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Company focus

KAYAK

What caused the sudden 30% decrease in mobile app bookings for KAYAK's hotel search feature last week?

Prepared by NextSprints

15 mins
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Data Analysis Problem Solving Product Strategy Travel E-commerce Mobile Apps Conversion Optimization Data Analysis Root Cause Analysis Travel Tech Mobile Apps
Product Management Root Cause Analysis Question: Investigating sudden drop in KAYAK's mobile app hotel bookings

Introduction

A sudden 30% decrease in mobile app bookings for KAYAK's hotel search feature last week is a critical issue that demands immediate attention. This significant drop in a core product metric could have far-reaching implications for user satisfaction, revenue, and overall business performance. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

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 this could be a recent change. Has there been any significant update to the app or backend systems in the past two weeks?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, there was a minor UI update. Impact on approach: If yes, we'd focus on the update's impact; if no, we'd look at external factors.

  • Considering user segments, I'm curious about the distribution. Is this decrease uniform across all user types, or is it more pronounced in specific segments?

Why it matters: Helps narrow down if it's a universal issue or segment-specific. Expected answer: The decrease is more significant among repeat users. Impact on approach: Segment-specific issues would lead us to investigate those user journeys more closely.

  • Given the nature of hotel bookings, I'm wondering about seasonality. How does this 30% decrease compare to the same period last year?

Why it matters: Distinguishes between seasonal trends and actual problems. Expected answer: This decrease is abnormal compared to last year. Impact on approach: If seasonal, we'd focus on why this year is different; if not, we'd look at recent changes or market shifts.

  • Thinking about the competitive landscape, have there been any major moves by competitors recently, like promotional campaigns or new features?

Why it matters: External factors can significantly impact user behavior. Expected answer: No significant competitor actions noted. Impact on approach: If yes, we'd analyze our market position; if no, we'd focus more on internal factors.

  • Considering the metric itself, I'm curious about its components. Has there been any change in how we're measuring or defining "mobile app bookings" recently?

Why it matters: Ensures we're comparing apples to apples in our analysis. Expected answer: No changes to the metric definition or measurement. Impact on approach: If changed, we'd need to recalibrate our analysis; if not, we can proceed with our current understanding.

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NextSprints

Updated Jan 22, 2025