How Marketing Mix Modeling (MMM) Supports Smarter Media Investment Decisions

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How modern Marketing Mix Modeling (MMM) and tools like Google Meridian can help you reduce wasted spend, optimize media ROI, and make truly data-driven marketing decisions. This article is an adaptation of a longer piece by Elias Mourdi.

The marketing world continues to grow more complex, with new channels and short-term metrics to balance against long-term brand building. For marketers to understand what makes their customers tick, digital attribution, already weakened by the phasing out of third-party cookies and walled gardens, is no longer sufficient. To overcome potential blind spots, organizations need a holistic and reliable way to understand where investments are most efficient. Enter modern Marketing Mix Modeling, bolstered by cloud computing and open-source frameworks like Google's Meridian.

Spending More Doesn't Always Mean Earning More

When attributing media budgets, marketers know that more isn't always better. In practice, spending €1 million rarely doubles the impact of a €500k investment; this phenomenon is known as the law of diminishing returns. At some point, spending more on TV, digital, or social media yields little to no results, and marketing teams risk doing more without producing incremental value. And in a highly competitive context, as budgets grow tighter, the cost of basing marketing decisions on instinct alone becomes too high. 

The real question is less "How much did we spend?" and more "At what point does spending stop paying off?"

Invaluable to guide wise decision-making, the law of diminishing returns is at the heart of Marketing Mix Modeling (MMM)

What Modern MMM Really Does

In essence, MMM measures the contribution of each marketing channel to revenue over time. This includes all media (TV, OOH, digital, search, etc.) as well as external factors like price, promotional actions, seasonality, and more. MMM enables marketers to know which levers truly drive business performance by modeling historical performance and future scenarios.

However, reliance on MMM was long challenging, as previous solutions tended to be slow and expensive, and delivered as static, punctual analysis rather than actionable tools. Even with privacy-driven data loss, the modern version of MMM addresses many of these hurdles: when appropriately configured and fueled by scalable data pipelines, it combines precise measurement with dynamic modeling. And an essential effect that can be modeled is what leads to diminishing returns: saturation.

Why does saturation matter in marketing?

Saturation tells you where your next euro works hardest.

For example, channel A could yield significant returns at low spend, but these returns could decline quickly as the budget increases. This means that a high marginal ROI is reached at low investments for channel A. Yet for another channel, channel B, low investments show weak early returns, but they accelerate sharply after a certain threshold is reached. Knowing exactly when saturation happens means that organizations can:

• Avoid over-allocating to channels already "maxed out"
• Find untapped growth pockets

Turning MMM Insights Into Strategic Moves

Let's use Google's open-source MMM Meridian as an example – we've successfully implemented this solution for several of our clients with stellar results since its global launch in early 2025. As an open-source framework, Meridian enables transparency, flexibility, and complete control of methodology. Meridian can model both channel saturation and incremental returns, yielding two highly actionable outputs: 

• Diagnostic view: "Which channels are saturated?"
• Forward-looking simulations: "What if we shift 10% budget from TV to paid search?"

This MMM functionality allows marketers to test various scenarios before committing to spend. 

How to Secure MMM Success

While a properly configured MMM can be a game-changing tool for organizations, several steps must be followed to ensure its effectiveness.

• Your MMM requires high-quality, well-structured data input to produce accurate insights.
• Scenario testing and spend decisions require collaboration between marketing, finance, and data teams.
• Your leadership must be willing to challenge assumptions – your MMM might yield results that go against common expectations.
• … But remember that your MMM is here to guide decisions, not replace human judgment.

Instead of providing single answers, MMM offers a range of outcomes with confidence levels, thereby improving decision quality rather than forcing certainty. Ultimately, your MMM should help reconcile data with executive intuition.

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The pressure to maximize marketing performance is likely to continue rising. As budgets tighten and competition intensifies, Marketing Mix Modeling can provide companies with a clear and objective view of what drives growth. Properly tuned and integrated into decision-making processes, MMM helps ensure each euro works harder, avoids waste, and protects long-term brand performance. And adopting MMM, not as a technical model but as a strategic steering compass, empowers brands to make the best choice at the right time. To explore how fifty-five can find the best MMM for your needs, prepare your data and fine-tune a composable model for you, and accompany you throughout your MMM adoption, don't hesitate to contact us!