Auto Insights can help marketing teams understand attrition and retention patterns, analyse customer behaviour, and launch more targeted marketing campaigns. You can read more here on our website.

This article will cover:

  • 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 which Auto Insights can help answer through a combination of her 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 contract term

Analyse customer behaviour

  • Annualised charges by customer life stage and product

  • Annualised 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

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Please refer to this article for more information about data structure.


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.

Related material
Customer churn use case
What type of data can be used in Auto Insights?
Options for ingesting data into Auto Insights
Quick guide to Auto Insights

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