What factors are contributing to the recent spike in early returns for Progressive Leasing's furniture leasing program?

Introduction

The recent spike in early returns for Progressive Leasing's furniture leasing program is a concerning trend that requires immediate attention. To address this issue, I'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term and long-term implications for the business.

My analysis will follow a structured framework, beginning with clarifying questions to establish context, followed by a thorough examination of external factors, product understanding, metric breakdown, data gathering, hypothesis formation, root cause analysis, and finally, validation and next steps.

Step 1

Clarifying Questions (3 minutes)

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

Why it matters: Seasonal trends could explain cyclical patterns in returns. Expected answer: The spike occurred outside of typical seasonal patterns. Impact on approach: If seasonal, we'd focus on anticipating and managing these cycles.

• Considering user segments, I'm curious if this is widespread or concentrated. Are we seeing this spike across all customer segments or is it more pronounced in specific groups?

Why it matters: Helps identify if the issue is systemic or segment-specific. Expected answer: The spike is more pronounced in newer customers. Impact on approach: If segment-specific, we'd tailor our solutions to those groups.

• Thinking about recent changes, have there been any significant updates to the leasing terms, user interface, or furniture selection process in the last few months?

Why it matters: Recent changes could directly impact user behavior and satisfaction. Expected answer: A new online leasing process was implemented two months ago. Impact on approach: If related to recent changes, we'd focus on optimizing those specific areas.

• Regarding performance metrics, has there been any change in how we're measuring or defining "early returns"?

Why it matters: Ensures we're comparing apples to apples in our data analysis. Expected answer: The definition and measurement of early returns have remained consistent. Impact on approach: If unchanged, we can confidently compare current data to historical trends.