To find the “magic moment” in a user’s journey for Robyn, I would analyze user behavior data to identify when users first engage deeply with features that drive emotional connection, such as sending meaningful messages or returning frequently. By comparing patterns between highly engaged users and those who drop off, I’d pinpoint key actions or sequences that correlate with retention. I’d also gather qualitative feedback through surveys or interviews to understand the emotional impact behind these moments. Combining these insights, I’d run targeted experiments to enhance and highlight these moments, helping users quickly experience the value and connection that Robyn aims to create.

While leading the Commencement 2 Careers Program at Lowell High School, I ran a real-world retention experiment to boost engagement across a 17-week career readiness workshop series. Around week 5, attendance was dipping, so I created a lightweight “growth badge” system to gamify progress — awarding students for completing sessions, participating in mock interviews, or refining their resumes. I used Google Sheets and scripting to automate badge tracking and Google Forms to collect session-level feedback. I analyzed participation patterns and restructured the schedule to prioritize more interactive sessions early on. This led to a 35% increase in retention, with students reporting a stronger sense of progress and motivation. On the technical side, I bring a lot of experience working with Python for data analysis, visualization, and product experimentation. Right now, I’m building an AI-powered medical data dashboard, where I’ve been parsing FHIR-formatted health data, building front-end visualizations (e.g., time-series charts), and integrating with LLMs to help users explore patterns in their own health metrics. This project has taught me how to blend data storytelling, user empathy, and experimentation, exactly the approach I’d bring to designing growth and retention loops at Robyn.

One growth experiment I would run for an app like Robyn is a “Streaks for Sharing” feature, rewarding users who share the app (or a specific experience/moment) for a certain number of days in a row with exclusive content or early access to new features. This taps into Gen Z’s love for personalization, status-based rewards, and social interaction.The goal would be to increase both user retention and virality by creating lightweight, gamified pressure to stay active and bring friends along. Tools I’d use: PostHog or Firebase for tracking daily active users, shares, and drop-off points in the flowSegment or Mixpanel to track cohort behaviors and compare retention between “streak” users vs. control. Python (or SQL) for analyzing user event data and segmenting by behavior. A/B testing framework (PostHog has one) to validate impact of the feature. If successful, this experiment could evolve into a deeper social layer that builds emotional stickiness and brings the Robyn community closer.

One Gen Z-focused app I love is TikTok. It’s more than just entertainment, it’s a cultural engine. What makes TikTok so compelling is how it personalizes the experience through its algorithm, surfaces niche communities, and gives users tools to create content easily and authentically. From a product growth perspective, TikTok nails retention and virality. Features like duets, stitches, and trends encourage creative remixing and social interaction, making the platform feel alive and participatory. It also does a great job at lowering the barrier to entry you don’t need a big following or polished content to go viral, which resonates with Gen Z’s preference for authenticity and expression over perfection.