October 24, 2023

Dive deeper into participant responses with segments

Our exciting new feature, segments, saves time by allowing you to create and save groups of participant responses based on various filters. Think of it as your magic wand to effortlessly organize and scrutinize the wealth of data and insight you collect in your studies. Even more exciting is that the segments are available in all our quantitative study tools, including Optimal Sort, Treejack, Chalkmark, and Questions.

What exactly are segments?

In a nutshell, segments let you effortlessly create and save groups of participants' results based on various filters, saving you and the team time and ensuring you are all on the same page. 

A segment represents a demographic within the participants who completed your study. These segments can then be applied to your study results, allowing you to easily view and analyze the results of that specific demographic and spot the hidden trends.

What filters can I use?

Put simply, you've got a treasure trove of participant data, and you need to be able to slice and dice it in various ways. Segmenting your data will help you dissect and explore your results for deeper and more accurate results.

Question responses: Using a screener survey or pre - or post-study questions with pre-set answers (like multi-choice), you can segment your results based on their responses.

URL tag: If you identify participants using a unique identifier such as a URL tag, you can select these to create segments.

Tree test tasks, card sort categories created, first click test and survey responses: Depending on your study type, you can create a segment to categorize participants based on their response in the study. 

Time taken: You can select the time taken filter to view data from those who completed your study in a short space of time. This may highlight some time wasters who speed through and probably haven’t provided you with high-quality responses. On the other hand, it can provide insight into A/B tests for example, it could show you if it’s taking participants of a tree test longer to find a destination in one tree or another.

With this feature, you can save and apply multiple segments to your results, using a combination of AND/OR logic when creating conditions. This means you can get super granular insights from your participants and uncover those gems that might have otherwise remained hidden.

When should you use segments?

This feature is your go-to when you have results from two or more participant segments. For example, imagine you're running a study involving both teachers and students. You could focus on a segment that gave a specific answer to a particular task, question, or card sort. It allows you to drill down into the nitty-gritty of your data and gain more understanding of your customers.

How segments help you to unlock data magic 💫

Let's explore how you can harness the power of segments:

Save time: Create and save segments to ensure everyone on your team is on the same page. With segments, there's no room for costly data interpretation mishaps as everyone is singing from the same hymn book.

Surface hidden trends: Identifying hidden trends or patterns within your study is much easier.  With segments,  you can zoom in on specific demographics and make insightful, data-driven decisions with confidence.

Organized chaos: No more data overload! With segments, you can organize participant data into meaningful groups, unleashing clarity and efficiency.

How to create a segment

Ready to take segments for a spin?  To create a new segment or edit an existing one, go to  Results > Participants > Segments. Select the ‘Create segment’ button and select the filters you want to use. You can add multiple conditions, and save the segment.  To select a segment to apply to your results, click on ‘All included participants’ and select your segment from the drop-down menu.  This option will apply to all your results in your study. 


We can't wait to see the exciting discoveries you'll make with this powerful tool. Get segmenting, and let us know what you think! 

Help articles

How to add a group tag in a study URL for participants

How to integrate with a participant recruitment panel
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Affinity mapping - an introduction

User research is key to discovering the inner workings of your users’ minds – their emotional, organizational, informative needs and desires. These are all super important to creating a user experience that is intuitive and meeting your users’ needs in a way that means they feel loved, cared for and considered. All the deep understanding stuff that keeps them coming back!

Qualitative research allows you to collect verbatim data from participants that give insights into why they do or feel things. You can even get into whether ‘Dee’ understood how the website worked or why ‘Andrew’ would (or wouldn’t) revisit the app outside of testing.

Gathering these awesome insights is one step. Analyzing and organizing these is a skill and talent in its own right. And armed with the right tools or methods it can be immersive, interesting and a great way to get under the skin of your users. Let’s take a look at affinity mapping as a method of analyzing this data - as a tool it can help researchers visualize and easily group and theme data.

Affinity mapping is used outside of the UX world and can be done independently, however is a great analysis method to use collaboratively. For researchers, it can be a great tool to collaborate and engage the team and potentially stakeholders. Bringing people together to identify, discuss and resolve user experience issues. 

Here we’ll lay out what affinity mapping is, specifically why it’s useful for user research and set out key steps to get you underway. 

What is Affinity Mapping? 🗺️

By definition, affinity mapping is the process of collecting, organizing, and grouping qualitative data to create an affinity diagram.

Put simply it is a tool to group, map, sort and categorize information. A tool where you’ll look at the information and patterns of your qualitative user research and work to group these together to make sense of them. It helps you to find patterns, similar outcomes and insights that allow you to draw conclusions and collate results in a cohesive manner, then report to the wider team in a way that makes sense and provides a clear road to applicable and achievable outcomes.

