Why has the average time spent on Payscale's Career Path Explorer feature declined from 5 minutes to 2 minutes per session in the past two weeks?

Introduction

The recent decline in average time spent on Payscale's Career Path Explorer from 5 minutes to 2 minutes per session over the past two weeks is a concerning trend that requires immediate attention. This analysis will systematically identify potential root causes, validate hypotheses, and propose solutions to address this issue while considering both short-term fixes and long-term implications for the product.

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 Career Path Explorer feature in the last month?

Why it matters: Recent changes could directly impact user behavior. Expected answer: Yes, there was a UI refresh two weeks ago. Impact on approach: If confirmed, we'd focus on the UI changes as a primary factor.

• Given the specific metric, I'm curious about user engagement patterns. Are we seeing a change in the number of career paths explored per session, or just in the time spent?

Why it matters: This helps distinguish between efficiency improvements and potential usability issues. Expected answer: The number of paths explored has remained constant. Impact on approach: If true, we'd investigate whether the reduced time is positive (increased efficiency) or negative (less engagement).

• Considering user segments, I'm wondering if this change is uniform across all user types. Have we seen any differences in time spent between new and returning users?

Why it matters: Different user behaviors could indicate separate issues for each group. Expected answer: The decline is more pronounced among returning users. Impact on approach: We'd focus on understanding why returning users are spending less time and if their needs are being met more quickly or if they're encountering friction.

• Thinking about data integrity, I want to confirm our measurement methods. Has there been any change in how we track or calculate time spent on the feature?

Why it matters: Ensures we're addressing a real issue and not a data anomaly. Expected answer: No changes in tracking or calculation methods. Impact on approach: If confirmed, we can rule out measurement issues and focus on actual user behavior changes.