Introduction
The recent 15% drop in Ola Auto's average ride completion rate is a critical issue that demands immediate attention. This analysis will systematically investigate potential root causes, validate hypotheses, and propose targeted solutions to address this concerning trend in our key performance metric.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Seasonal trends can significantly impact ride demand and driver availability. Expected answer: No major seasonal events correlate with the drop. Impact on approach: If confirmed, we'll focus more on internal factors.
Why it matters: Segmentation could reveal targeted issues affecting specific user groups. Expected answer: The drop is more pronounced among occasional riders. Impact on approach: We'd prioritize investigating the occasional rider experience and onboarding process.
Why it matters: Recent product changes could have unintended consequences on ride completions. Expected answer: A minor update to the driver assignment algorithm was rolled out three weeks ago. Impact on approach: We'd focus on analyzing the impact of this specific change on ride completions.
Why it matters: Ensures we're comparing apples to apples and not facing a data anomaly. Expected answer: No changes to the metric calculation or tracking systems. Impact on approach: We'd rule out measurement issues and focus on actual performance factors.
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