This case study shows how Blend helped a pharmaceutical client implement an automated and model-driven approach to omnichannel marketing. We addressed issues of conflicting insights and lack of trust, transforming the approach into a scalable solution that drove incremental business value. The team optimized the recommendation algorithm, leveraging existing machine learning models to develop the Next Best Action and create a data architecture for automation. The impact was significant, with a 30% increase in sales and marketing ROI, vendor consolidation, and a 90% boost in digital effectiveness. This highlights our ability to transform marketing strategies and optimize efficience.
The Pharmaceutical client sought to revolutionize their omnichannel marketing strategy by implementing a more automated and model-driven approach. However, they were encountering challenges with multiple analyses for each brand, resulting in conflicting insights and organizational skepticism. Blend was entrusted with the mission of transforming their current approach into a future-proof, scalable solution that would drive incremental business value.
We co-created the concept and overall approach for the solution, providing detailed roadmaps and specific milestones along the way. One of the key aspects of the solution was the optimization of the recommendation algorithm, which took into account the expected number of TRx (Total Prescription) that would be generated from each marketing activity. By leveraging existing machine learning models, the team was able to efficiently create the Next Best Action, saving valuable time and cost by avoiding unnecessary reinvention. Additionally, we helped design a robust data architecture structure that facilitated automation across all models and analyses, ensuring a seamless and efficient workflow.
The solution brought about impressive results for the Pharmaceutical client. They experienced a 30% increase in sales and marketing ROI while saving 65% on resource expenses through vendor consolidation. Digital effectiveness soared by 90% as wasteful spending was eliminated and digitally-influenced targets were identified.
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