What caused the sudden 30% decrease in daily active users for Times Internet's Gaana music streaming app last week?

Introduction

The sudden 30% decrease in daily active users for Times Internet's Gaana music streaming app last week is a critical issue that demands immediate attention and thorough analysis. As we delve into this problem, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term and long-term implications for the product and business.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a specific event or change that triggered this. Has there been any recent product update or feature release?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, a new UI was rolled out last week. Impact on approach: If true, we'd focus on the UI change as a primary hypothesis.

• Considering user segments, I'm wondering if this decrease is uniform across all user groups. Have you noticed any particular user segment more affected than others?

Why it matters: Helps identify if the issue is global or specific to certain users. Expected answer: The decrease is more pronounced among Android users. Impact on approach: We'd prioritize investigating Android-specific issues.

• Given the magnitude of the decrease, I'm curious about any external factors. Has there been any significant competitor activity or market changes recently?

Why it matters: External factors can sometimes explain sudden metric changes. Expected answer: A major competitor launched a promotional campaign last week. Impact on approach: We'd need to consider competitive pressure in our analysis.

• Thinking about data integrity, I want to confirm the reliability of our tracking. Have there been any changes to our analytics systems or data collection methods?

Why it matters: Ensures we're not chasing a phantom problem due to data issues. Expected answer: No changes to analytics systems have been made. Impact on approach: If true, we can focus on actual user behavior rather than data anomalies.