Success Metrics for Uber's Rider Location Search and Pickup Map

You are the product manager for the search map in Uber's app. How would you measure whether it is successful? Explain what success means for this feature, the metrics you would track, which one you would treat as the north star and why, and the guardrails you would watch. ```hint Success means the right place, not just a search Ask what goes wrong in the physical world when this feature fails, such as a driver waiting at the wrong corner, and make sure at least one metric captures that outcome rather than only activity on the screen. ``` ### Clarifying Questions - Does "search map" mean the rider's pickup and destination search with its confirmation map, the map of nearby cars shown before booking, or a driver-side map? - Is the goal a standing health dashboard for the feature, or judging a specific change that is about to launch? - Should the effect on drivers, such as finding the rider at pickup, count toward the feature's success? - Are all markets in scope, including cities where street addresses are unreliable? ### What a Strong Answer Covers - A clear statement of the feature's job for riders and its downstream effect on drivers - Metrics mapped to each step, from starting a search to meeting the driver and arriving at the right destination - One north-star metric justified against alternatives such as completed rides or search volume - Guardrails such as latency and overall request conversion, plus segment cuts like airports and poorly addressed markets - How to interpret ambiguous movements, for example a rise in pin adjustments ### Follow-up Questions - After a release, riders adjust the map pin after selecting a search result much more often. Is that good or bad, and how would you find out? - How would you measure success differently at a large airport? - Your north star improved, but completed rides stayed flat. What do you tell leadership?