Optimizing Promotional Spending
A leading pharma manufacturer partnered with Mu Sigma to optimize promotional spending across various channels and geographies. The goal was to maximize profits in the NOAC (Novel Oral Anticoagulants) and DME (Diabetic Macular Edema) markets.
Marketing Mix Modeling
We implemented a 2-step Marketing Mix Modeling (MMx) methodology that:
Significantly improved data analysis readiness through the application of data transformation methods, including Linear-Linear, Log-Log, Linear-Log, Time Trend Variable, Dummy Variable, and Interaction Variable.
Strengthened outcome assessment utilizing diverse modeling techniques, such as Multivariate Additive Regression Splines (MARS), Ordinary Least Squares (OLS), and Partial Least Squares (PLS).
Promoted independent execution of MMx projects by the local teams through reusable components such as Jupyter notebooks.
The modeling exercise helped determine the relative impact of personal and non-personal promotions on drug prescription volumes in various regions. It also revealed that digital channels consistently delivered a higher ROI, emphasizing the need for action. Additionally, it identified non-responsive geographic areas, prompting the revision of promotional strategies and budget allocation in those regions.
Profit Increase, Spanning 5 regions and 2 brands
MMx models in 30 markets across 18 geographies
The firm's is derived from the statistical terms "Mu" and "Sigma," which symbolize a
probability distribution's mean and standard deviation, respectively.