Customer Churn &
Retention
Why this use case matters
You work hard and spend valuable resources to acquire customers, losing them to factors that are in your control is simply unacceptable. ML not only can predict when a customer might leave but uncover why they left.
Techniques
Supervised Learning – classification, customer lifetime value
Algorithms
Support Vector Machine (SVM), Logistics Regression, Tree-Based Models (XGBOOST, LightGBM, Random Forest), Deep Neural Networks, Bayes Networks
Outcome
Predicting churn not only shaves dollars off the top & bottom line, but it provides any organization with valuable insights on their consumer, which if harnessed properly can inform new product & service decisions.
We utilized several ML
approaches to help this retail
energy company combat
customer churn.
Mosaic has compiled our industry expertise into a Machine Learning playbook for Utilities.
