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.

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What exactly are segments?

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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.

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What filters can I use?

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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.

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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.

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

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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. 

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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.

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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.

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When should you use segments?

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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.

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How segments help you to unlock data magic 💫

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

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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.

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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.

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

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How to create a segment

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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. 

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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! 

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Help articles
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How to add a group tag in a study URL for participants
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How to integrate with a participant recruitment panel

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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!

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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.

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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.

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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. 

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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. 

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What is Affinity Mapping? 🗺️

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

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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.

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What is an Affinity Diagram? 🖼️

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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. 

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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.

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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?

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1. Start with a large space

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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.

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2. Record all notes

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

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3. Look for patterns

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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.

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4. Create a group/theme

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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.

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5. Give each theme or group a name

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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.)

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6. Determine priorities

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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.

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7. Report on your findings

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

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How to define research themes 🔬

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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. 

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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:

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• 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

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Wrap up 🌯

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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.

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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.

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In the realm of financial services, complexity isn't just a challenge, it's the default state. From intricate investment products to multi-layered insurance policies to complex fee structures, financial services are inherently complicated. But your users don't want complexity; they want confidence, clarity, and control over their financial lives.

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How to keep things simple with good UX research 

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Understanding how users perceive and navigate complexity requires systematic research. Optimal's platform offers specialized tools to identify complexity pain points and validate simplification strategies:

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Uncover Navigation Challenges with Tree Testing

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Complex financial products often create equally complex navigation structures:

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How can you solve this? 

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• Test how easily users can find key information within your financial platform
• Identify terminology and organizational structures that confuse users
• Compare different information architectures to find the most intuitive organization

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Identify Confusion Points with First-Click Testing

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Understanding where users instinctively look for information reveals valuable insights about mental models:

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How can you solve this? 

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• Test where users click when trying to accomplish common financial tasks
• Compare multiple interface designs for complex financial tools
• Identify misalignments between expected and actual user behavior

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Understand User Mental Models with Card Sorting

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Financial terminology and categorization often don't align with how customers think:

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How can you solve this? 

• Use open card sorts to understand how users naturally group financial concepts
• Test comprehension of financial terminology
• Identify intuitive labels for complex financial products

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Practical Strategies for Simplifying Financial UX

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1. Progressive Information Disclosure

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Rather than bombarding users with all information at once, layer information from essential to detailed:

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• Start with core concepts and benefits
• Provide expandable sections for those who want deeper dives
• Use tooltips and contextual help for terminology
• Create information hierarchies that guide users from basic to advanced understanding

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2. Visual Representation of Numerical Concepts

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Financial services are inherently numerical, but humans don't naturally think in numbers—we think in pictures and comparisons.

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What could this look like? 

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• Use visual scales and comparisons instead of just presenting raw numbers
• Implement interactive calculators that show real-time impact of choices
• Create visual hierarchies that guide attention to most relevant figures
• Design comparative visualizations that put numbers in context

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3. Contextual Decision Support

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Users don't just need information; they need guidance relevant to their specific situation.

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How do you solve for this? 

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• Design contextual recommendations based on user data
• Provide comparison tools that highlight differences relevant to the user
• Offer scenario modeling that shows outcomes of different choices
• Implement guided decision flows for complex choices

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4. Language Simplification and Standardization

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Financial jargon is perhaps the most visible form of unnecessary complexity. So, what can you do? 

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• Develop and enforce a simplified language style guide
• Create a financial glossary integrated contextually into the experience
• Test copy with actual users, measuring comprehension, not just preference
• Replace industry terms with everyday language when possible

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Measuring Simplification Success

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To determine whether your simplification efforts are working, establish a continuous measurement program:

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1. Establish Complexity Baselines

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Use Optimal's tools to create baseline measurements:

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• Success rates for completing complex tasks
• Time required to find critical information
• Comprehension scores for key financial concepts
• User confidence ratings for financial decisions

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2. Implement Iterative Testing

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Before launching major simplification initiatives, validate improvements through:

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• A/B testing of alternative explanations and designs
• Comparative testing of current vs. simplified interfaces
• Comprehension testing of revised terminology and content

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3. Track Simplification Metrics Over Time

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Create a dashboard of key simplification indicators:

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• Task success rates for complex financial activities
• Support call volume related to confusion
• Feature adoption rates for previously underutilized tools
• User-reported confidence in financial decisions

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Where rubber hits the road: Organizational Commitment to Clarity

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True simplification goes beyond interface design. It requires organizational commitment at the most foundational level:

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• Product development: Are we creating inherently understandable products?
• Legal and compliance: Can we satisfy requirements while maintaining clarity?
• Marketing: Are we setting appropriate expectations about complexity?
• Customer service: Are we gathering intelligence about confusion points?

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When there is a deep commitment from the entire organization to simplification, it becomes part of a businesses’ UX DNA. 

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Conclusion: The Future Belongs to the Clear

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As financial services become increasingly digital and self-directed, clarity bcomes essential for business success. The financial brands that will thrive in the coming decade won't necessarily be those with the most features or the lowest fees, but those that make the complex world of finance genuinely understandable to everyday users.

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By embracing clarity as a core design principle and supporting it with systematic user research, you're not just improving user experience, you're democratizing financial success itself.

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