From mixed qualitative signals to a 94.4% clear answer.
Survey participants recruited for the quantitative study.
Chose the intended option in the clearer iteration, up from 79.1%.
Felt either "extremely confident" or "Confident" in their choice.
Project Overview
Project Overview
The user problem
A shared segmented control component had shown mixed results across two usability sessions (10 participants total, run at different times as part of wider user studies). When presented in a dual-selection context it wasn't universally clear which option was actually selected.
The business objective
This component was used broadly across the application, so a wrong call there carried system-wide risk. The goal was to replace a 10-user anecdote with validation from a much wider sample before committing to a direction.
My role and scale of ownership
I ran the quantitative follow-up end to end: designed two alternative iterations, built the randomized survey, recruited a 138-person domain-agnostic panel, analysed the results, and presented a recommendation with next steps to product and engineering.
How I closed the loop with data
Background
Two prior usability rounds where component was used left it unclear which state read as "selected" in a dual-choice segmented control.
Sample & options
Sent a randomized survey to 138 participants testing two alternative iterations, "1" (67 responses) and "2" (71 responses).
Results
Measured which option each group picked as selected, why in their own words, and how confident they felt.
Conclusion
The 2 iteration was markedly clearer, with concrete suggestions handed off for the next pass.
Execution
Execution
Methodology & Sample
Total Participants: 138 participants
Testing Structure: Randomized survey presenting two toggle variations:
- Group 1: 67 participants tested Toggle Design 1
- Group 2: 71 participants tested Toggle Design 2
Task was domain-agnostic, so no one needed to be part of a specific team to take part which opened up a much larger, faster-to-recruit panel than a moderated study would allow.
Total participants, domain-agnostic.
Tested Design 1: Flush / no padding
Tested Design 2: Bordered / container style
Participants were asked to identify which state (Option A vs. Option B) they perceive as "selected" across two distinct UI styles and explain why.
The styles were presented in 4 separate images at a time and after evaluating each image they rated how confident they felt in their selection.
Design Variation 1 : Which option is selected? (67 answers)
Scenario A
This one!
This one
Reasoning
The solid highlighted background clearly signals the active selection.
The contrasting colour makes Option B look recessed or unselected.
No outer container boundary made it hard to tell the options apart.
Confidence level
at allExtremely
confident
Scenario B
This one
This one!
Reasoning
The highlighted fill clearly stands out against the neutral background.
Flag icons and contrasting text helped reinforce state changes.
The white background surrounding Option A created visual ambiguity.
Confidence level
at allExtremely
confident
Design Variation 2 : Which option is selected? (71 answers)
Scenario A
This one!
This one
Reasoning
Strong contrast and rounded container define Option A as the active/selected state.
The greyed-out appearance of Option B clearly signals an inactive state.
The inner border and background fill created a distinct "button" feel.
Confidence level
at allExtremely
confident
Scenario B
This one
This one!
Reasoning
Clear hierarchy and high contrast make Option B unmistakably active.
The distinct container around the active state eliminates ambiguity between options.
Option B's solid, darker fill reads as pressed-in and selected, fully framed by a white box.
Confidence level
at allExtremely
confident
Results & Business Impact
Results & Business Impact
A clearer segmented control, backed by data
Picked the correct option in the clearer iteration, up from 79.1% in the less clear iteration.
Were secure of their choice, either "extremely confident" (47.9%) or "Confident" (45.1%).
The quantitative pass confirmed that option 2 provided more clarity giving the team a clear, low-risk direction to ship broadly and confidently expanding the segmented control variations in the design system.
Text and flag
Text only
Icons only
Clarity nearly doubled
Correct-option selection rose from 79.1% on the first iteration to 94.4% on the second, due to outer container boundary applied to selected pill, framing and reinforcing reading.
Confidence followed
"Extremely confident" responses grew from 32.8% to 47.9% between iterations: participants weren't just picking correctly more often, they were also more sure of it.
De-risked a shared component
Evaluated the direction for a segmented control used broadly across the application before wider rollout, replacing a close call with a data-backed one.
A repeatable research model
Domain-agnostic recruiting meant no team dependency, making the same quantitative pass reusable for future component decisions.
Clear next steps for the roadmap
Suggestions from both groups, sharper "on" colour cues, an animated state change, were handed directly to design and engineering for the next pass.
Recommendations
Recommendations
What people say about working with me
“Inês is an exceptional user experience researcher and designer. Her dedication to creating a seamless and intuitive experience coupled with the relentless explorations and optimisation of the use of existing design patterns has not gone unnoticed.I worked with Inês on the development of an interface and user flow for a brand new product to support complex research processes for genomics data processing. Her work was crucial in triggering discussions on the technical implementation and her prototypes made several conversations much easier. Inês did not limit herself to just design a like-to-like user experience based on the product team prototypes, she wanted to understand the user needs and translate that into an interface that not only met the needs but exceeded expectations. Inês would iterate over and over again with feedback from product, from users, from engineers and from her own team, I've never seen Inês frustrated by this. Inês was a quick responder, acting fast with a basis for our work and then iterate over and over until we were all satisfied with the result. We worked at the transition between design systems, Inês embraced the challenge with both arms and always ensured constant feedback back to other teams about challenges or usability findings.Inês led the work without ego and made it truly a co-design experience while putting users at the centre. Inês was always prepared to cover for others and putting additional effort at the cost of her own personal time to drive the work forward. Moreover, the collaborative spirit and professionalism demonstrated throughout the design process have been invaluable for me personally. Inês was always very transparent in her communications and ensured she brought all stakeholders and cards to the table so that the best decisions could be made collaboratively.Inês is an inspiration for me and for the colleagues in her team, she truly cares about her work and doing better everyday.”
“Any software development team fervently hopes for a UX designer like Inês. I was very fortunate to work with her in the early stages of a project, where we were defining and adjusting the UI text for several different workflows. Frequently, our conversations led not only to the best placement of in-application content, but enhancements to the design itself.Inês' superpower is the ability to simultaneously hold deep technical nuance of the product, consistency of design standards, and the ability to improvise, while making it all look effortless. She is a great communicator, and conveys her ideas gently, thoughtfully, and thoroughly. She is also an excellent leader who brings people to her understanding by showing, not just telling.I would relish the opportunity to work with Inês again, and cannot overstate my informed opinion that she would be an incredible asset to any organization.”