Enabling sales reps to target relevant physicians to increase brand awareness and sales
Next Best Sequence of Marketing Activities
The Akaike Edge
Experienced ML and DL Ops teams
Efficient Deployment 0%
Ongoing Maintenance 0%
Collect the marketing and claims data from different sources
We gathered data on physicians and patients from a variety of sources in order to better understand the actions of physicians and the medical claims made by patients. We compiled statistics on physician engagement in marketing, prescriptions, demographics, medical and insurance claims from patients, and patient treatments. Marketing data was further fragmented into PP(personalized promotion) data, such as in-person visits, and NPP (non-personalized promotion) data, such as emails to make the solution even more effective.
Feature engineering and model building
Using deep learning algorithms, a complex sequential AI model was trained from relevant physicians’ features such as patient treatment history, active patients count, treatment and prescriptions behavior, marketing activity engagement patterns, and more. Features were designed using historical data for a specific time to predict the Next-Best-Sequence of marketing activities.
Transfer the model output to the omnichannel dashboard
Next-best sequence activities were rolled out to the customer’s omnichannel dashboard for effective utilization by sales representatives and marketing teams. Later, the model was also improved for marketing expenditures to obtain the best return on investment for each marketing activity by a dollar. The customer profited from this strategy both from a budgetary and effectiveness perspective, making it the optimal sequence of marketing activity.
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