Research Process Steps

Steps to conduct in-depth interviews

• Obtain the necessary information about the respondents and the context in which they operate.
• Make a script or a list of topics you want to cover. This will make it easy to add secondary questions.
• Schedule an interview at a time and date of the respondent’s choice.
• Ask questions confidently and let the interviewees feel comfortable, so that they too are confident and can answer difficult questions with ease.
• Set a maximum duration such that it doesn’t feel exhaustive.
• Observe and make notes on the interviewee’s body expressions and gestures.
• It is important to maintain ethics throughout the process.
• Transcribe the recordings and verify them with the interviewee.

Advantages of in-depth interviews

The benefits of conducting an in-depth interview include the following:

• They allow the researcher and participants to have a comfortable relationship to generate more in-depth responses regarding sensitive topics.
• Researchers can ask follow-up questions , obtain additional information, and return to key questions to gain a better understanding of the participants’ attitudes.
• The sampling is more accurate than other data collection methods .
• Researchers can monitor changes in tone and word choice of participants to gain a better understanding of opinions.
• Fewer participants are needed to obtain useful information. 
• In-depth interviews can be very beneficial when a detailed report on a person’s opinion and behavior is needed. In addition, it explores new ideas and contexts that give the researcher a complete picture of the phenomena that occurred.

Disadvantages 

The disadvantages of in-depth interviews are:

• They are time-consuming, as they must be transcribed, organized, analyzed in detail.
• If the interviewer is inexperienced, it affects the complete process.
• It is a costly research method compared to other methods.
• Participants must be chosen carefully to avoid bias, otherwise it can lengthen the process.
• Generally, participants decide to collaborate only when they receive an incentive in return.

LEARN ABOUT: Self-Selection Bias

What is the purpose of in-depth interviews?

The main purpose of in-depth interviews is to understand the consumer behavior and make well-informed decisions. Organizations can formulate their marketing strategies based on the information received from the respondents. They can also gain insights into the probable demand and know consumer pulse.

In the case of B2B businesses, researchers can understand the demand in more detail and can ask questions targeted for the experts. Interviews offer a chance to understand the customer’s thought process and design products that have higher chances of being accepted in the market.

LEARN ABOUT: 12 Best Tools for Researchers

Final words

An in-depth interview should follow all the steps of the process to collect meaningful data. Hope this blog helps you decide whether you should conduct a detailed interview with your target audience, keeping in mind the pros and cons of it.

If you want to get started with conducting research online, we suggest using an online survey software that offers features like designing a questionnaire , customized look and feel, distributing to your contacts and data analytics. Create an account with QuestionPro Surveys and explore the tool. If you need any help with research or data collection, feel free to connect with us.

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in-depth adjective

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What does the adjective in-depth mean?

There is one meaning in OED's entry for the adjective in-depth . See ‘Meaning & use’ for definition, usage, and quotation evidence.

How common is the adjective in-depth ?

How is the adjective in-depth pronounced?

British english, u.s. english, where does the adjective in-depth come from.

Earliest known use

The earliest known use of the adjective in-depth is in the 1960s.

OED's earliest evidence for in-depth is from 1963, in Journal Negro Education .

in-depth is formed within English, by derivation.

Etymons: in- prefix 1

Nearby entries

• independent variable, n. 1816–
• independing, adj. 1601–1758
• indeplorable, adj. 1623
• indeposable, adj. 1673–
• in deposito, adv. 1546–1700
• indepravate, adj. 1609
• indeprecable, adj. 1623–58
• indeprehensible, adj. 1633–52
• indeprivability, n. 1789–
• indeprivable, adj. 1744–
• in-depth, adj. 1963–
• inderborite, n. 1941–
• inderite, n. 1937–
• inderkins, n. 1696
• indescribability, n. 1824–
• indescribable, adj. & n. 1785–
• indescribableness, n. 1880–
• indescribably, adv. 1795–
• indescript, adj. 1854–
• indescriptive, adj. 1828–
• indesert, n. 1612–

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Meaning & use

Pronunciation, entry history for in-depth, adj..

Originally published as part of the entry for in-, prefix¹

in-, prefix¹ was revised in September 2021.

oed.com is a living text, updated every three months. Modifications may include:

• further revisions to definitions, pronunciation, etymology, headwords, variant spellings, quotations, and dates;
• new senses, phrases, and quotations.

Earlier versions of this entry were published in:

A Supplement to the OED, Volume II (1976)

• Find out more

OED Second Edition (1989)

• View in-, prefix¹ in OED Second Edition

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Definition of in-depth adjective from the Oxford Advanced American Dictionary

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