Domain: Data Science
Client: Telecom sector in the Netherlands
Subject: Predicting customer churn
A Dutch-based provider of telecommunications and information technology services has a high percentage of customers cancelling their subscription on monthly basis.
Customer retention is one of the important elements for growth, especially in subscription-based services. In general, it can cost five times more to attract new customers than to retain existing customers. So, churn is an important KPI for businesses with customers as subscribers with recurring payments which makes churn rate important to measure and act accordingly.
The main goals of the project was to decrease the churn rate using all the data available about the customers and their history.
We set up a pilot to identify customers ‘at-risk’ to churn using predictive modelling and launched an email campaign to these customers with a sales offer. What we did briefly:
Step 1 to 3: customer view, training- and testing & model evaluation and - selection
We demonstrated briefly how to set up and execute a data driven retention strategy step-by-step using a churn model. Although the predictive model performed as expected and the churn rate decreased, overall the ROI was negative for this specific business case. The company and the customer base was too small at that given time to make the pilot a solid investment. The results of this pilot were presented within the organization to encourage more data driven solutions for specific business challenges.
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Arjan Schoe
Director Data & Analytics
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