What caused the sudden 30% decrease in GoHealth's prescription drug plan quote requests over the past month?

Introduction

The sudden 30% decrease in GoHealth's prescription drug plan quote requests over the past month 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 solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal component. Has this 30% decrease been compared to the same period last year?

Why it matters: Seasonal trends could explain the decrease and impact our solution approach. Expected answer: Yes, it has been compared, and this decrease is unusual for this time of year. Impact on approach: If seasonal, we'd focus on why this year is different; if not, we'd look at recent changes.

• Considering user segments, I'm curious about the distribution of this decrease. Is the 30% drop uniform across all user segments or concentrated in specific groups?

Why it matters: Identifying affected segments could point to specific issues or changes impacting certain users. Expected answer: The decrease is more pronounced in the 65+ age group. Impact on approach: We'd focus on investigating factors specifically affecting older users.

• Thinking about recent changes, have there been any significant updates to the quote request process or the plans offered in the last 1-2 months?

Why it matters: Recent changes could directly correlate with the decrease in quote requests. Expected answer: A new UI for the quote request form was implemented 6 weeks ago. Impact on approach: We'd prioritize analyzing the impact of this UI change on user behavior.

• Considering data integrity, has there been any change in how quote requests are tracked or measured in the past month?

Why it matters: Ensures we're not dealing with a data anomaly rather than an actual decrease. Expected answer: No changes in tracking or measurement methods. Impact on approach: We'd focus on actual user behavior changes rather than data discrepancies.