What caused the sudden 30% increase in customer support tickets related to Flip's new filter feature?

Introduction

The sudden 30% increase in customer support tickets related to Flip's new filter feature is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term implications for our product strategy.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this might be related to a recent update. When was the filter feature launched or last updated?

Why it matters: Helps pinpoint potential causes tied to recent changes. Expected answer: Within the last week or two. Impact on approach: If recent, focus on new code or features; if not, investigate gradual degradation.

• Considering user segments, I'm curious about the distribution of these tickets. Are they coming from a specific user group or spread across all users?

Why it matters: Identifies whether the issue is universal or segment-specific. Expected answer: Concentrated in a particular user segment. Impact on approach: Target investigation on affected segment if specific, or broader system issues if widespread.

• Thinking about the nature of the complaints, are users reporting similar issues, or is there a wide variety of problems?

Why it matters: Helps determine if there's a single root cause or multiple factors at play. Expected answer: Majority reporting similar issues. Impact on approach: Focus on common denominator if similar, or investigate multiple potential causes if varied.

• Considering system performance, have there been any notable changes in server load or response times coinciding with this increase?

Why it matters: Could indicate backend issues affecting user experience. Expected answer: Some increase in server load observed. Impact on approach: Investigate backend scalability and performance if load increased, or focus more on frontend if not.