Customer Churn Prediction
Customer Churn Prediction
Churn represents the quantification of customers who are very likely to cancel a subscription or stop paying for services. Artificial intelligence is helping to detect such customers by leveraging customer historical transactional, geographic, and other data. Company can then re-engage before it is too late and the customer already decided to move to a competitor. Advance knowledge about customers at high risk of churn can help to prevent such situations.
Did you know that:
- New customer acquisition costs five times more than retaining an existing customer?
- Customer retention increase by 5% can increase profits for more than 40%?
Use Case: Enhancing Customer Retention in Call Centre Environments
In this scenario our algorithm predicts what the potential customer might do next. Options could include cancelling a service or ordering a new service.
Predicting: Once our algorithm has identified the customers possible actions it predicts the highest probability for the action the customer will take next and aligns this with the defines set of rules for what should then happen. For example, if the algorithm predicts the customer might cancel a service it will put in place the options available that would help to retain the customer.
Resolving: Call centre staff would be able to see the real-time prediction and be ready to respond accordingly with a range of potential activities which would help to retain the customer. The same activity can also be translated to digital communications, allowing the firm to contact a client digitally with the same customer retention strategy.
Results: Compared to predicted customer churn, our solution increased customer retention by 1.5%. For a large business this could represent thousands of individuals.
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About iERP
iERP’s mission is to provide an end-to-end business prediction platform with modules that address multiple business scenarios and ZERO required knowledge of artificial intelligence or machine learning technologies.
We are helping companies to predict sales and inventory demands, what their customers are going to purchase next, or identify customers that are going to be late with the payment.