Optimisation / Germany / Healthcare
Recover and win back dissatisfied customers
"The regular delivery of predictions enabled our client to promptly implement retention measures, very specifically targeting customers at high risk of churn."
Business issue
Operating in the pharmaceutical industry, our client was working on the implementation of a patient retention program, offering tailored services for their customers.
One key aim of this programme was to predict and identify dissatisfied customers on an ongoing basis, so the client could offer benefits that convert them into satisfied customers. Ultimately, this would detect churn whilst also ensuring patients were adhering to the effective treatment.
Due to the sensitive nature of the data, it was essential for this to be executed with data privacy and governance in mind in a way that protected patient information.
Our solution
Leveraging the client's CRM data, we developed an AI model which determined the drop-out probability for each individual customer. With a continuous stream of data, we continuously operated the model within a GDPR compliant and data-secure SaaS framework, whilst providing short-term regular updates.
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Impact
The AI model reached precision of more than 90% while maintaining a recall rate of above 60%. The regular delivery of predictions enabled our client to promptly implement retention measures, very specifically targeting customers at high risk of churn.
