The real divide: application, not technology
Today’s customer journey is more fragmented, faster moving and harder to track than ever. Consumers move between platforms, devices and channels in ways that don’t follow linear paths, and their decisions are shaped by factors far beyond paid media.
Despite this, many organizations still practice marketing mix modeling (MMM) with a decade-old mentality. Annual refresh cycles, separate ownership, and static inputs such as channel-level spend, impressions, or GRPs remain common. Some models assume linear, time-invariant effects or rely on last-touch logic, which does not accurately reflect how customers actually move across channels. These old assumptions no longer align with faster, more complex decision cycles.
Foundational practices still matter if they are applied thoughtfully. Multi-year data helps establish reliable baselines, and limiting variables support model stability. But the pace of change in consumer behavior, media and culture means these practices must evolve. New channels, trends, devices and market dynamics are constantly changing the way people engage, requiring data that captures emerging channels, real-time behavior and broader market shifts.
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MMM must reflect that complexity. It needs broader inputs, more frequent innovations, and an operating model designed to guide decisions as conditions change. However, the challenge does not lie in the technology itself. The real divide lies in how organizations approach MMM. Too often, models are used to validate past decisions rather than guide future decisions. Making MMM effective requires cross-functional ownership, better data access, faster feedback loops, and a mindset that views measurement as a continuous, decision-making capability.
The Interactive Advertising Bureau’s book Modernizing MMM: Best Practices for Marketers provides a practical blueprint for doing just that, focusing less on modeling theory and more on the impact of decisions.
What is needed to make MMM decision-ready
If your MMM is still running annually and based solely on campaign performance, you’re already behind. IAB highlights three principles that distinguish leaders from those who still rely on outdated methods.
- Earn trust: Transparency is non-negotiable. All input, assumptions and data lineage must be clearly documented and managed. This enables verification by legal, financial and procurement stakeholders. Trust is based on transparency, which strengthens the reliability of the model.
- Balance speed and stability: Models require automated data pipelines for frequent refreshes to reflect market realities. However, agility must be accompanied by discipline. Model retraining should be reserved for periods of meaningful underlying pattern shifts, to prevent noise from undermining leadership confidence.
- Drive Strategy: MMM outputs should directly support executive decision-making. This requires insights that leaders can act on, clear links to the P&L statement, and scenario planning that gives leaders confidence to take action. If a model cannot drive strategy frequently and reliably, it is designed inefficiently.
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The complexity of the customer journey and the need for real-time responsiveness require more than just model innovations. They require an operational shift. The IAB Guide outlines six best practice areas that will help build MMM into a truly modern, business-driven function.
- Stronger foundation: MMM needs more than impressions and spend. It is most reliable when there is detailed, multi-year data on paid, owned and earned media, plus external factors such as prices and market shifts. Centralized, well-documented data is essential.
- Omnichannel coverage and representation: Emerging channels should not be ignored or lumped in with other digital channels. Whether it’s CTV, gaming, podcasts, influencers, or commercial media, they should be treated as different, even if the data isn’t perfect.
- Speed ​​and flexibility: Do it often enough to guide the next decision. Ideally before and during the campaign, so teams can adjust spend as needed. That requires automated pipelines and modular components. Responsiveness is more important than perfection.
- Integrated measurement: MMM should not operate alone. It is highly recommended to triangulate results with attribution, incrementality, and lift studies. Conflicting results should lead to smarter hypotheses, not internal disputes. No one method provides every answer.
- Actionable, tailor-made results: Different stakeholders need different types of output. Managers want scenarios. Finances need clarity about business results. Media teams need ROI guidance. One well-structured model should meet all these needs.
- Organizational adoption: Even the most effective models fail without widespread adoption. That means embedding MMM into planning cycles, assigning ownership, and training teams to act on insights. If it has no influence on decisions, it is an expensive system that provides no strategic direction.
The road to maturity in the field of measurement
Most organizations don’t need real-time models to make progress. Clean data, a clear goal and one successful pilot that leads to a real decision are enough to get beyond the fundamentals. Tools and dashboards exist, but without organizational commitment and acceptance they do not deliver value.
Progress requires more than just a budget; it requires cultural alignment and a commitment to action-based insights.
Strong measurements are not about chasing perfection. It’s about enabling smarter, faster decisions and having the confidence to know what to do next.
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Marketers are under increasing pressure. Data changes reduce visibility. Platforms evolve quickly. New channels and behaviors surpass existing models. CFOs want more clarity about the impact of marketing.
MMM is not a luxury: it is mission-critical business infrastructure. Organizations that fail to modernize risk:
- Misaligned media investments: Spending money where the public isn’t.
- Missed optimization opportunities: Inability to adjust expenses during the flight.
- Leadership Skepticism: Difficulty linking marketing results to business results.
The question is not whether your MMM technology is up to date. What matters is whether your organization is structured to act on what it tells you. If your MMM isn’t making decisions, it’s time to reconsider your approach.
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Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the supervision of the editors and contributions are checked for quality and relevance to our readers. MarTech is owned by Semrush. The contributor was not asked to make any direct or indirect mentions of it Semrush. The opinions they express are their own.
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