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.
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.
Business Impact
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$14 Million
Profit Increase, Spanning 5 regions and 2 brands
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Globally Scaled
MMx models in 30 markets across 18 geographies
Mu Sigma is the world's largest pure-play big data analytics and decision sciences company. Through our Art of Problem-Solving, we strive to scale and systematize better decision-making through business intelligence services. Mu Sigma works across the entire decision support ecosystem (data sciences, data engineering, and decision sciences) with Fortune 1000 companies across the world, including 140+ Fortune 500 companies.
The firm's is derived from the statistical terms "Mu" and "Sigma," which symbolize a
probability distribution's mean and standard deviation, respectively.
