#career-journey

Covered the PM role for a client's sports-booking platform: 0 → 20K+ users, 5K+ DAU, 2,000+ weekly bookings at peak.

• ▹Ran product for the platform from launch to 20K+ users, 5K+ daily active users and 2,000+ weekly bookings at peak: analysed usage data and customer reviews, prioritised the backlog, led feature discussions with the team, and ran weekly reviews directly with the platform's owner.
• ▹Built an AI feedback platform that pulled 1,000+ feedback items a week from 5 channels (Instagram, support email, Google Maps reviews, call recordings, in-app chat) into one database and dashboard using a browser-automation agent, automating collection and sorting that a full-time support executive had done by hand.
• ▹Used its AI sentiment scores, issue tags and trend summaries to find venue quality as the top complaint; introduced a response process (re-shooting misleading venue photos, escalating issues to venue owners, compensating affected users, delisting repeat offenders) that cut those complaints by 25%+.
• ▹Built the product's behaviour-analytics pipeline: 20+ Firebase custom events exported to BigQuery, with a daily webhook loading the data into the same in-house analysis platform as customer feedback, built and extended with AI coding tools. Used it to redesign search and filters, raising completion of that step by 10%+.
• ▹Designed an AI-personalised reward engine that tailored rewards to each user's bookings and engagement, increasing repeat bookings by 10%+.
• ▹Designed an expectation-vs-experience rating system with 20% off the next booking for completing a review, whatever the rating. Reviews rose from under 5% to 60%+ of completed bookings, and the gap between expectation and experience showed whether a problem was the venue's or the platform's.
• ▹Interviewed 100+ players, coaches and venue owners, mainly in Ahmedabad and Gandhinagar (55% of users and bookings) plus Mumbai, and ran discovery, competitor research and requirements for an AI performance-tracking module.