Improve customer retention.
Your data combined with the latest machine learning technologies can help you predict which of your customers are most likely to churn in the future.
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Your data combined with the latest machine learning technologies can help you predict which of your customers are most likely to churn in the future.
Satisfied customers are the foundation of most businesses. Returning customers guarantee cash flow and are more likely to make up-sell. It has been proven many times over that it is up to 7 times more expensive to acquire new customers than it is to retain existing ones.
With customer churn analysis, you can determine which customers are most likely to churn based on their behavior by comparing their behavior with the behavior of previous customers who have churned
A customer churn analysis can reveal how likely each of your customers is to churn in a given time period.
When you combine a customer churn analysis with a customer lifetime value analysis, you can focus specifically on retaining your most valuable customers. With a customer churn analysis from Borbaki, you can retain your most valuable customers and increase their lifetime value.
Our data scientist will create a costumer churn model algorithm suitable for analysing your data.
The model predicts how likely each of your customers is to churn. Using performance metrics over a specified test period, we can determine how accurately the churn model can predict which customers are most likely to churn.
Each of your customers is assigned a retention value score.
This value score is calculated based on the likelihood of churn and the economic value of the customer to your business.
With a retention score, you can focus on retaining the customers that generate the most value for your business, and not just the customers who are most likely to churn
Customer churn analysis is not worth a dime if the results are not understandable or actionable. Therefore, global and local effects can be analyzed based on the churn analysis.
Global effects are the consideration of overall trends from the churn model. This could mean that customers who do not receive newsletters or live in a certain area are most likely to churn.
Local effects show you how each churn driver affects your individual customers. You’ll learn which drivers there are most important to each customer and how much of an impact those drivers have on each customer.
Once the analysis is complete and we have identified the factors that lead to the most churn, it’s time to take action to retain customers. We divide your customers into groups based on their retention rate and likelihood to churn.
A “one size fits all” strategy is usually not enough. Based on the results of local and global impact, you can develop individual churn strategies to increase your customer retention rate.
Total potential identified by our team
Do you have a question that you really want an answer to, but it does not fit into one of our analyses.
Just contact us and we will create an analysis tailored to your needs.
Read about data science here.
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