use cases

Customer Churn

Predicting and preventing customer churn through machine learning

What Is Churn Prevention With AI ?

With our AI churn prediction expertise, we help companies to predict which customers will leave, for which reason, and to prioritize retention activities accordingly.

Why Prevent Churn With AI ?

It is 25 times more expensive to gain a new customer than to retain an existing one. Yet many companies only remark that a customer has left when it is too late.

What are the Business Benefits?

As a sales or marketing manager, you may have an idea of what are the drivers of churn. With AI based churn prediction, you can have a data driven assessment of: what are the drivers of churn, what is their relative importance, and what is their cost. Beyond understanding the reasons of churn at a very granular level, this enables you to take action in a data driven way.

Predict Which Customers Will Leave

What if you could predict which customers will leave? It may sound impossible to some of you, but this is a field of application of AI that works with a high level of certainty. As a marketing or customer service manager, it enables you to focus your actions on the high risk customers.

Focus On What Will Work

Within a few weeks, know exactly where you must focus your sales and marketing and customer service actions in order to have rapid ROI.In other words: aim at the right target instead of losing time testing actions.

A Case study on Churn Prediction

One of our latest projects is a churn prediction solution for a company active in the financial industry.


The company was faced with losing 25000 B2B customers per year. Some of the churners were identified, some of them were not identified because their contract was still running, even if they were not ordering. The reasons for churn were not known, and the company was not able to identify churners in advance. As a consequence, our client had no actionable way to prevent its customers from leaving.


Kantify developed an AI based solution in order to enable its client to identify what were the reasons for churn, what was the cost of churn from each variable (churn impacting event), and to predict the churn, client per client. This solution is based on internal client data and external data. One of the valuable elements from the solution is to capture and predict the impact of economic churn : when the economic situation of a client directly impacts its purchasing behaviour towards our client.

Thanks to its new churn prevention solution, our client is able to adapt its marketing, sales and customer service activities to not only predict, but also prevent its customers from leaving.


How much data is needed to build an AI solution
We explain different AI use cases and the amount of data each of these AI algorithms needs in order to be trained and work properly.Read More
Difference between Data Science, Machine Learning and Artificial Intelligence
We help in understanding the difference between DS, ML and AI and when to use each of themRead More
Data sources that can be used in Artificial Intelligence
We explain the different types of data and data sources companies can leverage to implement Artificial Intelligence and improve the decision making processRead More
2 ways Artificial Intelligence can save traditional asset management firms
Robo Advisers and digital-first fintechs are disrupting traditional asset management firms. AI might just save them.Read More
3 Problems that logistics and transport companies are solving through Artificial Intelligence
Transport and logistics companies are facing a host of challenges: here's how they have been using AI to solve these problems.Read More
Predicting Churn with Machine Learning
Predicting churn with Machine Learning: the essential steps in terms of data collection, machine learning techniques, and evaluation.Read More
Can AI Nudge Us to Make Better Choices?
Human behaviours are more predictable and sometimes influenceable that we would like to admit. AI can remove this factor and help us make better choices.Read More
Explainable AI Vs. Black Box AI- A Customer Retention Profitability Analysis
When considering strategic decision making, explainable AI is more popular than black box AI.Read More
Online ads can be targeted based on your emotions
The New York Times is now able to sell ads based on the emotion the reader will most likely feel while reading an article.Read More


The EU Focus Group on AI is launched
Kantify has been selected to be a member of this group of European AI experts who will give input into the EU policy on Artificial Intelligence.Read more
Kantify joins the European Commission / Digital SME Focus Group on Artificial Intelligence
Kantify is an official member of the Group that will monitor the progress of AI technology and regulations in EuropeRead more
Trophées Montaigne 2020 : Our CEO wins the Trophée ‘Enterprise'
Our CEO Ségolène Martin was awarded the Trophy Montaigne for the category ‘Enterprise'.Read more
Kantify selected as Belgian Digital Champion by the Belgian Association of Marketing
Our CEO, Segolene, presented our solution in hyperpersonalized marketing at the BAM event on Belgian Digital ChampionsRead more
Kantify explains hyperpersonalized marketing on Radio La Premiere
Our CEO, Segolene, was interviewed by RTBF - La Premiere, concerning hyperpersonalized marketing.Read more
Kantify algorithms make marketing intelligent
Our CEO, Segolene, has been interviewed by DataNews concerning the impact AI can have on marketing.Read more

Related Industries

Consumer Products
Machine learning and AI in Consumer ProductsDiscover
Financial Services
Machine learning and AI in financial servicesDiscover
Non Governmental Organizations
Machine Learning and AI for NGOsDiscover
Machine learning and AI in retailDiscover
Machine learning and AI in technologyDiscover

Related Business Functions

Increasing revenue through AIDiscover
Better management of cash, payments and investments through AIDiscover
Reaching existing and prospective customers through AIDiscover