Skip to main content

Customer Churn Use Case

A guide to implementing Auto Insights for a customer churn use case, including data structure and sample questions.

Auto Insights can help marketing teams understand attrition and retention patterns, analyze customer behavior, and launch more targeted marketing campaigns.

This article covers:

  • Example insights from this use case.

  • Recommended data structure for this use case.

What Sort of Insights Can Auto Insights Help Me Uncover?

We've outlined some example questions that Auto Insights can help answer through a combination of its proactive insights, Search, and What caused this? analysis:

Understand Attrition and Retention Patterns
  • Churned customers by customer life stage

  • Customers by customer life stage and product

  • Churned customers by the contract term

Analyze Customer Behavior
  • Annualized charges by customer life stage and product

  • Annualized charges by family size

  • Number of customers by family size

Launch More Targeted Marketing Campaigns
  • Churned customers by customer tenure

  • Churned customers by customer life stage

  • Churned customers by customer life stage and product type

How Do I Structure My Data?
  • Auto Insights requires structured, transactional data, with at least 1 measure (e.g. Price) and 5 segments (e.g. customer demographics). In addition, we recommend at least 7 months of data (at monthly or daily granularity) so you can take full advantage of Auto Insights' Unexpected Changes feature.

  • Auto Insights can connect to databases and .csv files.

Example Data Structure

Please click on the picture to download a larger copy of the image.


Here are some of the typical segments we find in revenue data. A segment is a qualitative value, like names or categories:

  • Customer attributes: Customer name, gender, family size, customer life stage, customer status, etc.

  • Product attributes: Product/service purchased, payment method, contract term (if applicable), etc. 


A measure is a quantitative, numeric value. Some of the typical measures include price, bill amount, total charges, number of customers, etc.