The following excerpt is from Google’s Rethink ROI event showcasing best-in-class client success stories, industry research, thought leadership, and product innovation.
For the “Masters of Measurement” panel discussion, Measured’s Chief Strategy Officer Nick Stoltz was interviewed by Marta Martinez, Managing Director, Data, Measurement & Analytics, Google.
Google Rethink Discussion:
From your vantage point, how are leading brands evolving the way they leverage synergies between MMM, attribution, and incrementality testing? What are the top barriers?
Here’s the honest take: Most brands don’t have a measurement strategy — they have a measurement diner menu. Media Mix Modeling (MMM) over here, attribution over there, maybe some incrementality testing when it’s convenient. And what happens next is pretty human — we bias toward the answer we like best. We cherry-pick the model that tells the most favorable story or matches the narrative that’s already in motion. MMM says one thing, Google Analytics (GA) says another, and incrementality only gets airtime if it confirms everyone’s doing a great job. That’s not measurement — it’s measurement theater.
Leading brands are moving beyond that. They’re not asking, “Which model do we trust today?” They’re asking, “How do we integrate these models into a single, consistent system that guides how we operate?”
That’s the unlock.
We see the best teams use incrementality to establish causal ground truth, then use that to calibrate attribution for speed and granularity, and train MMM for planning and forecasting. And because it all flows from one consistent foundation, it resolves conflicting narratives and creates what every organization needs: A “north star” for decision-making.
But it can’t stop at marketing. For this to work, it has to connect back to business strategy, so the CMO, the CFO, the analytics lead, the board — they’re all speaking the same measurement language. This isn’t just “What does the model say?” It’s about building an analytical framework that drives how the business moves forward."
Is the continuous test-and-learn cycle truly achievable? What are the critical ingredients and trade-offs?
Here’s my take: Most organizations talk about continuous testing, but what they’re actually building is continuous motion — not continuous value. They prioritize speed and scale: how many tests can we run, how fast can we get results, but they skip the most important part: Are we learning anything that actually changes how we operate?
Tests are expensive. They take time, money, and strategic focus. So when you build a culture of “test everything all the time,” without a clear learning agenda, you end up with what I call the “throwing-shit-at-the-wall incrementality strategy.” And that’s dangerous. It erodes trust in testing, undermines confidence in results, and turns measurement into noise.
The true value of automation and scale isn’t in running more tests, it’s in freeing up time to focus on the What, Why, and How. What should I be testing that will actually move the business? Why did I see the result I saw—what’s driving it under the hood? And how do I use that insight to change how I allocate budget, design strategy, and deploy media?
So yes, continuous test and learn is achievable, but only if we stop equating it with nonstop testing. It's not about volume. It's about building a continuous learning loop that delivers real value — every time you run a test.
How are brands using granular data to make smarter decisions, and what’s holding them back?
The problem today isn’t a lack of data — it’s too much. Brands are drowning in granularity: MMM outputs, attribution dashboards, incrementality lift curves sliced by geo, tactic, audience, and time of day.
But none of it means anything if it doesn’t translate into action.
That’s where most organizations get stuck — not because they lack data science or infrastructure, but because they lack curiosity. They want a clean, definitive answer, something that tells them where to spend, what to do, and lets them move on.
Marketing doesn’t work like that. We’re not solving for certainty, we’re solving for people. Real audiences, with real variability. Granular results are powerful when they ladder up — when they help us understand what’s working and why, so we can build smarter strategy and execution.
But granularity becomes dangerous when it ladders down, when it gets weaponized into overly simplistic takeaways. “This worked for this campaign, so it must work for everything.” That’s how teams end up chasing ghosts, mistaking local truths for universal answers.
The best brands don’t fall for that trap. They don’t just look for answers, they look for meaning. They connect granular data into insights, insights into action, and action into strategy. Because measurement isn’t about proving what worked yesterday for someone, it’s about building a system that helps you get better every single day.
Is measurement still siloed in marketing, or is it truly permeating the organization to drive business strategy? What signals a measurement-mature org? And what role does leadership play?
Measurement is evolving, but in most companies, it’s still largely a marketing function. It lives in the performance team or analytics org — and it gets referenced when there’s a planning cycle or a QBR. But truly measurement-mature organizations? They treat measurement as a strategic asset, not a marketing tool.
The shift happens when measurement stops being used to justify spend and it starts being used to guide decisions. That’s when you see marketing, finance, and strategy teams using the same models, speaking the same language, and aligning on the same version of the truth.
And the signal that you’ve reached that point? You stop hearing questions like, “Why is our ROAS down?” and start hearing questions like, “What are we learning? What should we do next?” That’s a totally different culture — one driven by curiosity, clarity, and accountability.
But that shift doesn’t happen by accident. It happens when leadership sets the expectation that measurement isn’t a post-mortem, it’s a system to run the business. It takes executive support to move from siloed metrics to a shared decision framework that drives growth across the org.
Because at the end of the day, measurement isn’t just how we track performance. It’s how we build confidence in our strategy.
How are client questions evolving? Are they becoming more sophisticated or are their priorities shifting? How is this evolution driving your product roadmap and partnerships?
The questions we’re hearing from brands today are very different than they were just a few years ago. It’s no longer “Is Meta working?” or “Can you validate my ROAS?” Now it’s “What should I be testing next? How do I build a learning agenda that aligns with my strategy? How do I connect measurement to actual business decisions?”
That shift, from using measurement to validate, to using it to optimize, is what’s driving our roadmap at Measured. And it’s why our partnership with Google has become so important. Together, we’re helping brands move beyond siloed tools and into structured measurement journeys — where every model, test, and insight ladders up to a broader plan for learning and growth.
And here’s what makes it truly game-changing: Measured has run tens of thousands of incrementality tests across hundreds of brands. That means we’re not just helping individual clients, we’re building what we call incrementality intelligence —insight into what’s working, across channels, across categories, across the ecosystem.
When we connect your test results to the patterns we’re seeing across the entire market — in real time — you’re no longer just measuring your media. You’re seeing the field. That’s what allows measurement to stop being reactive and start driving strategy.
That’s the unlock.