What is an Affinity Diagram? 🖼️

An affinity diagram is what you have once you have gone through the affinity mapping process. It is the final ‘diagram’ of your grouping, sorting and categorizing. An ordered visual sorting of insights and information from your user research. And the place to filter or funnel observations and information into patterns and reach final outcomes. 

Allowing you to see where the key outtakes are and where there may need to be improvements, changes or updates. And from here a roadmap can be decided.

An affinity map using Reframer by Optimal Workshop

Essentially the mapping part is the process of creating the diagram, a visual sorting of insights and information from your user research. So how do you make affinity mapping work for you?

1. Start with a large space

This could be a table, desk, pinboard or even a whiteboard. Somewhere that you can stick, pin or attach your insights to in a collaborative space. Becoming more common recently is the use of shared digital and online whiteboard tools.  allowing people to access and participate remotely.

2. Record all notes

Write observations, thoughts, research insights on individual cards or sticky notes.

3. Look for patterns

As a group read, comment and write notes or observations. Stick each of the notes onto the board, desk or whiteboard. Add, and shuffle into groups as you go. You can keep adding or moving as you go.

4. Create a group/theme

This will start to make sense as more sticky notes are added to the map. Creating groups for similar observations or insights, or for each pattern or theme.

Create a group/theme using affinity mapping

5. Give each theme or group a name

As more notes are added there will be natural groups formed. Openly discuss if there are notes that are more difficult to categorize or themes to be decided. (We’ve outlined some ideas for UX research themes in another section below.)

6. Determine priorities

You’ve tidied everything into themes and groups, now what? How do you decide which of these are priorities for your organization? Discussion and voting can be the best way to decide what outcomes make the most sense and may have the biggest impact on your business.

7. Report on your findings

Pulling together and reporting on the findings through your affinity diagram process should be key to putting actionable outcomes in place.

How to define research themes 🔬

Commonly, user research is digested through thematic analysis. During thematic analysis, you aim to make sense of all the notes, observations, and discoveries you’ve documented across all your information sources, by creating themes to organize the information. 

Depending on your role and the type of research you conduct, the themes you create for your affinity diagram can vary. Here are some examples of affinity groups that you could form from your UX research:

  • User sentiment and facial expressions when completing certain tasks
  • Frequently used words or phrases when describing a product or experience
  • Suggestions for improving your product or experience

Wrap up 🌯

Qualitative user testing and the resulting observations can be some of the best insights you get into your users’ minds. Filtering, organizing and ordering these disparate and very individual observations can be tricky. Especially if done in silo.

So, draw a team together, bring in stakeholders from throughout your organization and work collaboratively to sort, organize and categorize through affinity mapping. This opens the doors to discussion, buy-in and ultimately a collective understanding of user research. Its importance and its role within the organization. And most importantly the real-world implications UX research and its insights have on organizational products and output.

Learn more
1 min read

Dive deeper into participant responses with segments

Our exciting new feature, segments, saves time by allowing you to create and save groups of participant responses based on various filters. Think of it as your magic wand to effortlessly organize and scrutinize the wealth of data and insight you collect in your studies. Even more exciting is that the segments are available in all our quantitative study tools, including Optimal Sort, Treejack, Chalkmark, and Questions.

What exactly are segments?

In a nutshell, segments let you effortlessly create and save groups of participants' results based on various filters, saving you and the team time and ensuring you are all on the same page. 

A segment represents a demographic within the participants who completed your study. These segments can then be applied to your study results, allowing you to easily view and analyze the results of that specific demographic and spot the hidden trends.

What filters can I use?

Put simply, you've got a treasure trove of participant data, and you need to be able to slice and dice it in various ways. Segmenting your data will help you dissect and explore your results for deeper and more accurate results.

Question responses: Using a screener survey or pre - or post-study questions with pre-set answers (like multi-choice), you can segment your results based on their responses.

URL tag: If you identify participants using a unique identifier such as a URL tag, you can select these to create segments.

Tree test tasks, card sort categories created, first click test and survey responses: Depending on your study type, you can create a segment to categorize participants based on their response in the study. 

Time taken: You can select the time taken filter to view data from those who completed your study in a short space of time. This may highlight some time wasters who speed through and probably haven’t provided you with high-quality responses. On the other hand, it can provide insight into A/B tests for example, it could show you if it’s taking participants of a tree test longer to find a destination in one tree or another.

With this feature, you can save and apply multiple segments to your results, using a combination of AND/OR logic when creating conditions. This means you can get super granular insights from your participants and uncover those gems that might have otherwise remained hidden.

When should you use segments?

