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  • Helen defines the parameters of the churn report: Duration: 4 weeks, Publications: Publication 1 and publication 2, Geography: Belgium, Netherlands.
  • I'll run a churn analysis report
  • Helen, a marketing manager, wants to know which subscribers are likely to churn in the next 4 weeks.
  • Helen has run the report and finds that there are 80 customers who have 50% (or more) probability to churn in the next 4 weeks.
  • Helen filters the report to focus on the subscribers with 80% or more probability of churning in the next 4 weeks.
  • I want to focus on the subscribers with 80% probability or more to churn. Do they have any commonalities?
  • Success!
  • Helen looks at the report, and for each entry looks at the following parameters: Has the customer accessed the digital edition of the publication, when has the customer called the call center (and the details of the calls), the customer's first subscription date.
  • Let's see- what can I do to prevent these subscribers from stopping the subscription? What were the reasons that they may be churning?
  • Helen goes ahead and creates a campaign to provide 4 weeks of free subscription to compensate these subscribers for the delivery issues.
  • Helen then finds that many of the high probability churners have called the call center to complain about delivery issues.
  • The churn analytics report has provided the company the ability to predict churn and the insight to act to prevent it.
  • Answer 1
  • Answer 2
  • 4 weeks later, many of the high probability to churn subscribers have not cancelled the subscription and provided appreciation for the 4 free weeks of subscription.
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