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Product Management Root Cause Analysis Question: Investigating sudden drop in Gokada app's new rider sign-ups

What caused the sudden 30% drop in new rider sign-ups on the Gokada app last week?

Data Analysis Problem-Solving Hypothesis Testing Ride-Sharing Transportation Mobile Apps
Data Analysis Product Metrics User Acquisition Root Cause Analysis Ride-Sharing

Introduction

The sudden 30% drop in new rider sign-ups on the Gokada app last week is a critical issue that demands immediate attention. As we analyze this product challenge, we'll follow a systematic framework to identify, validate, and address the root cause while considering both immediate and long-term implications.

Our approach will involve a thorough examination of the problem, generation of data-driven hypotheses, and development of actionable solutions. We'll begin by clarifying the context, then rule out external factors before diving deep into the product ecosystem, user journey, and metric breakdown. This will lead us to form and validate hypotheses, ultimately resulting in 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)

  • Looking at the timing, I'm thinking there might be a recent change in the app or marketing strategy. Has there been any significant update to the app or change in marketing campaigns in the past two weeks?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, we launched a new UI for the sign-up process. Impact on approach: If true, we'd focus on the new UI's usability and conversion funnel.

  • Considering the magnitude of the drop, I'm wondering about potential technical issues. Have we noticed any increase in app crashes or error rates during the sign-up process?

Why it matters: Technical problems can significantly impact user acquisition. Expected answer: Our error logs show a 15% increase in sign-up related errors. Impact on approach: This would shift our focus towards technical troubleshooting.

  • Given the specificity of new rider sign-ups, I'm curious about our user segments. Has this drop been consistent across all user demographics and acquisition channels?

Why it matters: Segmentation helps identify if the issue is global or specific to certain groups. Expected answer: The drop is more pronounced in the 18-25 age group and social media channels. Impact on approach: We'd investigate factors specific to this demographic and these channels.

  • Considering potential external factors, have there been any significant competitor actions or market changes in the past week?

Why it matters: External factors can sometimes explain sudden metric changes. Expected answer: No major competitor actions, but there's been increased media coverage on ride-sharing safety. Impact on approach: We'd explore how safety perceptions might be impacting sign-ups.

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