Dynamic Marketing Mix Modeling & Optimal Budget Allocation
A global electronics brand wanted to understand the effectiveness of a $50 million marketing budget, covering in-store pricing offers and a wide range of off and online media investments. Building on the results, the brand then wanted to optimize spend over the next planning cycle and forecast future sales performance.
To answer these questions, we conducted a dynamic marketing mix model, combining multivariate regression analysis with the power of time series econometrics. Working with the brand and its agencies, we collected over two years of weekly marketing spend, sales, in-store and consumer experience tracker data. We then ran our proprietary dynamic marketing mix analytics to determine the effectiveness of:
- Point of sale marketing
- Online paid search, social, display advertising and video
- Traditional offline TV and print media
- Pricing & promotions
The resulting model was then used to make recommendations on future budget optimizations and forecast likely sales outcomes.
We provided the brand with:
- A clear ranking of marketing initiative effectiveness based on historical ROIs
- Granular understanding of which marketing configurations – timing, spend amounts, media types – drove the best short-term returns
- Optimization of marketing budgets for the upcoming year resulting in ~10% increase in revenue for the same marketing budget
- Drivers of brand evolution and a clear view into how consumer brand perceptions and experience drives long-term brand performance
- Sales forecasts simulating the impact of alternative levels of media and promotional investments. This allowed our client to optimally manage product inventory, facilitating the supply chain planning process