Why has the average deposit amount for Stash's Auto-Stash recurring investment feature declined by 20% this quarter compared to last?

Introduction

The decline in average deposit amount for Stash's Auto-Stash recurring investment feature by 20% this quarter is a significant issue that requires thorough investigation. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both immediate and long-term implications for the product and business.

Step 1

Clarifying Questions (3 minutes)

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

Why it matters: Seasonal trends could explain temporary fluctuations in deposit amounts. Expected answer: No significant seasonal correlation identified. Impact on approach: If seasonal, we'd focus on cyclical patterns; if not, we'd investigate other factors.

• Considering user segments, I'm curious about the distribution of this decline. Is the 20% decrease uniform across all user groups, or are certain segments more affected?

Why it matters: Identifying specific affected segments could pinpoint the root cause more accurately. Expected answer: The decline is more pronounced in newer users. Impact on approach: We'd focus on onboarding and early user experience if newer users are more affected.

• Thinking about recent changes, have there been any updates to the Auto-Stash feature or related systems in the past quarter?

Why it matters: Recent changes could directly impact user behavior and deposit amounts. Expected answer: A minor UI update was implemented two months ago. Impact on approach: We'd investigate the impact of the UI change on user engagement and deposit behavior.

• Regarding metric definition, has there been any change in how we calculate or track the average deposit amount?

Why it matters: Ensures we're comparing apples to apples and not facing a data anomaly. Expected answer: No changes in metric definition or tracking. Impact on approach: If changed, we'd need to recalibrate our analysis; if not, we can proceed with current data.