Marketing Mix Modeling (MMM) vs Multi-Touch Attribution (MTA)
Marketer’s have been using MMM for decades to provide a “top-down” approach of campaign performance. More than 60 years have passed since the invention of marketing mix modeling. One of the earliest businesses to employ this kind of marketing study was Kraft Foods, that did so in the 1960s to enhance its operation and understand the impacts of changes in sales trends.
MMM — 101
Marketing mix modeling or Media mix modeling (MMM) uses statistical methods like multivariate regressions, hierarchical mixed effects modeling, or time series analysis on sales and marketing data to calculate the effects of various marketing tactics (marketing mix) on sales and then predict the effects of upcoming sets of tactics.
With the help of the MMM analysis technique, marketers can evaluate the results of their marketing and advertising efforts to establish how multiple variables contribute to their objectives ( which is usually to drive conversions). Because it utilizes aggregate data, it can analyze a wider array of traditional and digital sources. Additionally, MMM enables marketers to take into account other influences like promotions and seasonality.
How does MMM work ?
Media mix modeling performs statistical analysis (e.g. multiple linear regression) to determine the relationship between dependent variables such as sales and engagement and independent variables such as advertising spend across channels. MMM can use linear and nonlinear regression techniques to determine how an increase in advertising/ marketing spend affected total sales.
When using MMMs, it is important to distinguish between the data you want to measure and the data you can actually measure. It’s important to spend time aggregating and cleaning data from internal databases, third-party sources, or both. MMM typically requires 2–3 years of data to account for factors such as seasonality.
MMMs are much too slow for the online world, often providing results weeks after a campaign has been completed, rather than during one.
Fortunately, the move to digital marketing has given marketers the tools and techniques to modernize their marketing attribution models, allowing them to track every step of the customer journey.
MTA — 101
The application of attribution theory in marketing today is the shift in advertising spending from traditional offline advertising to digital media and the availability of data through digital channels such as paid and organic search, display and email marketing.
How does MTA work?
MTA is designed to assign credit to the individual touchpoints that affect consumers’ path to purchase. These models are built to measure each channel’s contribution along the customer’s journey, providing a clearer picture of which investments (or combination of investments) improve key business metrics.
MTA can have limited visibility into offline conversations and largely focus on digital marketing platforms.
MMM vs MTA
- MMM is good at providing a top-down, macro-level view of your marketing across all channels.
- MTA is used for a bottom-up analysis of your marketing investment. It’s considered a more granular approach.
- As a result, in most cases MMM insights are delivered on a quarterly basis, whereas MTA results are reported daily.
- MMM lends itself to big strategic media portfolio considerations and long-term planning cycles while MTA outputs can be used to make very tactical near-term shifts in budget allocation.
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