Key takeaways
- Churn prediction scores every wireless and broadband subscriber for risk of leaving, with reason codes that show what is driving each score.
- Churn risk combined with expected lifetime value tells you which subscribers are worth a retention offer and which need a network fix or a care callback instead.
- H2O Feature Store keeps the features your churn and offer models share, so training and scoring use the same definitions.
- The models run in four deployment options: on-premises, air-gapped, private cloud, and cloud, so subscriber data stays in your environment.
A churn list nobody acts on
You probably have a churn model already. It produces a list each month, and the list goes to a team that cannot call everyone on it. The subscribers who leave are often the ones who were flagged, and the ones who stay were sometimes given a discount they did not need.
Churn in telecom has many causes: a contract ending, a competitor's device offer, repeated dropped calls, a billing dispute that went badly. A score without a reason leaves your team guessing which action to take, so every at-risk subscriber gets the same offer.