Why has Internet Brands's WebMD Symptom Checker seen a 15% drop in daily active users over the past month?

Introduction

The recent 15% drop in daily active users for WebMD's Symptom Checker is a concerning trend that requires immediate attention. As we analyze this issue, we'll follow a systematic approach to identify, validate, and address the root cause while considering both short-term and long-term implications for the product and its users.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be seasonal factors at play. Has this 15% drop been consistent across all user segments, or are certain demographics more affected?

Why it matters: Understanding the distribution of the drop helps focus our investigation. Expected answer: The drop is more pronounced among younger users. Impact on approach: If confirmed, we'd prioritize hypotheses related to younger users' behavior or preferences.

• Considering recent product updates, I'm curious if any changes were made to the Symptom Checker in the past 1-2 months. Have there been any significant feature updates or UI changes during this period?

Why it matters: Recent changes could directly impact user engagement. Expected answer: A new UI was rolled out 6 weeks ago. Impact on approach: If confirmed, we'd focus on usability issues and user feedback related to the new interface.

• Given the nature of health-related searches, I'm wondering if there have been any changes in search engine algorithms or health information policies. Have you noticed any shifts in organic traffic or referrals from major search engines?

Why it matters: External factors could be driving users away before they even reach the Symptom Checker. Expected answer: No significant changes in search traffic have been observed. Impact on approach: If confirmed, we'd focus more on internal factors and user behavior within the WebMD ecosystem.

• Thinking about potential technical issues, I'm concerned about the reliability of our data collection. Can you confirm that there haven't been any changes to our analytics setup or data processing methods in the past month?

Why it matters: Ensures we're working with accurate data and not chasing a phantom problem. Expected answer: No changes to analytics or data processing have been made. Impact on approach: If confirmed, we can confidently proceed with analyzing user behavior and product performance.