The illusion of precision
Most marketers already know attribution models don’t tell the full story. Whether it’s last-touch, linear, MTA or “data-driven” models, attribution reports track touchpoints, not impact. And yet, despite this fundamental limitation, attribution remains central to how most marketing decisions are made today. In fact, research shows that 78% of marketers still rely on last-click attribution and web analytics to evaluate media effectiveness even as trust in these methods continues to decline.
After more than a decade in performance marketing, I’ve seen this play out again and again. Teams huddled around attribution dashboards, treating platform data as gospel. A dip in a KPI? Alarms go off. Budgets are reallocated. Creatives refreshed. Audiences rebuilt. All in the name of “agility”.
But here’s the truth: attribution doesn’t measure impact, it measures paths and optimising paths is just optimising noise. Attribution models aren’t designed to explain impact. They can’t isolate what would have happened without that touchpoint. They don’t account for bigger forces like seasonality, competitive activity, pricing shifts, or demand cycles.
So while the data may appear precise, it does not identify causality. And when decisions are made based on attribution alone, there’s no guarantee that changes will actually improve business outcomes. So we end up reacting to changes that we have no control over and that have nothing to do with marketing effectiveness.
This illusion of precision is costly for businesses. It directs focus toward what’s easy to measure, not what matters. It biases spend toward channels that look good on paper, not the ones that drive long term growth. It pushes marketers into a cycle of reactive decision-making, chasing short-term performance at the expense of sustainable impact.
If we want to make better decisions and focus on real business growth, we need to let go of this false sense of certainty and shift toward tools that actually reflect how marketing works:
It’s not a tidy, linear journey from view to click to buy. A broad body of research across marketing science, behavioural economics, and brand strategy consistently shows that growth comes from reaching as many category buyers as possible, building mental availability, and reinforcing memory structures over time. Most purchase decisions are made when customers are already in-market and in those moments, the brands that come to mind most easily are the ones that get chosen. That’s the real dynamic we need our measurement systems to reflect not just visible touchpoints, but the cumulative, often invisible effects that shape demand over time.
Redefining how you measure
Attribution isn’t the problem, it’s simply being asked to do a job it was never designed to do. That’s why we need to stop searching for a single “source of truth” and instead build a measurement toolkit that reflects the full complexity of modern marketing. It’s not about swapping one model for another. It’s about using the right tool for the right question and combining them to form a complete, evidence-based view of impact.
Attribution can give some directional insights, but it shouldn’t be relied on to measure true impact. It often misses important context and can’t show what actually caused a result especially as data privacy changes make it even less reliable.
Controlled experiments can strip away guesswork and give clear causal answers. They’re unbeatable for proving if a specific tactic truly shifts outcomes. But they’re also narrow. By design, experiments can only be run in specific scenarios, on specific questions, so they can prove if something works, but they can’t explain everything that does.
That’s where MMM comes in.
However, if you’re treating MMM as a slow, annual planning tool, it’s like navigating a storm with last season’s weather report. Markets and businesses move quickly, and a model that lags months behind reality can’t guide today’s choices.
With faster refresh cycles, richer data inputs and better validation, MMM has become one of the only tools capable of separating signal from noise in a world where attribution has collapsed. Done properly, MMM is no longer just a high-level strategic tool, it’s a living system of record for what’s really driving real outcomes. It doesn’t just show where to spend more, it exposes what actually grows the business and gives the ability to act with confidence, not react to noise.
And accountability is rising. Open MMM validation frameworks are now raising the bar for validation, making it harder to hide behind black-box models. If your measurement can’t withstand that level of scrutiny, it’s not built for the next decade.
A new growth mindset
So what’s the path forward? Let go of attribution as your main source of truth. It has value for platform optimization, but it can’t show true impact. Instead, invest in a toolkit that works: use experiments to test specific tactics and modern MMM for accurate, ongoing measurement of what’s really driving growth.
Letting go of attribution as a single source of truth doesn’t mean losing control, it means gaining clarity. It means trading surface level certainty for deeper understanding. And it means finally aligning how we measure marketing with how marketing actually works for driving growth.
Marketers who thrive in the next decade will be the ones who understand what data can and can’t tell them. Who know when to zoom in for detail, and when to step back for perspective. Who recognizes that measurement isn’t about optimising isolated metrics, but a tool for focusing on what really matters: driving sustainable business growth.
This shift is already happening. More and more teams are rethinking how they measure impact, testing new methods, and adopting more robust, modern systems. The tools are here. The evidence is clear. And the benefits for business clarity and long-term growth are significant.
The only real question is: are you ready to move beyond legacy systems, and build a measurement approach that truly reflects what drives growth today?
Andie Potter is a Marketing Science Partner at Mutinex.
