Examining the Relationship Between Media Mix Modeling and Brand Health

Rah, rah, sis-boom-bah. M! M! M!

Media mix modeling (MMM) definitely has its cheerleaders among the marketing set. At the same time, it has undergone some criticism in recent years among branding advocates. But MMM and brand health can coexist with some strategic planning.

At its heart, MMM tends to focus on completed sales. Consequently, mid-level and upper-funnel media such as linear TV, over the top (OTT), and online video tend to get the short end of the budgeting stick after MMM models are run. However, MMM doesn’t have to snub upper-funnel dynamics. With a sufficiently flexible modeling framework in place, MMM can absorb and leverage all the signals that lead toward conversions.

Though many marketing teams have heard about MMM, they may not be certain how to implement it. If you’re interested in peppering your company’s or product’s MMM with historic brand-related data to glean more accurate budgeting recommendations, you can start with these specific actions:

Invest In a Brand Tracker

Investing in a third-party brand health tracking system capability can be a first step toward gathering the data needed to infuse brand-building impacts into any MMM model. Certainly, it takes time to amass brand health data: It can take a couple of quarters to craft a meaningful, trend-driven structure around brand awareness, brand consideration, and brand favorability. But once the brand tracker has been in place for six to nine months, the information can be inputted into the MMM model to gain richer, more holistic insights.

When evaluating potential brand tracking systems, make sure that you’re using one that offers numerous options. These can include competitor trend insights, as well as branded keyword monitoring and sentiment analysis based on the branded keywords you choose. In time, the feedback you collect on consumer perceptions of your brand can be fed into your MMM framework.

Leverage Social Listening to Capture Value of Earned Media

Subscribing to a social listening service which scrapes and curates social mentions of your brand and/or products can provide the raw inputs needed for your MMM to incorporate the value of earned media. The volume and sentiment of the chatter, as well as your brand’s share of voice relative to the category, are also strong signals that capture dynamics far beyond the realm of paid media that fill out a holistic view of the drivers of conversion.

Deploy Brand and Social Listening Data Into Your MMM

Your brand tracker and social listening data should be processed and aggregated to the same level as your media and conversion date (e.g., daily or weekly totals) and inserted directly alongside your media-based model features and the new brand- and earned media-based features would be engineered using the same process used for media factors.

And while paid media does not typically play a leading role in driving earned media, it often has a direct and significant impact in moving brand health metrics over time. This creates the opportunity to use those metrics both as features to explain conversion and targets that themselves are driven by paid media to create a richer and more nuanced modeling framework capable of capturing complex brand dynamics.

Will your MMM-meets-branding efforts pay off? Let me share a story to illustrate why it should: One of my clients integrated long-established brand tracker data into the company’s established MMM framework. Then, the client recast the same experiment without using the brand tracker metrics.

The outcome was obvious — and a bit exciting. The MMM model developed without consideration of brand health recommended a lower spend in online and streaming audio. When brand health metrics were factored in, the model ultimately found more value in —and suggested a higher spend toward — those upper-funnel channels.

Whether you’ve been measuring brand health all along or are new to the concept, get started today. When you do, you’ll be able to produce more comprehensive MMM models to better allocate your marketing dollars — and you’ll be cheering for a winning team.


  • Jared Rodecker

    With experience in a variety of statistical modeling roles focused on managing risk in Financial Services and Insurance, Jared Rodecker brings technical rigor and a keen interest in customer privacy and data security to his work at RAPP.

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