Marketing has always been about getting the right message in front of the right audience. But with more channels, platforms, and data than ever before, it’s easy to feel like you’re navigating a maze. That’s where Marketing Mix Modeling (MMM) comes in, offering a sophisticated way to understand how your different marketing efforts impact business outcomes. Google’s latest tool, Meridian MMM, takes the power of MMM and blends it with machine learning to give marketers a clearer picture of how their marketing mix is really performing. But Google isn’t alone in the MMM game. So, let’s break down what’s going on.
The Problem with Old Attribution Models
If you’ve spent any time in digital marketing, you’re probably familiar with traditional attribution models. The most common ones—last-click attribution or linear attribution—are simple, but they’re not always accurate. Last-click attribution gives all the credit to the final touchpoint a user interacts with before converting. That’s great if you’re trying to optimize for immediate sales, but it completely ignores the other 10 touchpoints that may have influenced the decision.
Attribution, in general, tends to oversimplify things. When someone clicks on an ad, it doesn’t mean that one interaction alone caused the conversion. It might have taken multiple impressions, emails, social interactions, and even offline touchpoints. Traditional models fail to capture this complex journey, leaving marketers with skewed insights.
That’s where Marketing Mix Modeling (MMM) is different. Instead of focusing on individual touchpoints, MMM looks at the broader picture, factoring in offline data (TV, print ads) and other influences like seasonality, economic shifts, and competitor activity. It’s about seeing how all the pieces of your marketing strategy fit together.
Google Meridian MMM: How Does It Work?
Google Meridian MMM is a tool that uses historical data to evaluate the effectiveness of your marketing channels and predict future performance. Unlike traditional models that rely on click-through or conversion data, Meridian digs deeper. It uses machine learning algorithms to process large datasets and assess how various media—paid search, social, display, even TV ads—work in tandem to drive your business results.
Meridian is designed to help marketers forecast the ROI of different marketing investments and understand how shifting resources from one channel to another might affect their bottom line. By looking at aggregate data, it helps you identify which channels truly drive results, even when those results aren’t immediately obvious or measurable through traditional tracking.
For example, if you’ve been pumping money into your Google Ads campaigns but aren’t seeing the expected uplift in sales, Meridian can give you insights into whether your TV ads or social media campaigns are creating a halo effect. It won’t just tell you that ads on Facebook are doing better—it’ll show you how different channels influence one another, even indirectly.
Other MMM Solutions: Not Just Google
Google Meridian MMM is a new player in the space, but it’s not the only one offering advanced modeling solutions. Companies like Nielsen, Ekimetrics, and Modus Research have been offering MMM solutions for years. They all operate on the same core principles—using statistical analysis to understand how marketing activities contribute to sales and ROI.
For example, Nielsen has long been the go-to for media measurement, with deep expertise in traditional channels like TV and radio. Their MMM solutions are well-suited for large brands that need to integrate offline data into their strategies. Ekimetrics, on the other hand, focuses on creating highly customizable models tailored to specific business needs. Their MMM tools allow for a more granular, bespoke analysis that some brands might find more useful than Google’s out-of-the-box offering.
Despite these differences, what all MMM solutions have in common is their ability to bring together cross-channel data to help you understand the true impact of your marketing. Whether you use Google Meridian or another solution depends on your business’s needs—how much customization you require, how much data you have access to, and how much budget you’re willing to allocate.
The Role of Mobile Measurement Partners (MMPs)
As digital marketing becomes increasingly mobile-first, Mobile Measurement Partners (MMPs) like AppsFlyer, Adjust, and Branch have gained prominence. These platforms help track app installs, in-app purchases, and user behavior across mobile channels. But MMPs aren’t necessarily built to handle the cross-channel complexity that MMMs like Meridian excel at.
While MMPs provide incredibly useful insights into mobile app performance, MMPs also have their own MMM solutions that allow for a more integrated view of mobile app performance alongside other channels, helping marketers understand the broader impact of their campaigns. These tools bring together mobile-specific data with cross-channel marketing efforts, providing more accurate models of performance across digital and offline touchpoints.
Let’s say you’re running an app campaign on Facebook, but you’re also running ads on YouTube and Google Search. An MMP might help you track how many app installs came from each platform, but it won’t tell you how that Facebook ad contributed to the overall customer journey, or how your YouTube campaign is affecting the ROI of your Google Search ads. This is where MMM shines, showing how each channel contributes in ways that might not be immediately measurable through last-click attribution.
The Challenge of Cookie Attribution
With privacy laws like GDPR and CCPA becoming the norm, and cookie-based tracking being phased out by major browsers, attribution is becoming even trickier. Cookie tracking has always been a cornerstone of digital attribution, but it’s unreliable in a cookie-less world. As users shift between devices and use privacy tools to block tracking, marketers are losing the ability to trace a customer’s journey with precision.
Google Meridian MMM, like other MMM solutions, doesn’t rely on cookie-based attribution. Instead, it looks at aggregate data from multiple touchpoints, even when those touchpoints are cookie-less. While this might sound less precise than user-level tracking, it’s a more scalable solution, especially in a world where cookie-based data is getting harder to come by.
By using historical data and external signals, Meridian can help you understand the long-term trends that drive success, even when you can’t track every individual user’s actions. It’s not about tracking the precise click of a button—it’s about understanding how your marketing mix as a whole influences sales, brand lift, and customer loyalty.
Why Data Quality Matters
While Google Meridian MMM and other tools are incredibly powerful, their success hinges on data quality. The more accurate and comprehensive your data, the better the insights you’ll get. Whether it’s pulling data from Google Ads, Facebook, your CRM, or offline sales data, ensuring that everything is aligned and clean is crucial.
Good data doesn’t just mean more data. It means having the right data—whether it’s understanding how your TV campaign drove brand awareness or how weather patterns influenced sales during a particular season. The clearer your data inputs, the more reliable your output.
The Bigger Picture
At the end of the day, Marketing Mix Modeling is about big-picture thinking. In a landscape where every channel, platform, and data source matters, it’s easy to get lost in the weeds of daily campaign performance. But Meridian and other MMM solutions help you zoom out and make strategic decisions based on the long-term impact of your marketing efforts.
Whether you use Google Meridian, Nielsen, Ekimetrics, or an MMP solution, the core benefit is the same: understanding how everything works together. Marketing isn’t just about optimizing for the next conversion—it’s about building an ecosystem where all your efforts, digital and offline, align to create sustainable growth. That’s the kind of insight that makes MMM worth the investment.
