Why has the number of active users for Aurora's AI chatbot decreased by 15% over the past month?

Introduction

The 15% decrease in active users for Aurora's AI chatbot over the past month is a significant issue that requires immediate attention. As we dive into this product root cause analysis, we'll systematically examine potential factors contributing to this decline, generate data-driven hypotheses, and develop a comprehensive plan to address the problem.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal component. Has this decline coincided with any particular events or time of year?

Why it matters: Seasonal trends can significantly impact user behavior. Expected answer: No significant seasonal events noted. Impact on approach: If seasonal, we'd focus on cyclical patterns; if not, we'll investigate other factors.

• Considering user segments, I'm curious about the distribution of the decline. Is the 15% decrease uniform across all user groups, or are certain segments more affected?

Why it matters: Identifying affected segments helps pinpoint specific issues. Expected answer: The decline is more pronounced in casual users. Impact on approach: We'd focus on casual user experience and engagement strategies.

• Thinking about recent changes, have there been any significant updates to the chatbot's functionality or user interface in the past month?

Why it matters: Recent changes often correlate with shifts in user behavior. Expected answer: A minor UI update was implemented three weeks ago. Impact on approach: We'd investigate the impact of this update on user experience.

• Regarding performance metrics, has there been any change in how we measure active users or in the systems tracking this data?

Why it matters: Ensures we're comparing apples to apples in our metrics. Expected answer: No changes in measurement or tracking systems. Impact on approach: Confirms the decline is real, not a measurement artifact.