Antichurn models
Talk to an expert
Talk to an expert
Request
Predict the churn probability of each customer based solely on their browsing behavior outside the client’s website (wherever its banners are), without any socio-demographic or contract information. No distinction is made between recent and distant browsing behavior in this initial phase.
Approach
Implement a machine learning system enriched with sophisticated user profiling tailored to meet specific needs.
Result
A server-side solution that takes user profiles as input and, through data enrichment processes, returns churn probability and other KPIs. The last quantile shows a churn likelihood up to 400% higher than the first, confirming the model's ability to successfully differentiate high-risk customers.
Categories
Type
AI & Data Science
Need
Benefit
Business function
Industry
Telco, Media & Entertainment, Utilities, Publishers, Finance, Software, Logistics, Associations, Goods Production & Distribution, Retail Distribution
Business Model
Business Size

