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Company focus

Getaround

What caused the sudden 50% decrease in new car listings on Getaround's platform in the last week?

Prepared by NextSprints

15 mins
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Problem Solving Data Analysis Strategic Thinking Transportation Sharing Economy Technology Metrics Analysis Root Cause Analysis User Behavior Data-Driven Decision Making Car Sharing
Product Management Root Cause Analysis Question: Investigating sudden decrease in car listings on Getaround platform

Introduction

The sudden 50% decrease in new car listings on Getaround's platform in the last week is a critical issue that demands immediate attention. This significant drop could have far-reaching implications for the platform's health, user satisfaction, and overall business performance. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing 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 this could be related to a recent platform change. Has there been any significant update to the listing process or user interface in the past two weeks?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, we updated the car listing flow last week. Impact on approach: If confirmed, we'd focus on the new listing process as a primary area of investigation.

  • Considering the magnitude of the decrease, I'm wondering about potential technical issues. Have we noticed any unusual error rates or system downtime recently?

Why it matters: Technical problems can cause immediate and drastic drops in user actions. Expected answer: Our monitoring systems haven't reported any major issues. Impact on approach: If no technical issues are found, we'd shift focus to user behavior or external factors.

  • Given the specificity of new car listings, I'm curious about our user segments. Has this decrease been uniform across all user types, or is it more pronounced in certain groups?

Why it matters: Segmented data can reveal targeted issues affecting specific user groups. Expected answer: The decrease is more significant among casual listers compared to power users. Impact on approach: This would lead us to investigate factors specifically impacting casual listers.

  • Considering potential external factors, have there been any recent changes in local regulations or competitor actions that might affect car sharing?

Why it matters: External events can significantly impact user behavior and platform usage. Expected answer: No major regulatory changes, but a competitor launched a promotional campaign last week. Impact on approach: We'd need to assess the impact of competitive actions on our listing volume.

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NextSprints

Updated Mar 29, 2025