Want to know how to do marketing mix modeling (MMM)? This is a critical step for businesses that must understand and remain aware of the impact of marketing channels on incremental sales.
Compared with other modeling methods, MMM incorporates online and offline media channels into its dataset. In addition, MMM also accounts for a wide range of external influences, including pricing, inventory, and distribution.
We’ll provide a brief overview of the process of how to do marketing mix modeling. Consider it a 30,000-foot view; the minute details — the domain of econometricians — are beyond the scope of this blog piece.
Marketing Mix Modeling: How to (Overview)
Traditional marketing mix models use four common variables in their construction — aka the “Four Ps”: price, promotion, product, and place (or distribution). Later strategists added two more Ps, people and process, into the mix.
The Ps are utilized and (over the long-term) adjusted in order to create marketing strategies. MMM’s output is usually an additional variable (sales or website conversions, for example).
Here are the four main steps of how to do a marketing mix model (an overview):
- Input the data.
- Analyze that data (some of the more common approaches to this analysis include correlation matrix and pair plots)
- Apply non-linear transformations (preferably multiple configurations)
- Build the model (linear regression analysis)
- Graph the data (for example, predicted vs. actual incremental sales)
Advantages of MMM and Leavened’s Approach
When it comes to marketing mix modeling, businesses and the agencies with which they partner are often at a disadvantage. Or, at least, they have historically been at a disadvantage.
Why? Because MMM modeling can be expensive. It can also be time-consuming. Plus, more often than not, the datasets and analysis are hidden beneath a shroud of secrecy.
So not only does MMM often cost a lot of time and money, its results are usually presented without transparency. In other words, businesses must accept the results and the analysis on faith.
Leavened figured out a better way to perform marketing mix modeling. The Leavened way — powered by the Leavened Iterative Hypothesis Testing Engine (LIHTE) — is less expensive, much faster, and totally transparent.
Leavened thinks every member of a brand and/or agency team should be involved in the process. Other solutions take the data and return (often many) months later with answers that may not make sense. Or the results can be presented with inadequate context.
Leavened tests every variable and does so without black boxing any steps of the analysis. In fact, the analysis is downloadable from our platform and the process is 100% transparent.
Best of all, Leavened will teach agencies to use the tools. Those same agencies can even brand the results as their own.
MMM vs. MTA
Finally, it can be helpful to compare/contrast MMM with multi-touch attribution (MTA). Media mixed modeling is much older than multi-touch attribution modeling, for one thing.
But there are substantial and fundamental differences between the two. They differ both in approach, operation, focus, and in how they analyze data that leads to marketing budget allocation.
For example, MMM relies on aggregate data (historical data, to be precise) rather than the real-time focus of attribution models. Both these approaches have their pros and cons when it comes to marketing activities. Each can inform how to proceed in the wake of data analysis, reporting, and interpretation.
Does a marketing mix model work for everybody? We think so. Leavened performs a high level statistical analysis (linear regression analysis). The results can be immediately implemented in a new round of marketing efforts and marketing tactics.
The impact on sales can be gleaned in real time, thus further informing marketing campaigns and influencing future business outcomes.
Get in touch with us today to learn all about it.
