Why has customer retention for Extra (Financial Services)'s personal loan product declined from 85% to 70% in the last quarter?

Introduction

The decline in customer retention for Extra's personal loan product from 85% to 70% in the last quarter is a critical issue that demands immediate attention. This significant drop could have far-reaching implications for the company's financial health and market position. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent product change. Have there been any significant updates to the personal loan product in the last 3-6 months?

Why it matters: Product changes can directly impact user experience and retention. Expected answer: Yes, there was a recent update to the loan application process. Impact on approach: If confirmed, we'd focus on analyzing the specific changes and their effects.

• Considering the competitive landscape, I'm curious about market dynamics. Has there been any notable shift in competitor offerings or marketing strategies recently?

Why it matters: External market forces can significantly influence customer behavior. Expected answer: A major competitor launched a lower interest rate product. Impact on approach: We'd need to assess our product's competitiveness and value proposition.

• Thinking about user segments, I'm wondering if the retention drop is uniform across all customer groups. Do we have data on which customer segments are most affected?

Why it matters: Identifying specific affected segments can help pinpoint the issue. Expected answer: The decline is more pronounced in the 25-35 age group. Impact on approach: We'd focus on understanding the needs and behaviors of this particular segment.

• Considering potential data anomalies, I'm curious about our measurement systems. Has there been any change in how we calculate or track retention rates?

Why it matters: Ensures we're dealing with a real issue and not a measurement error. Expected answer: No changes in measurement systems or definitions. Impact on approach: We'd proceed with confidence in the data's accuracy.