Why has Policygenius's term life insurance quote engine seen a 30% drop in completed applications over the past month?

Introduction

The recent 30% drop in completed applications for Policygenius's term life insurance quote engine is a significant issue that requires immediate attention. 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 there might be a seasonal component. Has this drop coincided with any particular time of year or event?

Why it matters: Seasonal trends could explain the fluctuation and inform our solution approach. Expected answer: No significant seasonal correlation. Impact on approach: If seasonal, we'd focus on adapting to cyclical patterns; if not, we'd investigate other factors.

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

Why it matters: Identifying specific affected segments could point to targeted issues or changes in market dynamics. Expected answer: The drop is relatively uniform across segments. Impact on approach: If uniform, we'd look at system-wide issues; if segmented, we'd focus on specific user group needs.

• Thinking about recent changes, have there been any updates to the quote engine or related systems in the past 1-2 months?

Why it matters: Recent changes could directly correlate with the performance drop. Expected answer: Minor UI updates were implemented. Impact on approach: If changes occurred, we'd scrutinize their impact; if not, we'd look at external factors or gradual shifts in user behavior.

• Considering data integrity, has there been any change in how completed applications are tracked or defined?

Why it matters: Ensures we're comparing apples to apples and not dealing with a measurement issue. Expected answer: No changes in tracking or definitions. Impact on approach: If changed, we'd recalibrate our metrics; if not, we'd focus on actual performance issues.