What caused the sudden 50% decrease in lead submissions through Edmunds's "Get Your Price" feature last week?

Introduction

The sudden 50% decrease in lead submissions through Edmunds's "Get Your Price" feature last week 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 business.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and next steps.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking this could be related to a recent product change. Has there been any significant update to the "Get Your Price" feature in the past two weeks?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, there was a UI update. Impact on approach: If yes, I'd focus on the change's impact on user behavior.

• Considering the magnitude of the decrease, I'm wondering about potential technical issues. Have there been any reported errors or outages in our systems during this period?

Why it matters: Technical problems can cause drastic drops in user engagement. Expected answer: No major reported issues. Impact on approach: If no, I'd shift focus to user behavior or external factors.

• Given the specificity of the metric, I'm curious about our measurement accuracy. Has there been any change in how we track or define lead submissions recently?

Why it matters: Metric definition changes can create false alarms. Expected answer: No changes in metric definition. Impact on approach: If no, I'd rule out measurement issues and focus on actual user behavior changes.

• Thinking about user segments, I'm wondering if this decrease is uniform across all user groups. Do we see any particular demographic or geographic segment more affected than others?

Why it matters: Segmented impact could point to specific user issues or regional factors. Expected answer: The decrease is relatively uniform. Impact on approach: If uniform, I'd look at broader issues affecting all users; if not, I'd focus on segment-specific factors.