OTT Churn Machine Learning

Reducing OTT Churn & Machine Learning. Why you should try it?

Increasing OTT competition and slowing OTT market growth will make customer acquisition a more challenging, and expensive, proposition for OTT services.

As it becomes harder to win new customers, it becomes even more important to retain those customers you already have.

Customer churn is a growth decelerator and has a significant impact on your business profitability.

In this white paper we will explain how Artificial Intelligence algorithms allow video service providers to build and automatically run more accurate churn prediction models, which predict future churn based on past churn.


  • Introduction
  • Good reasons you should use machine learning to predict OTT churn
  • How to build a machine learning model to predict OTT churn
    • Historical OTT user churn data as input
    • Transform data and analyse data quality
    • Historical churn data prepares the system
    • Visualize user attributes: data distribution
    • Finetune the churn algorithm with customer data
    • Predict and cluster new OTT user churn

Reducing OTT Churn & Machine Learning. Why you should try it?

How is artificial intelligence impacting TV and video service providers?
Why Audience Clustering in Video Services is crucial for success?