Our client – an American multinational snack conglomerate that serves over 150 countries – needed to understand the complete picture around one of their portfolios. In addition to identifying critical drivers for their ten power brands, the client wanted to:
Assess the effectiveness and payback periods for media and promotional activities
Determine price effectiveness for a major
Find any portfolio-level optimization opportunities
To accomplish this, we developed a market mix model (MMM) to provide a comprehensive look at their current situation and help them find ways to make for the future.
Answering What, Why, and How with MMM
Market mix modeling not only helped the company understand how their media and promotional activities were performing, but it also helped them:
Identify the key growth pillar for their
Create province-level segmentation strategies that drive growth
Use effective budgeting to support their media efforts
The client also used the model to target stores with the highest likelihood of success and enhanced in-store visibility and consumer promotions to promote further growth.
A Complete View of the Portfolio
To gauge the impact of various drivers on multiple brands, we built a regression-based market mix model using granular data. For portfolio analysis, we used brand-level results and estimated the elasticity of price and distribution for key SKUs across brands.
Thus, the model provided a detailed view of the entire business picture for this unit’s specific portfolio. With data-backed insights, they could now optimize media campaign spending and promotions across the brands. This led to the chance to increase payback at the portfolio level and drive up the portfolio’s value and ROI.
Data-Driven Decisions Enable Efficient Planning
Thanks to this market mix model, our clients understood what directions they needed to achieve portfolio growth. They also had a clear picture of how to support their actions with appropriate budgeting and planning, allowing them to operate with greater efficiency and precision.