Introduction
The decline in rider experience for Uber Airport rides over the past 6 months is a critical issue that demands immediate attention. As we analyze this product challenge, I'll employ a systematic framework to identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.
To tackle this problem, I'll start by clarifying the issue's scope, rule out external factors, and break down the user journey. Then, I'll dive into metric analysis, form data-driven hypotheses, and conduct a thorough root cause analysis. Finally, I'll propose validation methods and outline a comprehensive resolution plan.
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 patterns could indicate a cyclical issue rather than a new problem. Expected answer: No significant seasonal patterns observed. Impact on approach: If seasonal, we'd focus on anticipating and mitigating annual challenges.
Why it matters: Understanding the metric composition helps pinpoint specific areas of decline. Expected answer: It's a composite score including factors like wait times, ride duration, and user ratings. Impact on approach: We'd analyze each component to identify which factors are driving the overall decline.
Why it matters: External changes at airports could significantly impact our service quality. Expected answer: No major airport changes noted, but the decline is more pronounced at certain airports. Impact on approach: We'd focus on airport-specific factors and potentially tailor solutions for different locations.
Why it matters: Driver availability and quality directly impact rider experience. Expected answer: Some fluctuation in driver numbers, but no major changes in quality metrics. Impact on approach: If driver-related, we'd focus on recruitment, retention, and training strategies.
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