In the past year, 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. What did it take to achieve this goal?
“We made a list of various initiatives, one of which was to gain insight into which customers are most prone to churning,” says Carsten Dreyer Christensen, Head of Business Analysis.
After discussing with Kapacity, Aarstiderne chose to participate as a pilot customer in the Kapacity Churn & Retention Framework, which, based on a specific Advanced Analytics model and Machine Learning, is able to identify customers at risk of churning.
“It sounded like a win-win for both parties,” says Carsten Dreyer Christensen, continuing: “Kapacity needed a customer with relevant data for the project, and we needed a tool to help us further improve customer loyalty.”
Before initiating the development work for the actual model, clear objectives were defined, including what the model was supposed to do, the model change options level, and how simply it could be done.