How to Present Qualitative Data (Expert Tips + Tools)

Discover expert tips and tools to effectively present and visualize qualitative data insights.

15 mins read
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Why do we watch product reviews on YouTube?

Anyone can look up product specs. We want to know more about people’s real-life experiences. What are their impressions while using a product?

A simple, everyday example of how to present qualitative data.

Researchers face this battle every day.

Analysis reveals complex themes and trends. They constantly grapple with which findings to present to stakeholders. Include ALL their results, and they’ll overwhelm their audience. Ideally, they’d like to present insights that are digestible and actionable.

How do they achieve that?

Read on for tips and tricks on how to master qualitative data presentation.

Or… hop on over here if you already know you need the perfect research partner for your qualitative data analysis

Why Qualitative Data Matters in Research

Qualitative data enhances our understanding of the world around us.

Humans have multifaceted thoughts, emotions, and interactions throughout our lives. Scratch that, throughout the day. Researchers study qualitative data to decipher the underlying motivations behind human thinking.

Qualitative research involves collecting, analyzing, and interpreting non-numerical data. It helps explain processes and patterns of human behavior tough to quantify.

Researchers conduct studies, interviews and focus groups with open-ended questions to gather data. They analyze recordings (audio or video), documents, notes, and images to categorize complex data into themes.

Examining issues or themes in depth provides insight into human experiences. Qualitative data provides a nuanced understanding of people’s perceptions and attitudes. Researchers uncover subtleties and complexities about particular themes through this data.

The open-ended nature of qualitative research lends itself to agile product development. Researchers can alter interview questions in real time. They can also revise the framework and direction of a study as new information comes to light.

Explore the different types of qualitative research.

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Qualitative vs. Quantitative Data

Quantitative research measures variables, tests hypotheses, and establishes statistical patterns in data. Numerical and objective quantitative data describes “what” users are up to. How many visitors to a company’s webpage? How do they interact with it? Do they take desired actions?

Researchers spot trends and relationships and predict future user behavior using quantitative data.

Qualitative data explains people’s attitudes, opinions, and emotions. Qualitative data helps generate hypotheses for testing by statistical methods. Collect qualitative data in conjunction with its quantitative counterpart. Qualitative research helps make sense of social phenomena, allowing you to dive deep into quantitative data.

Qualitative data is subjective and explores context – the “how” and “why” behind user actions. Why did users drop off before making a purchase? What prompted them to leave the website?

Qualitative data offers rich insights into user experiences, diminishing ambiguity behind user behavior. It explains the nuances of user behavior and thinking, something quantitative data just can’t capture.

Learn when to use qualitative vs. quantitative research.

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Key Considerations for Presenting Qualitative Data

A researcher’s primary objective when presenting qualitative data to stakeholders is simple. To transform raw data into stories that implore them to take action. Sounds simple enough, but it’s easier said than done. Keep these points in mind when presenting qualitative data:

  • It’s messy: By nature, qualitative data is dense, complex, and unstructured. You have to dissect mountains of data, turning it into a digestible format. Remember, quality insights don’t arrive during preliminary analysis. Concrete themes begin to emerge after a few iterations. Don’t get fazed by the volume or complexity of data. 
  • Structure your presentation: Ensure your presentation aligns closely with the research questions. Synthesizing data into common themes helps create a narrative. Case studies support findings, providing credibility and context to your assertions. Ensure each case has a background, key issues, and outcome section. 
  • Be selective: Focus your presentation around key insights only. It’s tempting to include everything you’ve unpacked. However, presenting too much detail can overwhelm your audience. Explore insights that support arguments or themes you wish to convey. In the words of the late, great Tupac Shakur, resist the temptation. 
  • Establish authenticity: Use direct quotes from participants to add relatability to your presentation. Examples bring themes to life – so people know these are genuine user concerns or feedback. Personal stories resonate strongly with viewers, engaging intellectually and emotionally.
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Steps to Effective Qualitative Data Presentation

Without effective delivery, research that takes copious amounts of time is quickly forgotten. Presenting qualitative data is the final but crucial step. Follow these steps to get the most out of your qualitative data presentation:

1. Collect Data

Use focus groups, interviews, and observations to collect qualitative data. This includes artifacts from multiple sources, such as:

  • Recordings (audio + video)
  • Surveys and questionnaires (structured + unstructured)
  • Documents (clippings, diaries, reports, meeting minutes)
  • Case studies and field notes 
  • Images and photographs

2. Prepare Data

Researchers spend the bulk of their time cleaning and sanitizing unstructured qualitative data. Examine data closely for accuracy, correcting any errors and removing irrelevant information. Organizing data this way ensures completeness and consistency in their approach.

