I’ll be honest — a couple of years ago when marketing mix models started to catch on, I wasn’t entirely enthused. Like any new measurement technique or tool, I felt MMMs just skimmed the surface of tactical optimization when, to offer real value, they really needed to be used as a strategy support tool. But MMMs have gotten better at doing that. Specifically, today’s marketing mix models:
- Provide more operational guidance, aligning increases or decreases in marketing campaign spending with channel management and supply chain considerations;
- Link to trade-off analyses on a market segment or brand-equity level;
- Help companies monitor the impact of marketing programs on incremental revenue while further explaining that amorphous “baseline” number. Improved automated functionality is also allowing marketers to react more quickly to results based on their needs by, refreshing the models monthly to allow for more frequent changes in marketing support planning. Ever the devil’s advocate though, I still see some need for improvement. Specifically, modelers need to:
- Ensure that the organization as a whole understands the assumptions and limitations of the marketing mix model;
- Realize that laying the acceptance groundwork around those assumptions is as important and challenging as building the algorithms or collecting the data;
- Be aware of changes in the competitive environment and how they affect your results; this is an area where marketing mix models often break down;
- Understand that the model will, on occasion, fail; expect it and plan for it. Finally, don’t stop at marketing mix models. Risk is magnified by over-reliance on a single tool. Today’s marketing measurement toolkit needs to be much broader. Deep understanding of brand drivers, customer behavior and value require input from tools and techniques outside the mix model, as well as in. If you’re interested in more about marketing mix models, as well as how to evolve them, click here for the article on our website.