Question: Lyft Driver Cancellations
Explore how to methodically diagnose an increase in Lyft driver cancellations using a structured analytical framework. Learn to segment data by geography, time, and driver experience, form hypotheses about surge pricing and app issues, and propose clear validation steps. This lesson helps you develop strategic problem-solving skills for product management interviews.
Interview question
Diagnose why Lyft driver cancellations increased.
By the end of this exercise, you’ll confidently demonstrate your ability to methodically diagnose an unexpected metric change, specifically, an increase in Lyft driver cancellations, using a structured analytical framework. You’ll learn how to clearly segment the data, hypothesize plausible root causes, and propose actionable next steps.
Scenario overview
Imagine you’re a PM at Lyft. Your operations team reports a concerning issue:
Driver cancellations have increased by 15% in the past month.
As a PM, it’s critical to approach this systematically, clearly diagnose the root cause, and articulate a thoughtful, actionable response.
Step 1: Confirm the metric and context
First, let’s clarify what this metric precisely means:
What exactly ...