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Product Management Root Cause Analysis Question: Investigating sudden drop in TripAdvisor restaurant ratings

Why has the average review rating for restaurants in New York City on TripAdvisor dropped by 0.5 stars over the past month?

Data Analysis Problem Solving Strategic Thinking Travel Hospitality Tech
Data Analysis Root Cause Analysis User Behavior Algorithm Optimization Review Systems

Introduction

The sudden drop in TripAdvisor's average restaurant review ratings for New York City is a concerning trend that requires immediate attention. A 0.5-star decrease over just one month is significant and could have far-reaching implications for both restaurants and the platform itself. To address this issue, I'll employ a systematic approach to identify potential root causes, validate hypotheses, and develop both short-term and long-term solutions.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might be a seasonal factor at play. Has this drop coincided with any major events or holidays in New York City?

Why it matters: Seasonal trends can significantly impact restaurant experiences and reviews. Expected answer: No major events or holidays during this period. Impact on approach: If confirmed, we'd need to look more closely at internal factors or changes in user behavior.

  • Considering the magnitude of the change, I'm wondering about the sample size. Has there been any significant change in the number of reviews being submitted compared to previous months?

Why it matters: A change in review volume could indicate a shift in user engagement or a technical issue. Expected answer: Review volume has remained consistent. Impact on approach: If volume is stable, we'd focus more on content and sentiment analysis of the reviews.

  • Given the specificity to New York City, I'm curious about geographical patterns. Has this trend been observed in other major cities or is it unique to New York?

Why it matters: This helps determine if it's a localized issue or a broader trend. Expected answer: The trend is specific to New York City. Impact on approach: If confirmed, we'd need to investigate NYC-specific factors more closely.

  • Thinking about potential technical issues, have there been any recent updates to the review system or algorithm changes that might affect how ratings are calculated or displayed?

Why it matters: Technical changes can sometimes have unintended consequences on user-facing metrics. Expected answer: No recent major technical changes. Impact on approach: If no changes, we'd focus more on user behavior and external factors.

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