The client is a large US based telecommunication company that provides mobile, voice and internet services through a nationwide network. The main challenge for them was to predict the customer churn as they were unable to retain customer for long periods which resulted in lower profits. The company was not able to identify these customers in advance and as a result they were spending a lot of finds for new customer acquisition. The aim of this project was to build a predictive AI churn model based on several factors like gender, tenure, internet service, tech support, contract, payment method etc. After a detailed evaluation of their operation data, AI Labs used its proprietary Minsky AI Engine to build an optimized model using a combination of AI algorithms and prediction attributes. Based on this historical AI model, current customer data was used to predict churn for each customer. This solution was optimized and implemented in less than a week.
Typical Customer-churn Challenges:
Acquiring new customer always costs heavily to the company
Has a significant impact on the business as it lowers revenues and profits
Difficult to implement a customer loyalty program with constant customer churn.
Keeping customers informed about new offerings