Churn Prediction

Predicting churn helps businesses anticipate customers at-risk of leaving. We leverage your data to build a machine learning model that analyses customer experience and provides actionable insights for reducing customer churn.

The Challenge

Every business has its own definition of churn. Whether you sell subscriptions or you’re an FMCG company, customers leave.

As an increasing number of customers are not opting in to marketing communications, you need a way to talk to customers before it's too late. It's important to know whether their current interaction is likely to be their last visit to your site or the last order they place.

The Solution

Predicting churn allows you to intervene in a customer’s experience and interact with them in a way that convinces them to stay. With our bespoke customer churn prediction solutions, you can be one step ahead of the game.

The model finds the key variables that indicate a customer is about to stop using your product or service and uses these to generate a personalised risk score.

High scores are flagged along with an automatically generated explanation of why the user has been flagged as 'at-risk', allowing you to take action before the customer leaves your service.

Deliverables

01

The data transformation scripts that automatically transform and collate customer data from all your relevant sources and prepares the data in the required format for the churn predictor.

02

A machine learning model that predicts which customers will no longer be with you in the near future, unless preventative action is taken. The model is fully transparent and outputs a report - through either our custom dashboarding or your existing reporting tools -highlighting the reasons why high risk scores were given.

03

As part of the model build process, we develop a deep understanding of your data and customer base. This is presented back to you as a whitepaper that recommends long-term strategies and initiatives that would help alleviate customer churn.

The Outcome

By using the model to identify at-risk customers early, a proportion of your churn can be averted by taking preventative action, thus increasing long term revenue.