Marketing measurement is a top priority for brands, yet many still struggle to apply advanced methodologies effectively. A 2024 eMarketer study found that 61% of U.S. marketers are actively working on improving their MMM capabilities, reflecting strong demand for better marketing mix modeling.
The urgency is even clearer in by WARC’s Marketer’s Toolkit 2024, , which surveyed 1,400+ executives globally. It revealed that measurement remains a top concern for 39% of marketers worldwide—rising to 48% in North America.
To meet this need, MMM has become more accessible than ever, thanks to open-source tools like Meta’s Robyn and Google’s Meridian. These solutions lower cost barriers, allowing mid-market brands to explore MMM without the heavy upfront investment once required.
But accessibility doesn’t equal adoption. Despite the availability of these tools, most marketers still aren’t implementing MMM effectively. Only 4% integrate multiple measurement approaches, such as brand lift studies, MMM, experiments, and attribution. Meanwhile, 22% admit to not using any modeling at all. This suggests that the barrier isn’t just access to technology—it’s the ability to implement it properly.
The Business Case for MMM
“Well-implemented MMM routinely improves marketing ROI by 10% and often as much as 20-30%” (WARC/Magic Numbers, Marketing Mix Modelling: How to Get Started and Ensure Success, 2023). With stakes this high, it's clear why MMM is gaining traction among brands looking to maximize their media efficiency.
At the same time, the measurement landscape is shifting. According to Google's MEM (Modern Effectiveness Measurement) guidelines, marketers can no longer solely on tags or multi-touch attribution (MTA).
Privacy restrictions and the decline of third-party cookies have made deterministic tracking increasingly unreliable. Instead, marketers need a hybrid approach, combining:
- Data-driven attribution (DDA)
- Incrementality testing (lift studies)
- Media mix modeling (MMM)
Google acknowledges that no single tool has all the answers anymore. Where attribution once sufficed, today’s marketers require a broader measurement toolkit—combining attribution, MMM, and experiments to fill in the gaps.
Why Agencies Are in the Best Position to Lead MMM Adoption
Agencies are already responsible for campaign execution and have access to key marketing data, making them well-positioned to take on MMM. Agencies already collect attribution data from GA4 and advertising platforms, which serves as a strong foundation for MMM adoption. However, to build a robust model, agencies also need to incorporate sales data and control variables—elements that brands can easily provide.
Additionally, agencies are perfectly positioned to run lift studies—a critical component of modern measurement. MMM and geo-lift studies together represent the best way to measure true marketing impact ([link to another article]).
How Agencies Can Package MMM as a Service
But beyond running MMM, agencies must think about how to package and deliver insights in a way that makes sense for clients. There are two clear service models:
Project-Based MMM (One-Time Audit)
Use Case: A brand new to MMM or looking for a strategic budget review.
Deliverable: A 12-week analysis identifying underperforming channels, reallocating spend, and recommending future experiments.
Upsell Path: Transition to ongoing MMM monitoring.
Subscription-Based MMM (Ongoing Optimization)
Use Case: Brands with continuous media investments that need regular insights.
Deliverable: Periodic MMM updates + real-time budget recommendations.
Optional Add-On: Lift studies (Geo Lift or incrementality tests) to validate MMM findings and measure short-term campaign impact.
Pricing Model: Retainer fee with potential performance-based incentives.
From Analysis to Execution
One of the biggest reasons MMM adoption lags isn’t just the technical challenge—it’s the gap between analysis and execution. Many brands that attempt MMM in-house struggle with:
- Operationalizing insights into media planning
- Adjusting budgets in real-time based on MMM findings
- Integrating MMM with attribution and other measurement tools
Agencies, however, have a clear advantage here. Unlike in-house teams that focus on just one brand’s data, agencies work across multiple clients and industries. This allows them to benchmark performance, identify trends, and apply insights faster.
MMM isn’t just about understanding past performance—it’s about adjusting platform-reported ROI to reflect true contribution ([link to another article]). Agencies that integrate MMM into their ongoing measurement frameworks can offer clients a more transparent and actionable understanding of their media performance.
Implementation: Build vs. Buy
For agencies looking to implement MMM, there are two main paths:
- Building an in-house MMM stack – Offers gives full control but requires significant investment in data engineering, model development, and infrastructure.
- Using a third-party SaaS MMM solution – Platforms like Forvio offer a white-label MMM solution, allowing agencies to run MMM for multiple clients without the technical overhead.
Both options have pros and cons, but for agencies looking to scale MMM quickly, SaaS-based solutions can significantly reduce time-to-value while allowing teams to focus on execution rather than technical complexity ([link to another blog post]).
Final Thought
The future of marketing measurement is multi-layered—and MMM plays a central role. While brands recognize the need for better measurement, many lack the internal expertise and resources to execute MMM properly. Agencies that invest in MMM expertise today will be the ones leading tomorrow, bridging the gap between data analysis and real marketing execution.
