Customer Churn Prediction in Retail

One of the most important business metrics is churn rate, which shows the number of customers who leave a supplier. Today, companies are starting to apply machine learning to predict which customers are likely to churn in the near future.

Now, big retail companies, banks, and mobile carriers are collecting gigabytes of log data about their customers. Once processed, this data can help companies predict which individuals from their total customer database are most likely to churn. Taking into account the fact that the cost of obtaining a new customer is five times higher than maintaining an existing customer, a churn-prediction analytic system can save a company millions of dollars. BitRefine group has developed significant expertise in the area of churn prediction. We offer solutions based on different methods that mostly depend on available datasets. Rich customer datasets show impressive accuracy in our latest churn prediction model.

A rich training dataset for a reliable prediction model contains:

• More than 50000 customers
• More than 100 variables
• More than 3% of total customer number are negative examples (churn customers)

Company executives understand what’s best for their own business. The role of our company is to build a powerful tool that will show which customers you need to be concerned with, and who is in danger of churning. Then, based on this data, marketers can decide how to take steps toward those customers before it is too late—by sending them a bonus or a gift card, for example.