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Company focus

eHealth

What caused the sudden 30% decrease in eHealth's prescription drug plan comparison tool usage over the past month?

Prepared by NextSprints

15 mins
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Data Analysis Problem-Solving Strategic Thinking Healthcare Insurance Digital Health User Engagement Data Analysis Product Metrics Root Cause Analysis Healthcare Tech
Product Management Root Cause Analysis Question: Investigating sudden decrease in eHealth prescription drug plan comparison tool usage

Introduction

The sudden 30% decrease in eHealth's prescription drug plan comparison tool usage 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.

To tackle this problem, I'll follow a structured approach that covers issue identification, hypothesis generation, validation, and solution development. My goal is to provide a comprehensive analysis that not only pinpoints the cause of the usage drop but also outlines a clear path forward to resolve the issue and prevent similar occurrences in the future.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might have been a recent product update. Has there been any significant change to the tool's functionality or user interface in the past 1-2 months?

Why it matters: Recent changes could directly impact user behavior and tool usage. Expected answer: Yes, there was a UI refresh about 6 weeks ago. Impact on approach: If confirmed, I'd focus on analyzing the impact of these changes on user experience and engagement.

  • Considering user segments, I'm curious about the distribution of the decrease. Is the 30% drop uniform across all user groups, or are certain segments more affected?

Why it matters: Identifying specific affected segments could point to targeted issues or user needs. Expected answer: The decrease is more pronounced among older users (65+). Impact on approach: This would lead me to investigate accessibility issues or changes that might disproportionately affect older users.

  • Given the nature of the tool, I'm wondering about seasonal patterns. How does the current usage compare to the same period last year?

Why it matters: Ruling out seasonal fluctuations is crucial for accurate problem identification. Expected answer: Usage is typically stable year-round, with a slight increase during open enrollment. Impact on approach: If confirmed, this would strengthen the case for an internal or recent external factor causing the decrease.

  • Thinking about the broader ecosystem, have there been any changes in the prescription drug plan market or regulations that might affect how users interact with comparison tools?

Why it matters: External market factors could significantly influence user behavior and tool relevance. Expected answer: No major market changes, but a new competitor launched a similar tool last month. Impact on approach: This would prompt investigation into competitive pressures and potential user migration.

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NextSprints

Updated Jan 22, 2025