Strengthen customer loyalty and anticipate more than 50% of future contract or policy terminations


  • Predict each churn
  • Identify why the customer(s) want to leave
  • Target potentially loyal members
  • Develop personalized approaches, individually-centered approaches, with a human touch

Predictive Scoring

Complementing the analysis of past terminations with our Open Data sources allows a day-by-day assessment of the level of versatility of each client or policy holder


We start by compiling the data you already have in flat files. The data are then pseudonymized (in strict compliance with GDPR guidelines), augmented thanks to Open Data sources for greater depth, and then processed by our AI algorithms. The dashboard presents the results in an easy-to-read, user-friendly and business-ready way, so they can be more intuitively  interpreted. Our business teams guide you throughout the construction & consolidation phase, before transferring the day-to-day management to you when you are fully independent. Over time, our analysts continue to accompany you to add new gauges or refine the granularity of the results.

DataChurn is both an operational marketing module and a global strategic marketing software solution.

DataChurn can meet your operational marketing needs, by offering insight into the churn risk and motivations for each customer or policy holder, and also by highlighting the most efficient communication channel for each customer as well as the commercial mechanism best suited to each individual customer. These scores provide you with valuable operational marketing information for efficient multi-channel campaigns, as well as key CRM input for your sales representatives.

In terms of strategic marketing, the analysis of the most-frequent churn reasons enables you to take a proactive approach to customer loyalty. In addition, our simulation features enable you to predict the consequences of strategic choices such as price changes or the number of customer interactions.

A happy customer tells five people,
an unhappy customer tells ten people!