10 Churn demographics and firmographics

 

This chapter covers

  • Creating a dataset that includes demographic or firmographic information
  • Converting date information to intervals and analyzing the relationship to churn
  • Analyzing text categories for the relationship to churn
  • Forecasting churn probability with demographic or firmographic information
  • Segmenting customers with demographic or firmographic information

You now know all about using customer behavior data to segment your customers for the purpose of creating interventions to increase engagement. These strategies are the most important ones for increasing customer engagement and retention, which is why they are the focus of the book. But one other way to reduce your customer churn is not about intervening with your existing customers: find new customers who are more likely to be engaged to begin with. Identify facts about customers who tend to be more engaged, and then focus your customer acquisition efforts on finding more customers like them. Such facts are generally known as demographic data (data about individuals) and firmographic data (data about companies). For the purpose of this discussion, I use the following definitions.

DEFINITION

Demographics are facts about individual customers, and firmographics are facts about customers that are companies (firms).

10.1 Demographic and firmographic datasets

 
 
 
 

10.1.1 Types of demographic and firmographic data

 
 
 
 

10.1.2 Account data model for the social network simulation

 
 
 

10.1.3 Demographic dataset SQL

 
 

10.2 Churn cohorts with demographic and firmographic categories

 
 
 
 

10.2.1 Churn rate cohorts for demographic categories

 
 

10.2.2 Churn rate confidence intervals

 
 

10.2.3 Comparing demographic cohorts with confidence intervals

 
 

10.3 Grouping demographic categories

 

10.3.1 Representing groups with a mapping dictionary

 
 

10.3.2 Cohort analysis with grouped categories

 
 

10.3.3 Designing category groups

 
 
 

10.4 Churn analysis for date- and numeric-based demographics

 
 

10.5 Churn forecasting with demographic data

 

10.5.1 Converting text fields to dummy variables

 

10.5.2 Forecasting churn with categorical dummy variables alone

 

10.5.3 Combining dummy variables with numeric data

 
 
 
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