Overview

Problem

Solution

Our goal was to design an intuitive mobile health platform that simplifies symptom reporting, connects users to relevant care options, and provides personalized wellness guidance—all while reducing cognitive load and supporting users with varying levels of health literacy.

Overview

Problem

Solution

Our goal was to design an intuitive mobile health platform that simplifies symptom reporting, connects users to relevant care options, and provides personalized wellness guidance—all while reducing cognitive load and supporting users with varying levels of health literacy.

Overview

Problem

Solution

Our goal was to design an intuitive mobile health platform that simplifies symptom reporting, connects users to relevant care options, and provides personalized wellness guidance—all while reducing cognitive load and supporting users with varying levels of health literacy.

9 month completion

Lead UX Designer (me) • Product Designer (2) • Full-Stack Developers (3) • Project Manager • Marketing (3)

User Interviews • Empathy Mapping • Competitive Analysis • Info Architecture • Figma Prototyping • Usability Testing

9 month completion

Lead UX Designer (me) • Product Designer (2) • Full-Stack Developers (3) • Project Manager • Marketing (3)

User Interviews • Empathy Mapping • Competitive Analysis • Info Architecture • Figma Prototyping • Usability Testing

We designed Erinlé's mobile health app to translate complex biometric data into a clear, personalized snapshot of overall wellness.

We designed Erinlé's mobile health app to translate complex biometric data into a clear, personalized snapshot of overall wellness.

We designed Erinlé's mobile health app to translate complex biometric data into a clear, personalized snapshot of overall wellness.

Since we were starting from zero, I built the design and research process from the ground up. We leaned on Lean UX methods (rapid testing, tight feedback loops) but I also layered in statistical methods, scientific inference, and other research and design strategies to make sure our insights were reliable and not just “gut feelings.” Some of that included:


  • Randomization → We switched up task orders during usability testing so results weren’t biased by repetition.

  • Replication → Tested across different demographics to make sure the design worked for more than one type of user.

  • Factorial Thinking → Looked at how multiple variables (like notification timing + navigation clarity) impacted drop-offs.

  • Mixing Methods → Combined usability metrics (completion time, error rate) with interviews so we understood not just what users did, but why.

Since we were starting from zero, I built the design and research process from the ground up. We leaned on Lean UX methods (rapid testing, tight feedback loops) but I also layered in statistical methods, scientific inference, and other research and design strategies to make sure our insights were reliable and not just “gut feelings.” Some of that included:


  • Randomization → We switched up task orders during usability testing so results weren’t biased by repetition.

  • Replication → Tested across different demographics to make sure the design worked for more than one type of user.

  • Factorial Thinking → Looked at how multiple variables (like notification timing + navigation clarity) impacted drop-offs.

  • Mixing Methods → Combined usability metrics (completion time, error rate) with interviews so we understood not just what users did, but why.

Since we were starting from zero, I built the design and research process from the ground up. We leaned on Lean UX methods (rapid testing, tight feedback loops) but I also layered in statistical methods, scientific inference, and other research and design strategies to make sure our insights were reliable and not just “gut feelings.” Some of that included:


  • Randomization → We switched up task orders during usability testing so results weren’t biased by repetition.

  • Replication → Tested across different demographics to make sure the design worked for more than one type of user.

  • Factorial Thinking → Looked at how multiple variables (like notification timing + navigation clarity) impacted drop-offs.

  • Mixing Methods → Combined usability metrics (completion time, error rate) with interviews so we understood not just what users did, but why.

We also set up hypothesis tables and prioritization maps to keep the team aligned—basically making sure we weren’t just building cool features but solving real user and business problems.

During the design process…

During the design process…

During the design process…

We kept things scrappy but structured, running lightweight design sprints so we could move fast without losing focus:


  1. Mapping the App – First, we sketched out the Information Architecture basics: Home, Notifications, Care, Community, Shop, Profile. Just the bare bones so everyone was aligned.

  2. Prototyping – We started super rough with low-fidelity flows, then quickly turned them into clickable Figma prototypes so we could put something in front of users fast.

  3. Testing & Iterating – We ran quick sessions to watch where people stumbled (spoiler: the medical jargon and multi-step flows tripped almost everyone up). From there, we stripped things down, rewrote terms, and made interactions more direct.

  4. Refining with Accessibility – Instead of leaving accessibility for last, we baked in WCAG 2.1 compliance as part of the polish. That meant clearer language for readability, stronger contrast ratios, bigger tap targets, and adding proper labels/alt text so the app worked well with screen readers.

What we built

What we built

What we built

We ended up creating a set of features that felt both practical and human.


Users could report their symptoms in whatever way worked best for them—typing in a search, tapping an affected area on the body, or sliding on a pain scale. All of that fed into a Weekly Health Report, which turned messy health data into a clean, easy-to-read dashboard.


To make sure people didn’t feel isolated, we built a Community space with reels and posts where users could learn, share, and connect around health topics.


And finally, we added a Shop for remedies, where users could buy supplements that were actually tied to their health profile—so it wasn’t just another marketplace, it was personalized care.

We used task-based navigation and progressive disclosure to design a seamless ecosystem where users can easily find care providers and manage personalized remedies within a single, unified flow.

We used task-based navigation and progressive disclosure to design a seamless ecosystem where users can easily find care providers and manage personalized remedies within a single, unified flow.

We used task-based navigation and progressive disclosure to design a seamless ecosystem where users can easily find care providers and manage personalized remedies within a single, unified flow.

By applying strategies like information hierarchy and contextual grouping, we created an experience that empowers users to confidently take control of their health without cognitive overload or decision fatigue.

Usability testing showed that the pain-mapping flow made symptom entry 28% faster, which meant people could get through it without frustration.


After we cut down on confusing steps in navigation and notifications, task completion rates jumped by 34%.


On top of that, the accessibility updates (built to WCAG standards) meant users with vision impairments were able to complete flows on their own during testing, something that wasn’t possible before.

Usability testing showed that the pain-mapping flow made symptom entry 28% faster, which meant people could get through it without frustration.


After we cut down on confusing steps in navigation and notifications, task completion rates jumped by 34%.


On top of that, the accessibility updates (built to WCAG standards) meant users with vision impairments were able to complete flows on their own during testing, something that wasn’t possible before.

Usability testing showed that the pain-mapping flow made symptom entry 28% faster, which meant people could get through it without frustration.


After we cut down on confusing steps in navigation and notifications, task completion rates jumped by 34%.


On top of that, the accessibility updates (built to WCAG standards) meant users with vision impairments were able to complete flows on their own during testing, something that wasn’t possible before.

Conclusion

Our stakeholders gave the green light to move forward with this direction, which was a huge vote of confidence in both the product vision and the process we put in place.

Our stakeholders gave the green light to move forward with this direction, which was a huge vote of confidence in both the product vision and the process we put in place.

Our stakeholders gave the green light to move forward with this direction, which was a huge vote of confidence in both the product vision and the process we put in place.

For me, the biggest takeaway was that balancing rigorous research with lean, fast-moving design sprints is what made this possible. By keeping methods lightweight but grounded in real data, we stayed aligned as a team, built stakeholder trust, and delivered something that genuinely worked for people.

Copyright 2025 Miyya Cody

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