#FutureReadyHealthcare
Indegene Enables a Biopharma Achieve 2x ROI with Data-driven Pharma Marketing Mix Strategy
The Client
A global biopharmaceutical leader embarked on a journey to optimize its pharma marketing mix (MMX) strategy through a scalable and data-driven in-house solution. With four distinct brands across rare diseases, oncology, and neurology, the company aimed to improve channel engagement, enhance portfolio-level decision-making, and ensure more efficient budget allocation.
This initiative aligned with the client’s broader ambition of becoming a truly omnichannel organization, i.e. leveraging data to engage the right healthcare professionals (HCPs) , at the right time, through the most effective mix of channels, all while delivering measurable commercial impact.
The Challenges
Lack of clarity on optimal channel mix for HCP marketing - The client lacked insights on the most effective combination of engagement channels—such as face-to-face (F2F) interactions, emails, phone calls, and virtual meetings—which hindered their ability to allocate resources efficiently and execute a data-driven multi-channel marketing strategy targeting HCPs.
Difficulty in channel ROI attribution - Measuring the return on investment (ROI) for each channel proved to be another challenge. Additionally, there was no clear method to assess which channels drove the best outcomes. This made it difficult to justify HCP marketing spend and optimize future campaigns.
Lack of transparency in external studies - The client relied on an external partner to provide reports on its pharma marketing mix strategy. However, these reports were 'black box'—they lacked visibility into the methodology, underlying data, and specific insights.
The Solution
To enable a data-driven and scalable marketing mix strategy , we deployed NEXT Channel Optimization , Indegene’s proprietary machine learning-powered, self-serve solution that measures, benchmarks, and optimizes marketing effectiveness at the segment and channel level, faster and more efficiently.
We reviewed past marketing mix reports and conducted workshops with analytics and brand teams to understand which channels were being used, how campaigns were executed, and how HCPs were being engaged. We also factored in legal and compliance considerations from the start.
With these insights, we designed a project plan that addressed gaps left by previous marketing mix studies and ensured the client had full ownership of their MMX solution. We built the necessary data architecture and pipelines to enable real-time access to channel and HCP data . Additionally, we collaborated with the client to upgrade their technology to ensure long-term scalability. We then developed a custom marketing mix approach using four statistical models—Multivariate Regression (OLS, Ridge, Lasso) and Bayesian Regression—tailored to fit brand and channel data trends.
Finally, we integrated NEXT Channel Optimization into the client’s environment, allowing business users to run models independently. A complete marketing mix analysis for each brand was then executed on the solution to generate brand studies or reports with actionable recommendations on channel optimization and potential returns.
Beyond implementation, we focused on change management by training the client’s data engineers and data scientists to equip them to manage and refine the solution.
The plug-and-play functionality was the key differentiator of NEXT Channel Optimization that enabled users to execute models without external support. We implemented three modules to provide a comprehensive analysis: Channel Optimizer for selecting the best marketing channels, Brand Optimizer for brand strategy insights, and Enterprise Portfolio Optimizer for portfolio-wide decision-making.
Outcomes
By the end of the engagement, the client had a fully transparent, adaptable, and easy-to-use solution which helped it achieve significant improvements in its multi-channel marketing strategy and sales performance.
In the future, marketing mix solution will include additional brands and channels for a broader, more comprehensive analysis and improved HCP marketing.
~0–20% ↑
Sales from channel mix recommendations powered by NEXT Channel Optimization
0x
Return following 40% increase in investment in phone and virtual channels
~0% ↑
Potential sales with same investment using MMX recommendations