It helps if your research data all lives in one place. Marvin is a centralized research repository, housing all your data (qualitative AND quantitative).

3. Tag Data

Once collated and organized, code all your qualitative data to unearth meaningful insights. Coding or tagging (used interchangeably) involves labeling and categorizing your data into themes. Thematic analysis helps you identify trends, patterns, and relationships within qualitative data. 

Tagging is usually performed manually, but analytics platforms help expedite the process. Learn how to tag data to arrive at insights faster.

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4. Visualize Data

Textual and visual representations help drive your point(s) home. Visualize your data on a customer feedback analytics platform. Distil key insights from coded data to create charts, graphs, infographics and more. Attractive and comprehensible visuals help capture people’s attention. 

Data visualization helps you identify themes, patterns, and correlations in the data. Crystallize insights from hundreds of data points to make findings understandable and clear. More in the section below.

5. Create a Narrative

One of the final steps is to report your data. Tell a compelling story with data that resonates with your audience. The aim is to make research findings accessible and understandable to them. 

Like an essay (or this article), ensure your story has an introduction, main body, and conclusion. Structure your presentation around the main themes. This highlights impactful insights and helps create a cohesive storyline.

Identify one core message – what is the key takeaway for a viewer? Highlight the implications of insights. Tie them back to your research question. How do findings inform strategy or decision-making moving forward?

Weave personal experiences and anecdotes to illustrate complex themes in data. Capturing a user’s perspective makes it more immersive and memorable for the audience.

6. Detail the Process

Describe your qualitative data collection and analysis procedures. Was inductive or deductive reasoning used during coding? Any software used to aid analysis? 

A coherent outline of research methodology, findings, and insights helps determine the course of action. Rule of thumb – give readers enough information so they can carry out similar analysis themselves. 

Use this helpful checklist to ensure high-quality research.

7. Review and Refine

After concluding your presentation, engage in discussion and gather feedback from stakeholders. Discuss implications of research insights and elements they liked (or didn’t). What changes would you make the next time round?

Constantly refine the process as you go along.

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Methods of Representing Qualitative Data

Qualitative data offers a rich context that quantitative data doesn’t provide. It helps teams build compelling cases that inform product, marketing, and strategic decisions.

So, how is qualitative data presented?

Visual Representation of Qualitative Data

Visual representations bring static data to life.

Use charts and infographics to distill complex ideas into a comprehensible format. These enhance the clarity of findings. Quickly identify key themes, trends, relationships, and outliers in your data.

Condensing complex datasets into a visual format involves quantifying qualitative data. Yes, you read that correctly.

Depending on the data you want to present, here are some options for your next presentation:

  • Charts: Data presented in graphic form with two axes. Common charts include:
    • Bar (normal or stacked): Represent numerical values in relation to each other. Stacked bars display multiple series in each bar as part of a whole. 
    • Pie: Circular chart displaying different segments as a percentage of a whole. 
    • Histogram: Bar chart splitting a continuous measure into different buckets to analyze the distribution.
    • Map or geospatial: Shows data in map form, using color to show relationships between data and a location.
    • Heatmaps: This type of map visualization displays data in different colors.  
  • Graphs: A diagram using points, lines, curves, segments, or areas. Compares two variables on opposite axes.
    • Timelines: Represents milestones on an axis or timeline, showing events and developments.
  • Infographic: A combination of visuals and textual data that engage the viewer.
    • Mind & concept maps: Diagrams that visually organize information to show relationships between ideas. 
    • Flow charts: Diagrams that use arrows and symbols to represent processes or workflows. 
  • Tables: A dataset displayed in rows and columns. Like your typical Excel spreadsheet. 
  • Dashboards: A collection of data visualizations, accessible in one place. Helpful for presenting data in a narrative.

Researchers weave these into a narrative for presentation, into their tool of choice (more below).

Remember, visualizations require advanced planning. Begin by identifying core themes you’d like to explore. Use the following tips to take your qualitative data presentations to the next level:

  • Align visuals with objectives: Ensure the presentation communicates a clear purpose. Choose visual representations that align with these messages. 
  • Establish a visual hierarchy: Use size, color, and layout to guide people’s attention. 
  • Make it engaging: Add charts, icons, infographics, and images to tell your story.
  • Keep it concise: Don’t overwhelm viewers with text-heavy graphics. 
  • Labels: Ensure graphics are clearly labeled and easy to read from afar. 

