What is Media Mix Modeling?Also known as marketing mix modeling, MMM is a statistical method of measuring the performance of diverse paid, organic, and earned media on driving key outcomes, such as sales or revenue. The top-down analysis afforded by MMM allows your marketing team to adjust and optimize the mix of marketing, i.e., what kinds of ads get placed where and when, and make meaningful predictions about their outcomes. Most importantly for the future without cookies, MMM doesn’t rely on tracking individual users or their behavior.
How Does MMM Work?MMM works by analyzing large data sets (ideally at least two years’ worth of weekly data) consisting of marketing activity, pricing, trade or sales team activity, competitive activity, economic trends, and other external factors that can positively or negatively influence your sales outcomes over time. The analysis assesses how each of your media channels, offers, and promotions contribute to total sales in the context of these other factors outside of your control. This is essentially detecting how certain changes in impression levels and the media mix change the sales outcomes in the weeks and months that follow. With non-marketing and external factors included, MMM can calculate marketing contribution even when sales are declining or are partially offset by competitive activities. A good MMM compares any number of variables against each other in order to adequately track the strength and effectiveness of each in contributing to the final goal. These variables could be sales, revenue, new customers, engagement, or some other metric that you’d like to measure.
Why is MMM Important in a Cookie-less World?MMM is important for a big-picture perspective in a post-cookie world and actually offers advantages over MTA (Multi-Touch Attribution) modeling in the current world with cookies. Attribution models added insights beyond last-touch attribution, but never fully captured the impact of non-digital media or external factors. While bottom-up alternatives to MTA may emerge, MMM remains the best and most well-understood top-down attribution method. The flexibility of a strong marketing mix model is unparalleled in terms of a holistic, top-down, controlled viewpoint. As technology improves, so too will the ability to find data points with which to build a robust model.
How to Use MMMThe first and most important step is to gather a comprehensive data set to build the model. Like other statistical models, the key behind a strong prediction is finding the right mix of quality data with as little noise as possible. If your company doesn’t have at least a couple years’ worth of data to begin with, the validity of your model may be limited (but can still offer directional insights). To start with, gather as much information as possible as it relates to:
- Marketing Activities: Promotions, sales, and all marketing activities. You’ll need a breakdown by week (monthly works but is less predictive) of impressions and spend for all marketing activities.
- Non-Marketing Activities: price changes, product availability, distribution and product add/drops that can change sales outcomes independent of marketing. The model not only quantifies these impacts on sales but also better predicts marketing contribution with more complete data.
- Sales: Unit/dollar volume sold (including the percentage on promotion).
- Market Conditions (or External Factors): Economic trends such as inflation or consumer sentiment, competitive spend (if available from 3rd party sources), and other exogenous factors (e.g., COVID, etc.).