Why has John Lewis's click-and-collect service seen a 15% drop in usage over the past month?

Introduction

John Lewis's click-and-collect service has experienced a 15% drop in usage over the past month, raising concerns about customer satisfaction and potential revenue loss. To address this issue, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both immediate and long-term implications for the business.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be seasonal factors at play. Has this 15% drop been compared to the same period last year?

Why it matters: Seasonal trends could explain the decrease and impact our solution approach. Expected answer: Yes, it's been compared and is still significant. Impact on approach: If seasonal, we'd focus on optimizing for known patterns; if not, we'd investigate other factors.

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

Why it matters: Identifying specific affected segments could point to targeted issues. Expected answer: The drop is more pronounced among occasional users. Impact on approach: We'd focus on understanding and addressing the needs of occasional users.

• Thinking about recent changes, have there been any updates to the click-and-collect process or related systems in the past 1-2 months?

Why it matters: Recent changes could directly correlate with the usage drop. Expected answer: A new inventory management system was implemented. Impact on approach: We'd investigate how this system change might have affected the service.

• Regarding performance metrics, has there been any change in how we're measuring click-and-collect usage or in the systems tracking this data?

Why it matters: Ensures we're comparing apples to apples and not facing a data anomaly. Expected answer: No changes in measurement or tracking systems. Impact on approach: Confirms the issue is with actual usage, not data collection.