At BHANZU, I turned insights from more than 80 live sessions into prioritized product problem statements. I also authored a root cause analysis and PRD for defects in the Maverick pacing algorithm, presenting findings that influenced roadmap decisions.
After synthesizing feedback from more than 100 parent PTM sessions, I helped drive two dashboard and syllabus enhancements that improved user satisfaction by 20%. I also reported platform access issues from live math sessions, enabling data-driven resolutions that reduced session failures by 30%.
For OutLoud, I shaped product strategy through user interviews and surveys, contributing to a shipped voice-first AI product with more than 25 live users. I established a North Star metric of 40% Week-4 retention and iterated on the product through direct outreach.
I’ve also worked on AI agent design for SaaS support operations, product analytics, and product strategy projects. Across these projects, I’ve used research, prioritization, and prototyping to turn user needs into product decisions and testable solutions.
