JEFFREY ADU
WORK
RESUME
ABOUT
LIVE PRODUCT
LIVE PRODUCT
LIVE PRODUCT
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Feb. 2026 - Mar. 2026
Feb. 2026 - Mar. 2026
Feb. 2026 - Mar. 2026
Designing Reinforcement Loops
Designing Reinforcement Loops
Designing Reinforcement Loops
Contribution rate
Contribution rate
Contribution rate
12%
12%
12%
19%
19%
19%
+58% lift
+58% lift
+58% lift
Post engagement
Post engagement
Post engagement
30%
30%
30%
50%
50%
50%
+73% lift
+73% lift
+73% lift
Return rate 24–48h
Return rate 24–48h
Return rate 24–48h
20%
20%
20%
30%
30%
30%
+50% lift
+50% lift
+50% lift
ROLE
ROLE
ROLE
Product Designer
Product Designer
Product Designer
TOOL
TOOL
TOOL
Figma
Figma AI
Protopie
Lottielab
Claude Code
React Native
Figma
Figma AI
Protopie
Lottielab
Claude Code
React Native
Figma
Figma AI
Protopie
Lottielab
Claude Code
React Native
WHAT I DID
WHAT I DID
WHAT I DID
UX Research
Strategy
UI/UX Design
Usability Testing
UX Research
Strategy
UI/UX Design
Usability Testing
UX Research
Strategy
UI/UX Design
Usability Testing
TEAM
TEAM
TEAM
Founder + 2 Eng
Founder +
2 Eng
Founder + 2 Eng
01 — Context & Overview
01 — Context & Overview
What is Frens Frens and why does this matter?
What is Frens Frens and why does this matter?
What is Frens Frens and why does this matter?
Fren Frens is an early-stage, location-based social platform helping travelers and locals anonymously discover real-time hotspots, conversations, and events around them. With 5K total downloads and 50–100 new downloads per day, the product had promising early traction but was struggling to sustain it.
As the solo product designer, I led end-to-end design of a reinforcement system from qualitative diagnosis through to shipped experience targeting the gap between users discovering the app and actually making it a habit.
Fren Frens is an early-stage, location-based social platform helping travelers and locals anonymously discover real-time hotspots, conversations, and events around them. With 5K total downloads and 50–100 new downloads per day, the product had promising early traction but was struggling to sustain it.
As the solo product designer, I led end-to-end design of a reinforcement system from qualitative diagnosis through to shipped experience targeting the gap between users discovering the app and actually making it a habit.
Fren Frens is an early-stage, location-based social platform helping travelers and locals anonymously discover real-time hotspots, conversations, and events around them. With 5K total downloads and 50–100 new downloads per day, the product had promising early traction but was struggling to sustain it.
As the solo product designer, I led end-to-end design of a reinforcement system from qualitative diagnosis through to shipped experience targeting the gap between users discovering the app and actually making it a habit.
02 — Problem Statement
02 — Problem Statement
Why users weren't sticking
Why users weren't sticking
Why users weren't sticking
The product had traction at the top of the funnel but was hemorrhaging users before they could form a habit. A 30% DAU in the first two weeks collapsed to 8–12% after month one.
Only 8% of users returned after contributing their first post. The team's initial hypothesis pointed to content density — too many empty geographic areas, not enough active users per zone.
But this framing led to the wrong solution. If you try to solve silence by adding more posts, you ignore why the silence feels so defeating in the first place.
The product had traction at the top of the funnel but was hemorrhaging users before they could form a habit. A 30% DAU in the first two weeks collapsed to 8–12% after month one.
Only 8% of users returned after contributing their first post. The team's initial hypothesis pointed to content density — too many empty geographic areas, not enough active users per zone.
But this framing led to the wrong solution. If you try to solve silence by adding more posts, you ignore why the silence feels so defeating in the first place.
The product had traction at the top of the funnel but was hemorrhaging users before they could form a habit. A 30% DAU in the first two weeks collapsed to 8–12% after month one.
Only 8% of users returned after contributing their first post. The team's initial hypothesis pointed to content density — too many empty geographic areas, not enough active users per zone.
But this framing led to the wrong solution. If you try to solve silence by adding more posts, you ignore why the silence feels so defeating in the first place.
03 — Research & Insights
03 — Research & Insights
Diagnosing the Break
Diagnosing the Break
Diagnosing the Break
I ran a two-pronged research effort: behavioral analytics to find where users dropped, and qualitative interviews to understand why. Then a survey (n=40) to validate at scale.
I ran a two-pronged research effort: behavioral analytics to find where users dropped, and qualitative interviews to understand why. Then a survey (n=40) to validate at scale.
I ran a two-pronged research effort: behavioral analytics to find where users dropped, and qualitative interviews to understand why. Then a survey (n=40) to validate at scale.
The key insight I saw was that the issue was not lack of interest. It was lack of
visible reinforcement.
