Retail/B2B
Marketing Mix Model (MMM) Analytics for Mid-Size Companies
Business Need
A regional soccer organization, operating with a lean team, wanted to boost ticket sales and optimize its marketing spend. It relied on radio, bus signage, and billboards but struggled to determine which channels delivered the best results.
Solution
Customer Analytics implemented a next-generation Marketing Mix Model(MMM) through custom application of AI and machine learning, to transform the soccer team’s raw data into actionable intelligence. The project also included a spatial analysis of ticket buyers to identify the ideal geographic boundaries within which to purchase ads. Typically, MMMs require large budgets and heavy computing power, but this tailored solution gave the organization the ability to simulate different mixes of marketing channels and budget, and forecast outcomes with high statistical confidence.
Highlights
Advanced Marketing Data AnalyticsPredictive Analysis of Marketing Activity ROISpatial Analysis for Targeted Ad SpendsDynamic/Adaptive Model
Outcome
The MMM transformed the client’s data into actionable marketing intelligence. The team can now identify which channels and campaigns deliver the highest ROI. This insight allows them to reallocate budgets effectively and pinpoint when additional spending no longer drives meaningful returns.
Through scenario simulations, the team can analyze two paths for optimization:
• Increase revenue by 12 to 18% by focusing on high-performing channels.
• Reduce costs by 20 to 25% while holding revenue flat by eliminating waste in low-performing channels.
PREVIOUSMember vs Group Analysis
NEXTAcademic Staff Operations Management Solution