Why has Tiger Analytics's customer churn prediction model accuracy dropped by 15% over the past quarter?

Introduction

Tiger Analytics's customer churn prediction model accuracy has dropped by 15% over the past quarter, indicating a significant decline in the model's performance. This issue could have far-reaching implications for the company's ability to retain customers and maintain its competitive edge. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been recent changes to the model or data pipeline. Have there been any updates to the prediction model or data sources in the last quarter?

Why it matters: Changes in the model or data sources could directly impact accuracy. Expected answer: Yes, there were some updates to the data pipeline. Impact on approach: If confirmed, we'd focus on investigating those specific changes.

• Considering the scale of the drop, I'm wondering about data quality. Have you noticed any significant changes in the quality or quantity of input data for the model?

Why it matters: Data quality issues could lead to inaccurate predictions. Expected answer: There have been some inconsistencies in data collection. Impact on approach: We'd prioritize data quality assessment and improvement.

• Given the nature of churn prediction, I'm curious about customer behavior changes. Has there been any notable shift in customer engagement or usage patterns recently?

Why it matters: Changes in customer behavior could make the existing model less effective. Expected answer: Yes, we've seen some changes in customer engagement. Impact on approach: We'd focus on updating the model to reflect new behavior patterns.

• Thinking about the broader context, I'm wondering about market conditions. Have there been any significant changes in the competitive landscape or market dynamics?

Why it matters: External factors could influence customer churn patterns. Expected answer: There have been some new entrants in the market. Impact on approach: We'd consider incorporating market data into the model.