How can we explain the sudden 25% drop in daily active users for Starburst's SQL workbench tool compared to last week?

Introduction

The sudden 25% drop in daily active users for Starburst's SQL workbench tool is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for the product and its users.

To tackle this problem, I'll follow a structured approach that covers issue identification, hypothesis generation, validation, and solution development. My goal is to uncover the underlying reasons for this significant user decline and propose actionable steps to rectify the situation.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a recent product change. Has there been any significant update or feature release in the past week?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, a new version was released last week. Impact on approach: If true, I'd focus on analyzing the changes in that release.

• Considering user segments, I'm curious about the distribution of the drop. Is the 25% decrease uniform across all user types, or is it more pronounced in specific segments?

Why it matters: Helps identify if the issue is global or segment-specific. Expected answer: The drop is more significant among power users. Impact on approach: I'd investigate factors specifically affecting power users.

• Thinking about external factors, have there been any major industry events or competitor actions that could influence our user base?

Why it matters: External events can sometimes explain sudden metric changes. Expected answer: No significant external events noted. Impact on approach: I'd focus more on internal factors if external influences are ruled out.

• Regarding data integrity, I'm wondering about our tracking systems. Have there been any changes to how we measure or define daily active users recently?

Why it matters: Ensures the observed drop is real and not a measurement artifact. Expected answer: No changes to measurement systems or definitions. Impact on approach: If confirmed, I'd proceed with analyzing actual usage patterns.