Presenting qualitative data visually grabs people’s attention and helps them retain key information. 

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Textual Representation of Qualitative Data

There’s no getting around it – qualitative data is text-heavy. Researchers pore over lengthy transcripts to unearth meaningful and actionable insights. However, while presenting, the simpler, the better. An effective presentation of textual qualitative data makes insights easily comprehensible. 

Incorporating people’s stories and testimonials makes content relatable to viewers. Include detailed observations to provide context to your narrative. Remember, exclude large portions of text, only memorable instances that communicate a theme.

Here’s how to present textual data from:

  • Interviews: Select quotes most representative of research findings. Establish the setting and speakers with text at the end of the quote. 

“I found it very easy to navigate through the application. The menu options were intuitive and self-explanatory” – (participant 1, 34, female)

  • Observations: Continuing with the same example, the following paragraph describes the 

The participant describes how she encountered no problems while perusing the application. However, when tasked with selecting a simple option, she struggled. The moderator notices as she grimaces and fumbles around before eventually landing on the correct path. 

  • Focus Groups: Over to a focus group with more study participants:

Interviewer: So, would you prefer the menu button at the bottom of the screen or on the left?

Participant 1: Personally, I’d like it below so it’s always visible.

Participant 2: I disagree, I prefer that it’s out of sight on the left. Everyone knows that menu buttons are usually on the left anyway. 

Alternatively, you can display text using word clouds. These visual representations display a cluster of words in different sizes. The bigger and bolder a word appears, the more frequently it’s mentioned in textual data. 

Mine qualitative inputs from transcripts, documents, or any open-ended responses. Use software such as Tagxedo, Wordle, or WordItOut to generate your own clouds. 

Word clouds help stakeholders identify keywords representing themes and ideas from collected data. Use them to better understand client pain points or analyze employee sentiment. Further, they’re used to simplify technical data and identify new SEO keywords for targeting. 

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Tools for Presenting Qualitative Data

What’s the end goal of presenting qualitative data? 

To inform the audience (composed of stakeholders and decision-makers) and inspire them into action. You’ve undoubtedly heard of the phrase “data-driven decision-making.” Well, these applications help facilitate exactly that.

Gone are the days of manually creating charts in Excel and exporting them into a PowerPoint. Nowadays, researchers call upon specialized software to organize and present qualitative data.

The prevalence of APIs enables user data collection from various touch points. Data visualization tools such as Google Studio, Power BI, or Tableau enable data collation into one database. Use them to organize and prepare data before analyzing and presenting. 

Visualization tools turn static data into interactive dashboards with graphs and charts. Researchers use color coding, filters, slicers, and annotations to give the data a narrative. To tell a story. 

Simply looking at a dashboard gives the audience the gist of insights. Viewers slice and dice the data as they see fit, drawing their own conclusions. This becomes especially useful for various stakeholders interested in different outcomes from research. It helps drive informed strategic decision-making. 

Sharing insights across teams increases organization-wide collaboration.

No matter your tool of choice, keep an eye out for these universal yet essential features:

  • Ease-of-use
  • Data visualization tools
  • Data collection and management capabilities (from multiple sources) 
  • Collaborative features
  • Advanced analytical features

A Case for Marvin

Ideally, you want one tool for data collection, analysis, and presentation. Here’s why Marvin is perfect for generating and sharing impactful insights:

Collection

A powerful research repository tool, Marvin integrates with applications UX professionals love. It’s home for ALL your data. And we mean all of it — quantitative data, too! 

Use transcription within Marvin to turn conversations and recordings into editable text. Marvin is multilingual, offering transcription in over 40 languages and dialects. Don’t let geography or language barriers hinder your research. Preserve insights and conduct deeper analysis of user responses. 

Marvin’s AI generates summaries and time-stamped insights while you’re conducting interviews. So you can concentrate wholly on the line of questioning. 

Analysis

Marvin streamlines and expedites research workflows. 

Automation software conducts initial analysis on surveys and interviews. It even creates charts and graphs to summarize results. Marvin’s AI is proficient at surfacing actionable insights that humans might’ve ordinarily missed. Don’t begin from scratch.

Interrogate your entire repository with Ask AI, a Chat-GPT-esque search engine. Connect the dots across projects. 

