What caused the sudden 30% decrease in new user sign-ups on the Glovo app last week?

Introduction

A sudden 30% decrease in new user sign-ups on the Glovo app last week is a critical issue that demands immediate attention. This significant drop in a key performance indicator could have far-reaching implications for user acquisition, growth, and overall business health. 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.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this could be related to a recent app update. Has there been any significant changes or updates to the Glovo app in the past two weeks?

Why it matters: Recent changes could directly impact user experience and sign-up flow. Expected answer: Yes, there was an update to the sign-up process. Impact on approach: If confirmed, we'd focus on analyzing the changes made in the update.

• Considering user segments, I'm wondering if this decrease is uniform across all user groups. Are we seeing this 30% drop consistently across different demographics or regions?

Why it matters: Helps identify if the issue is global or specific to certain user segments. Expected answer: The decrease varies across regions, with some more affected than others. Impact on approach: We'd prioritize investigating the most affected segments first.

• Given the sudden nature of the drop, I'm curious about any external factors. Have there been any significant competitor actions or market changes in the past week?

Why it matters: External factors could explain the drop and require different solutions. Expected answer: No major competitor actions, but there's been some negative press coverage. Impact on approach: We'd need to factor in potential PR issues in our analysis.

• Thinking about data integrity, I want to confirm our measurement systems. Has there been any change in how we track or define new user sign-ups recently?

Why it matters: Ensures we're dealing with a real issue and not a data anomaly. Expected answer: No changes to tracking systems or definitions. Impact on approach: We can proceed with confidence in our data accuracy.