Why has Glassdoor's company review submission rate dropped 30% over the past month?

Introduction

The sudden 30% drop in Glassdoor's company review submission rate over the past month is a critical issue that demands immediate attention. This significant decline could have far-reaching implications for Glassdoor's core value proposition and user engagement. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal factor at play. Has this drop coincided with any particular time of year or event?

Why it matters: Seasonal trends could explain the sudden drop and inform our solution approach. Expected answer: No significant seasonal correlation. Impact on approach: If seasonal, we'd focus on annual patterns; if not, we'd investigate recent changes.

• Considering user segments, I'm curious if this drop is uniform across all user types. Have you noticed any differences in submission rates between job seekers, current employees, and former employees?

Why it matters: Identifying affected segments helps pinpoint potential causes and tailor solutions. Expected answer: The drop is more pronounced among current employees. Impact on approach: We'd focus on factors affecting current employees' willingness to submit reviews.

• Thinking about recent changes, has there been any modification to the review submission process or UI in the last 1-2 months?

Why it matters: Recent changes could directly impact user behavior and submission rates. Expected answer: A minor UI update was implemented 6 weeks ago. Impact on approach: We'd investigate the impact of this UI change on user experience and submission flow.

• Considering data integrity, I'm wondering if there have been any changes to how we measure or define a "submitted review" in our analytics?

Why it matters: Ensures we're comparing apples to apples and not facing a data anomaly. Expected answer: No changes to measurement or definition. Impact on approach: If changed, we'd recalibrate our analysis; if not, we'd focus on external factors.