Customers who will leave show signs. A six-hour Monday churn prediction model identifies them before they go.
A IPTV reseller in Sweden spends six hours every Monday building his churn prediction model.
He identifies predictors: no stream in 10+ days, support tickets in last 7 days, payment method expired, and tenure less than 90 days. He weights each predictor.
His Panel IPTV data feeds the model. He calculates a churn score for every customer daily.
A Revendeur IPTV who never predicts churn finds out customers are leaving when they're already gone. He reacts. He doesn't prevent.
Here's what the churn prediction model revealed. A reseller's model flagged a customer with high churn score. He messaged the customer. The customer had a technical issue he hadn't reported. The reseller fixed it. The customer stayed.
The practical implementation is simple. Block Monday 9 AM-3 PM. "Churn Prediction." Build your model. Calculate scores daily. Intervene with high-score customers.
What actually works is starting simple. "No stream in 10 days" alone predicts churn well. Start with that. Add more predictors over time.
I learned that churn is predictable. The Six Hour Monday Customer Churn Prediction predicts it.
Honestly, predict churn for your customers today. Your IPTV reseller retention will improve.