The key insight I saw was that the issue was not lack of interest. It was lack of
visible reinforcement.
The key insight I saw was that the issue was not lack of interest. It was lack of
visible reinforcement.
Deriving my user persona
Deriving my user persona
Deriving my user persona
I then created 3 user personas derived from analytics (2 months), 12 interviews,
and survey (n=40).
I then created 3 user personas derived from analytics (2 months), 12 interviews,
and survey (n=40).
I then created 3 user personas derived from analytics (2 months), 12 interviews,
and survey (n=40).
A Day in the Life of a Fren Frens User
A Day in the Life of a Fren Frens User
A Day in the Life of a Fren Frens User
I then storyboarded a day journey of the social initiator persona, which was very close all the signal theme (lack of visible reinforcement) insights from all my research
I then storyboarded a day journey of the social initiator persona, which was very close all the signal theme (lack of visible reinforcement) insights from all my research
I then storyboarded a day journey of the social initiator persona, which was very close all the signal theme (lack of visible reinforcement) insights from all my research
04 — Ideation & Exploration
04 — Ideation & Exploration
Designing the Loop
Designing the Loop
Designing the Loop
With the real problem framed, I pivoted strategy entirely. Instead of filling content density, I focused on making every contribution feel witnessed — immediately and continuously.
With the real problem framed, I pivoted strategy entirely. Instead of filling content density, I focused on making every contribution feel witnessed — immediately and continuously.
With the real problem framed, I pivoted strategy entirely. Instead of filling content density, I focused on making every contribution feel witnessed — immediately and continuously.
Bring my pivots into wireframes
Bring my pivots into wireframes
Bring my pivots into wireframes
I translated the hypotheses into low-fidelity wireframes to test whether reinforcement signals increased user confidence in posting.
I translated the hypotheses into low-fidelity wireframes to test whether reinforcement signals increased user confidence in posting.
I translated the hypotheses into low-fidelity wireframes to test whether reinforcement signals increased user confidence in posting.
So tradeoffs I considered
So tradeoffs I considered
So tradeoffs I considered
To drive engagement without overwhelming users, I made deliberate trade-offs between visibility, simplicity, and long-term retention across the reinforcement system.
To drive engagement without overwhelming users, I made deliberate trade-offs between visibility, simplicity, and long-term retention across the reinforcement system.
To drive engagement without overwhelming users, I made deliberate trade-offs between visibility, simplicity, and long-term retention across the reinforcement system.
05 — Design Execution
05 — Design Execution
High-Fidelity System
High-Fidelity System
High-Fidelity System
I translated validated reinforcement signals into a cohesive experience. Each design decision maps directly to a behavioral insight — nothing decorative, everything purposeful.
I translated validated reinforcement signals into a cohesive experience. Each design decision maps directly to a behavioral insight — nothing decorative, everything purposeful.
I translated validated reinforcement signals into a cohesive experience. Each design decision maps directly to a behavioral insight — nothing decorative, everything purposeful.
The goal was to replace silence after posting with visible signals of activity at every
moment in the journey.
The goal was to replace silence after posting with visible signals of activity at every
moment in the journey.
The goal was to replace silence after posting with visible signals of activity at every
moment in the journey.
06 — Iteration & Testing
06 — Iteration & Testing
Validating Through Testing
Validating Through Testing
Validating Through Testing
I ran 5 task-based usability walkthroughs on the low-fidelity wireframes, focused specifically on measuring confidence in posting and perception of activity.
I ran 5 task-based usability walkthroughs on the low-fidelity wireframes, focused specifically on measuring confidence in posting and perception of activity.
I ran 5 task-based usability walkthroughs on the low-fidelity wireframes, focused specifically on measuring confidence in posting and perception of activity.
Scroll to understand and the key iteration: visible activity signals
Scroll to understand and the key iteration: visible activity signals
Scroll to understand and the key iteration: visible activity signals
07 — Impact & Results
07 — Impact & Results
The Numbers After Launch
The Numbers After Launch
The Numbers After Launch
A/B tested in low-density areas, the highest-risk cohort against users who didn't receive reinforcement signals. Results measured over 2 months post-launch.
A/B tested in low-density areas, the highest-risk cohort against users who didn't receive reinforcement signals. Results measured over 2 months post-launch.
A/B tested in low-density areas, the highest-risk cohort against users who didn't receive reinforcement signals. Results measured over 2 months post-launch.
Making activity visible and reinforcing contributions transformed posting from a dead-end into a feedback loop that drives continued engagement.
Making activity visible and reinforcing contributions transformed posting from a dead-end into a feedback loop that drives continued engagement.
Making activity visible and reinforcing contributions transformed posting from a dead-end into a feedback loop that drives continued engagement.
08 — Reflection
08 — Reflection
What I Learned
What I Learned
What I Learned