Marvin facilitates powerful thematic analysis. Use the Analyze tab to create and modify codes or themes. Merge codes, or nestle them under overarching ones. 

Spend less time on manual tasks and more time on analysis with Marvin.

Presentation

It’s time to present your findings to stakeholders. 

Create fun, stunning and interactive reports with Marvin. Leverage multimedia capabilities by importing audio and video highlights into the report. Add quotes directly from customer transcripts so that viewers can hear from users. Elevate the voice of the user.

Share reports effortlessly with colleagues and peers. They only need a link to view a file.

What are you waiting for? Sign up for a free demo now!

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Best Practices for Reporting on Qualitative Data

The primary objective of all data reporting is to communicate findings clearly. This empowers stakeholders to act on insights and make informed decisions. Employ these practices to create powerful qualitative presentations:

Understand Your Audience

Who are you presenting to? 

Stakeholders have different priorities and takeaways from qualitative research. Leadership and decision-makers expect high-level strategic insights. Department heads are more interested in tactical and operational implications. Read the room. Tailor presentations to your audience’s needs.

Choose the Right Visualizations

Present findings in a visually appealing format using charts, graphs, and infographics. What visuals best convey the narrative you’re trying to communicate? Charts and bar graphs help display changes in a variable over time. Pie charts or word clouds show patterns that emerge from thematic analysis. 

The right data visualization makes research data clear and comprehensible

Provide Context

Synthesize qualitative insights with quantitative data to provide an overview of the data.

Identify key themes or patterns to serve as a foundation for analysis. Use real-world examples, observations, and quotes to enhance your narratives. Finally, contextualize findings with your research objectives. How do your insights tie into answering your research question(s)?

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Keep It Simple

Ensure visuals and other elements are clean and simple. This way, the audience understands your points easily. Focus on showcasing data that speaks to stakeholder interests. Don’t display every single data point or insight that you gleaned from research. 

This ensures that viewers retain key takeaways without suffering from dreaded information overload.

Use Color & Formatting

Use color intentionally. Adding different shades guides your audience’s attention to important data elements. Beware of using too many colors though, as that causes more confusion among viewers. 

Remember to label items clearly. When inserting text into your presentation, differentiate between body text and participant quotes. Use indentation and new lines to ensure readability.

Be Transparent

Outline and document the methodology used during all stages. How was data collected and analyzed? Carefully select the level of detail you’ll include. Attributing quotes correctly, and linking insights to sources helps people follow the paper trail. Further enhancing a finding’s credibility. 

Transparency in qualitative research helps maintain its rigor, trustworthiness, and data integrity. Over time, this facilitates review, critique and improvement of a researcher’s work. Furthermore, it establishes trust in research and communicates its value to an organization.

Conduct Quality Checks

Perform a thorough quality check of your presentation. Proofread it for clarity and coherence. Have a neutral and unbiased person review it to determine whether key points hit home. Eliminate any errors that could confuse people.

Keep It Ethical

Qualitative research involves people sharing their personal stories and information. First, obtain a participant’s written consent to use their data. Protect their identity by anonymizing them or using pseudonyms. 

Don’t misrepresent findings by altering data to fit your initial hypothesis. Avoid becoming selective when including or excluding results. Embrace the complexity – it doesn’t matter if the results don’t align with your expectations or preconceived notions.

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Challenges in Presenting Qualitative Data

Reader beware. Qualitative data’s convoluted nature comes with its own trials and tribulations. Plan studies (carefully) in advance to avoid these pitfalls of presenting qualitative data:

  1. Information overload: Assimilating large swathes of data from multiple sources helps gather different perspectives. However, it’s impossible to use all the data collected. The sheer volume makes organization and analysis cumbersome. There’s too much data to sift through and analyze.

Learn how Entertainment Partners use Marvin to organize terabytes of daily user data. 

  1. Time consumption: Analyzing qualitative data involves long hours. Researchers spend inordinate amounts of time examining, interpreting, and coding non-numerical data. Visualizing qualitative data is tough due to its complexity. 

This results in delayed timelines, hindering the ability to conduct in-depth analysis.

  1. Subjectivity: Research quality is heavily dependent on the researcher’s skills, biases, and idiosyncrasies. Rooted in interpretation, qualitative analysis differs from one researcher to another. Variation in interpreting and coding data affects the consistency and reliability of results.
  2. Replicability: Qualitative studies are dynamic and highly context dependent. Each researcher might have a different approach, so validating and replicating studies or building on them is not viable. It’s tough to assess and maintain qualitative rigor. 

