Aarstiderne gains unique
insight into customer loyalty
– The Advanced Analytics model Kapacity Buzzard
identifies customers who are at risk of becoming inactive
Kapacity’s new Advanced Analytics model, Buzzard Framework, makes predictions and tells Aarstiderne which customers are at risk of churning – with great precision.
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 Buzzard 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.
Kapacity Buzzard Framework
The first edition of the model was based on 25 different parameters, including transaction data, marketing definitions, web and app activities, customer supply chain experience as well as basic master data. All of these data were fed into the model – and already at the first round, Buzzard was able to differentiate the customers.
Over time, the model has been further developed and refined, now working with more than 300 different variables. Concurrently with this improvement, the precision has increased significantly. Carsten Dreyer Christensen says:
“The model now tells us with great precision which customers are at risk of churning as well as which customers are deemed loyal,” and he continues: “This will not save the world, of course, but the solution’s value potential is very important!”
Within a few months, when the model’s precision has become even better, Aarstiderne will use the results to increase the customer experience for real.
Being at the centre of a pilot project
As mentioned earlier, Aarstiderne’s Buzzard solution was delivered as a pilot project. In this respect, Carsten Dreyer Christensen says:
“It has been a really great and interesting phase that has been instructive for both parties. Kapacity has invested a lot of energy in the project, resulting in a well-functioning solution that gives us great value.”
Carsten Dreyer Christensen also emphasizes the high amount and good quality of Aarstiderne’s data as an important factor for the project, thereby forming a good basis for the Buzzard solution.
About being the first mover, Carsten Dreyer Christensen says: “It is interesting that Aarstiderne is among the first companies to use Machine Learning. I find that awesome, actually.”