Clients' Challenge
Each semester, Health Care Practitioners (HCP's) across various treatment areas all around the globe are surveyed for their opinion on products and related companies used to treat patients. In this survey, HCP's are asked to state the products that are used to treat patients as well as the patient share allocated to each product.
Unfortunately, business users that want to consume these insights find the methods behind the analysis black-box too complex. In some cases,the insights require extensive training and effort. It would be more desirable for the business to receive transparent, intuitive and actionable insights such that they can react timely and help grow our clients' brand in its competitive landscape.
Our Solution
In our solution, we developed a machine learning model that was able to learn the link between customer (HCP) brand loyalty and the answers to the questions of the Loyalty survey.
Through model explanation, we reverse engineered the model to generate a brief summary of KPI's that most drive HCP's to use and grow the clients' brand in their treatment area. Both these insights and real-world brand performance were linked to provide users with an intuitive and on-demand dashboard of actionable insights. We used an interpretable model to ensure a white-box solution and validated the generated insights for maximum reliability and actionability.
Created Impact
The actionable insights generated with our white-box solution continuously helps business users to take concrete steps in order to ensure that HCPs remain loyal to the clients' brand. Moreover, these insights guide users in understanding which KPI's generally drive HCP's to use brands to treat their patients.
With our solution, our client never misses out on insights to grow their brands’ share and is always informed on the KPI's that help them retain strong competitivity in the pharmaceutical market.