Thus, research findings are not entirely generalizable or reliable.

  1. Bias: While it’s inherent in every study, it’s important to leave any preconceived notions behind. Watch out and try to mitigate these different types of bias:
    • Sampling and self-selection bias: Part of a population becomes underrepresented in a sample. Or individuals voluntarily participate in a study. Affects generalizability. 
    • Confirmation bias: Researchers focus on data that supports their hypothesis, ignoring any contradictions. 
    • Hawthorne effect: Participants change their behavior if they know researchers are observing them.
    • Observer-expectancy effect: Participants change their behavior to achieve the researcher’s desired effect. Happens subconsciously. 
    • Artificial scenario: The artificial nature of the study doesn’t reflect reality. Findings offer limited information, which might be inaccurate. 
  2. Ethical challenges: Researchers must balance maintaining participant anonymity and confidentiality. This poses problems when presenting findings. Be careful while using descriptions or quotes that inadvertently reveal people’s identities. 
  3. Stakeholder reception: Qualitative analysis isn’t as widely accepted as its quantitative counterpart. The scientific and business community don’t use it for their everyday decision-making. Yet.
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Frequently Asked Questions (FAQs)

Still have pressing questions about presenting qualitative data? We tackle a few below: 

How to Ensure Objectivity When Presenting Qualitative Data?

Objective data allows viewers to draw relevant and accurate conclusions. Most importantly, it establishes trust in results. Use the following criteria to evaluate research data:

QualitativeQuantitative
CredibilityInternal validity
TransferabilityExternal validity
ConfirmabilityObjectivity
DependabilityReliability

Items in the qualitative column are analogous to their quantitative counterpart. Here’s how to ensure your data is credible, transferable, dependable, and confirmable:

  • Credibility: Use triangulation to cross-verify information from multiple sources. Conduct peer examination to ensure data is consistent with findings. 
  • Transferability: Use thick or rich descriptions that detail the study setting and observations.
  • Confirmability and Dependability: Audit trails document processes and steps taken during the study. They offer traceability so that people can verify the data.

How Long Should a Qualitative Data Presentation Be?

Not too long. You don’t want to bore or overwhelm your audience.

Consider the following when determining the length of your presentation:

  • Audience: Tailor presentations to your audience and their interest in the topic. Keep it simple for people without knowledge of research. 
  • Complexity: The more complex a theme or topic, the more explanation (and time) needed.

Remember to leave time for questions at the end, just like we did with this section here.

How to Avoid Bias When Presenting Qualitative Data?

You can’t fully eradicate bias from a qualitative study. Take the following steps to mitigate bias as much as possible:

  1. Ask objective questions and avoid leading ones
  2. Use multiple people to code data
  3. Have peers review your results
  4. Triangulate insights with more data sources
  5. Seek possible alternate explanations
  6. Acknowledge researcher bias in reports
  7. Maintain detailed records throughout the study

Can You Combine Qualitative and Quantitative Data in One Presentation?

Yes, you can and should.

Qualitative insights complement quantitative ones, offering a well-rounded view of the user experience.

Quantitative data provides a better understanding of a phenomenon. Qualitative insights offer rich context into the underlying thinking behind people’s behavior. It helps you understand what the numbers mean and what the implications are.

Include statistical data to highlight overarching trends and patterns. Add qualitative findings such as quotes and anecdotes to humanize insights. Present narratives that relate to your audience. Make sure it’s cohesive, i.e., easy to follow and comprehend. 

Successful qualitative data presentation balances both insights, creating stories that resonate with viewers.

Conclusion

Presenting qualitative data the right way makes your research impactful. Possibly as valuable a skill as conducting rigorous thematic analysis. Making it accessible helps convince your audience of the research’s value to a company. 

A clear, meaningful qualitative data presentation engages and informs its viewers. Narratives weave themes together, connecting with the audience on a personal level. Visual storytelling using graphs and text highlights important insights. A company’s decision-makers commit these to memory. 

Key stakeholders use qualitative insights to make strategic-level decisions. Ones that influence future product updates and with it, business performance. 

Elevate your qualitative data presentation with Marvin. Sign up for a free account today to begin exploring!

Krish Arora leverages his experience as a finance professional to turn data into insights. A passionate writer with a strong appreciation for language, Krish crafts compelling stories with numbers and words to elevate the practice of user research.

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