Data Driven Insights
Begin by looking at the flow to get a sense of the flow zones that represent the high level steps used to turn our disparate input data into actionable insights.
Explore !The goal of this adapt and apply solution is to identify key drivers of adoption for pharmaceuticals to design smarter and more effective marketing campaigns by using regression models in Dataiku. More details on the specifics and requirements of the solution can be found on the knowledge base. This solution is available on installed instances and Dataiku Online.
Business Overview
Like any business, pharmaceutical companies depend on strategic marketing campaigns to increase the reach and knowledge of their products and ultimately boost sales. Modern marketing benefits from the usage of multiple channels of messaging to inform health care providers (HCPs) in a variety of ways.
But wait, what are we exactly talking about?
We need to differentiate the use of multiple channels in a siloed manner vs. the true omnichannel marketing which consists in targeting prospects/clients (here, HCPs) with the right channel (emailing, phone calls, online ads), with the right content (product vs. informative) and at the right time. To do so, pharmaceutical companies need to answer the following question: what are the best marketing channels to engage with each HCP while optimizing marketing spend?
Data and modeling are key to answering this question. Using historical data – sales, marketing, HCP preferences, etc. – to forecast future marketing performances generates many benefits. On one hand, it improves the HCP relationship with the brand, by fostering trust, ensuring adoption and loyalty, creating a close to 1:1 relationship. On the other hand, it enables pharmaceutical companies to truly assess the performances of marketing channels and how they interact with each other. Overall, both the HCP experience and the marketing efficiency are improved.
Highlights
- Prepare and blend multiple data sources containing product data, HCP account information, and marketing outreach data
- Build regression models to correlate marketing outreach for HCPs with future pharmaceutical sales
- Investigate sales trends, marketing efforts, and drivers of drug adoption with shareable visualizations and dashboards
- Run the entire data pipeline on new products using a simple application
- Learn how to adapt this starter solution to your specific needs in order to make smarter marketing decisions.
Join & Aggregate Data
Bring in data from multiple sources to be blended and aggregated with one another by account into a singular dataset containing sales and marketing outreach data.
Explore !
Relate Marketing Actions to Future Sales
Understand how long it takes for marketing action(s) to impact future sales, and input the optimal time frame in order to generate the most accurate insights.
Explore !
Extract Key Drivers of Adoption from Regression Models
Correlate marketing outreach for HCPs to the sales of our pharmaceuticals to better understand past marketing campaigns, and design more effective campaigns for the future.
Explore !
Prebuilt Dashboards
View the output from models and explore data further with the pre-built charts, graphs and tables specifically designed to quickly and easily identify issues.
Explore !