This feature is your go-to when you have results from two or more participant segments. For example, imagine you're running a study involving both teachers and students. You could focus on a segment that gave a specific answer to a particular task, question, or card sort. It allows you to drill down into the nitty-gritty of your data and gain more understanding of your customers.

How segments help you to unlock data magic 💫

Let's explore how you can harness the power of segments:

Save time: Create and save segments to ensure everyone on your team is on the same page. With segments, there's no room for costly data interpretation mishaps as everyone is singing from the same hymn book.

Surface hidden trends: Identifying hidden trends or patterns within your study is much easier.  With segments,  you can zoom in on specific demographics and make insightful, data-driven decisions with confidence.

Organized chaos: No more data overload! With segments, you can organize participant data into meaningful groups, unleashing clarity and efficiency.

How to create a segment

Ready to take segments for a spin?  To create a new segment or edit an existing one, go to  Results > Participants > Segments. Select the ‘Create segment’ button and select the filters you want to use. You can add multiple conditions, and save the segment.  To select a segment to apply to your results, click on ‘All included participants’ and select your segment from the drop-down menu.  This option will apply to all your results in your study. 


We can't wait to see the exciting discoveries you'll make with this powerful tool. Get segmenting, and let us know what you think! 

Help articles

How to add a group tag in a study URL for participants

How to integrate with a participant recruitment panel
Learn more
1 min read

Why Understanding Users Has Never Been Easier...or Harder

Product, design and research teams today are drowning in user data while starving for user understanding. Never before have teams had such access to user information, analytics dashboards, heatmaps, session recordings, survey responses, social media sentiment, support tickets, and endless behavioral data points. Yet despite this volume of data, teams consistently build features users don't want and miss needs hiding in plain sight.

It’s a true paradox for product, design and research teams: more information has made genuine understanding more elusive. 

Because with  all this data, teams feel informed. They can say with confidence: "Users spend 3.2 minutes on this page," "42% abandon at this step," "Power users click here." But what this data doesn't tell you is Why. 

The Difference between Data and Insight

Data tells you what happened. Understanding tells you why it matters.

Here’s a good example of this: Your analytics show that 60% of users abandon a new feature after first use. You know they're leaving. You can see where they click before they go. You have their demographic data and behavioral patterns.

But you don't know:

  • Were they confused or simply uninterested?
  • Did it solve their problem too slowly or not at all?
  • Would they return if one thing changed, or is the entire approach wrong?
  • Are they your target users or the wrong segment entirely?

One team sees "60% abandonment" and adds onboarding tooltips. Another talks to users and discovers the feature solves the wrong problem entirely. Same data, completely different understanding.

Modern tools make it dangerously easy to mistake observation for comprehension, but some aspects of user experience exist beyond measurement:

  • Emotional context, like the frustration of trying to complete a task while handling a crying baby, or the anxiety of making a financial decision without confidence.
  • The unspoken needs of users which can only be demonstrated through real interactions. Users develop workarounds without reporting bugs. They live with friction because they don't know better solutions exist.
  • Cultural nuances that numbers don't capture, like how language choice resonates differently across cultures, or how trust signals vary by context.
  • Data shows what users do within your current product. It doesn't reveal what they'd do if you solved their problems differently to help you identify new opportunities. 

Why Human Empathy is More Important than Ever 

The teams building truly user-centered products haven't abandoned data but they've learned to combine quantitative and qualitative insights. 

  • Combine analytics (what happens), user interviews (why it happens), and observation (context in which it happens).
  • Understanding builds over time. A single study provides a snapshot; continuous engagement reveals the movie.
  • Use data to form theories, research to validate them, and real-world live testing to confirm understanding.
  • Different team members see different aspects. Engineers notice system issues, designers spot usability gaps, PMs identify market fit, researchers uncover needs.

Adding AI into the mix also emphasizes the need for human validation. While AI can help significantly speed up workflows and can augment human expertise, it still requires oversight and review from real people. 

AI can spot trends humans miss, processing millions of data points instantly but it can't understand human emotion, cultural context, or unspoken needs. It can summarize what users say but humans must interpret what they mean.

Understanding users has never been easier from a data perspective. We have tools our predecessors could only dream of.  But understanding users has never been harder from an empathy perspective. The sheer volume of data available to us creates an illusion of knowledge that's more dangerous than ignorance.

The teams succeeding aren't choosing between data and empathy, they're investing equally in both. They use analytics to spot patterns and conversations to understand meaning. They measure behavior and observe context. They quantify outcomes and qualify experiences.

Because at the end of the day, you can track every click, measure every metric, and analyze every behavior, but until you understand why, you're just collecting data, not creating understanding.

Seeing is believing

Explore our tools and see how Optimal makes gathering insights simple, powerful, and impactful.