Banking and Finance, Fintech, Insights, Insurance, Retail and Consumer Goods, Use Cases

Retaining current paying customers is more valuable to the growth of the business than trying to acquire new ones. Being able to predict and prevent customers who are at higher risk of churning on time, represents a huge potential revenue source for any business. Furthermore, when losing a paying customer, a business doesn’t only lose a direct source of revenue but also the investment of customer acquisition.

To make sure that they’re successful at retaining these customers, marketing experts need to be able to predict well in advance the likelihood of churn on each customer, and what marketing initiatives are most effective on retaining that customer.​

Typical churn prediction models are based on older data mining and statistical methods which, although they do provide some value, are mostly inaccurate and can only identify a limited percentage of customers at risk, leading to the business missing out on opportunities.

How can TurinTech help?

Having a highly accurate model that can predict on time the percentage of at-risk customers, as well as the most effective marketing actions that can be implemented to retain those customers, is extremely important. With TurinTech’s EvoML, customers can easily identify behaviour patterns of at-risk customers, and build highly accurate machine learning models at speed in a short period of time based on the interaction with the business environment. Users can also visualise their data before building a model so they can better understand their use case. Additionally, EvoML will provide a full picture of how the model was built and why it made the prediction it did helping you understand the model in depth.

  • Ensure high customer retention and improve ROI​.
  • Improve customer satisfaction by targeting the right customers with the right marketing efforts.
  • Learn about your customers preferences and expectations so you can take charge and reduce the reasons for churn.