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Do you want to keep your most valuable customers?

twoday kapacity’s Customer Churn & Retention Framework uses your data combined with the latest technology in machine learning to predict which customers are most likely to leave you.

Based on the insights of the churn model, we come up with concrete suggestions on how you should act to keep your most valuable customers. All the while the model is continuously retrained and optimized to predict what works in the pursuit of keeping customers.

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Why should you focus on Churn & Retention?

Satisfied customers are the foundation of most companies. They generate a steady stream of earnings and are more open to additional sales. Studies have repeatedly shown that it is significantly more expensive to acquire a new customer than to retain an existing one.

With churn prediction, you have the opportunity to spot customers who are at high risk of leaving the business. Specifically, a churn model can predict the probability of a customer churn within a specific period of time. Coupled with a customer lifetime value calculation, you can also see which customers are most valuable to the business.

With twoday kapacity's Churn & Retention Framework, we do not just spot churn – we act on that basis. With our retention actions, you get a powerful tool that allows you to retain the right customers.

Based on insights from the machine learning model, business hypotheses, domain experts and customer valuation via CLV, actions are designed that will be taken into use by the business.

These actions are measured and tested in a continuous feedback flow, which continuously improves the model, insights, actions and the business.

What will you get with twoday kapacity's customer churn & retention framework?

Churn model

The Churn model uses machine learning and your data to predict how likely it is that each customer will leave the business. Using performance metrics and a test period, we can measure how accurately the churn model can predict which customers will churn. If you want to know more about what data the churn model can use, you can read this blog post.

Retention Value (RV)

Retention Value is an overall score that is calculated based on the customer’s probability of churning compared to the customer’s value for the business. It is not necessarily the best solution to try and retrain the customers most likely to leave you if they are not valuable to the business – Retention Value takes this into account.

Understand Customer Churn

Based on our churn model, we can analyze global and local effects. Global effects look at the overall trends from the churn model. It can e.g. be that customers who do not receive newsletters – or a particular age group – have a particularly high risk of churning. From the local effects, you can see how each churn driver affects each customer, what the most important drivers are for the particular customer you are looking at or interacting with and how much influence the specific driver has.

Retention actions

Retention Value is an overall score that is calculated based on the customer’s probability of churning compared to the customer’s value for the business. It is not necessarily the best solution to try and retrain the customers most likely to leave you if they are not valuable to the business – Retention Value takes this into account.

Download our White Paper: 'Spot churn and retain the right customers with data and Marketing Science'

In the White Paper you get:

  • 34 pages packed with the latest knowledge in Customer Churn – and what you can do to avoid it – written by our expert in the field.
  • A detailed insight into how Machine Learning can easily provide insight into what drives the churn, each customer’s value to your business, and the likelihood that he/she will churn.
  • A thorough review of what to do to prevent churn – we give you answers on how to get started, who to go for and what methods to use.
Yes please, send me the white paper
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Case: Aarstiderne get a unique insight into customer loyalty with customer analyzes

Aarstiderne has carried out a strategic customer loyalty project entitled “the best customer experience each time”. The objective was to give more structure to the customer loyalty work. But what did it take to achieve this goal?

Aarstiderne chose, among other things, to focus on better customer analyzes and started a dialogue with twoday kapacity about Customer Churn & Retention. The goal was to gain better insight into which customers were most likely to churn.

The model used by Aarstiderne looks at more than 300 variables. This ensures a high degree of accuracy of the customer analyzes that the model delivers.

Read the case
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Knowledge about Customer Churn & Retention

Churn prediction in financial companies: How to get started

 

 

Satisfied customers are the foundation of most businesses. They generate a steady stream of income and are more open to upselling. At the same time, studies show that it costs five times as much to acquire a new customer as it does to retain an existing one. Therefore, it is important to focus on ho...

How to get from Customer Churn to Customer Retention

 

Your customer data can tell you a lot about which of your customers might be about to leave you but how much does it actually take? What specific information do you need in order to make a prediction of Customer Churn?

Would you like to understand your customer base better and be able to look into the future?

 

Quickly learn which of your customers will leave your business first.

Do you want to get started? So do we

Do as a large number of the country’s most ambitious companies:
Fill out the form or get in touch with Søren – then we can have a chat about your challenges and dreams.

Søren Toft Joensen

Partner & CCO
stj@kapacity.dk
26 30 90 01