A selection of engagements across product analytics, experimentation and AI growth ops — what the problem was, what I built, and what changed.
Connected each acquisition source to a meaningful product outcome — whether users actually built and published a support AI agent. That gave the team a way to prioritise channels by real product adoption, not just cheap registrations.
Designed a tracking system across passenger and driver journeys — from booking conversion to driver acceptance. A new measurement system revealed where passenger adoption was breaking down and which behaviours were linked to stronger booking engagement.
Worked alongside the product team to instrument every major product update in Amplitude and measure its impact on visitor → paid spiritual-service conversion. Created a consistent system to separate the features that moved monetisation from those that didn't.
Built an experimentation process across models and generation parameters — measuring their impact on stories creation and engagement. This helped the team choose AI configurations based on user response, not just model performance.
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