If your measurement strategy delays decisions, it’s broken | MarTech

Marketing measurement has changed a lot in recent years. Attribution alone isn’t enough, and most brands know it. Incrementality testing and media mix modeling (MMM) are no longer optional.

Yet many teams are still stuck. Not because they don’t understand measurements, but because they don’t know how to act when the data isn’t perfect.

Measurement should lead to action, not delay it

Measuring is there to substantiate decisions, not to absolve teams of the responsibility for making them. That sounds obvious, but it is not how many organizations behave in practice. When attribution says one thing, an incrementality test says another, and a model points to something else, the instinct is to pause, ask for more analysis, or wait for cleaner data.

Disagreement between measurement approaches is typical. The mistake is to regard it as a reason to do nothing. At some point, teams still have to decide what bet they are willing to make based on imperfect information. It is a misconception to claim that a measurement book will completely remove uncertainty.

Incrementality testing is the most powerful tool in a marketer’s toolkit, but they are not without challenges. Too often, these challenges prevent teams from getting started. And even when tests are conducted, they can prevent teams from taking action on the results. Common expressions include opportunity cost, confidence intervals, and results represent only a moment in time.

These are all reasonable concerns. But the biggest risk is not that the tests are imperfect. It’s that doing so doesn’t change anything in the marketing program, even if it means re-testing, making it more likely to get a better read.

Why MMM is harder to trust than attribution

Media mix modeling presents a different kind of discomfort, especially for teams coming from attribution-heavy environments. Attribution feels accurate. MMM openly admits that it is an exercise in correlation.

When a model proposes to shift spend and predicts a positive impact on revenue, the immediate reaction is to wonder how that exact number will be validated after the fact. The reality is that it won’t, and that’s okay.

Too many things are changing at once to expect pure validation. Pricing, promotions, product mix, seasonality and broader business decisions all move in tandem with marketing. Expecting a perfect before-and-after comparison misses the point.

This is where incrementality testing plays a crucial role. It provides validation within the time period, helps account for confounding factors, and complements MMM. Together they are much more useful than either approach alone.

Stop chasing big wins. The real validation comes from the P&L.

Marketing teams often optimize for big, obvious wins because they are easy to identify. They make for great slides and compelling case studies, and they create the reassuring feeling that progress is being made. We’ve all seen them: “XXX% increase in ROAS.” or “Sales YYY% increase after one simple change.”

The details are always conveniently thin. The time frame is suspiciously short. Somehow, none of these breakthroughs ever seem to translate into broader business results. That trend is understandable. Marketing teams are often defensive, and in organizations that still view marketing as a cost center, there is real pressure to present the work as confidently and clearly as possible.

But the goal isn’t to have a perfect record when it comes to winning tests. It’s not about making perfect predictions or generating impressive case studies. In reality, sustainable growth rarely comes from one major breakthrough. It comes from accumulating small improvements over time, such as slightly better allocation decisions, a more balanced channel mix, and a sharper understanding of diminishing returns.

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None of these are worth headlines on their own. But they are quietly constructed and the validation is cumulative. That’s what actually shows up in the annual growth and healthier mixed metrics.

A measurement system works when teams confidently deploy capital and make optimizations that lead to sustainable business growth over time.

Measuring must create trust

I’ll never forget working with a CFO who helped me reimagine the balance between rigor and urgency. After hearing me explain why I wanted to structure an experiment in a certain way to isolate the impact of a significant change in the way campaigns were run, he said something like this:

“I don’t care about isolating the exact impact of the exact changes that have been made now. I need to grow the business. And right now, as we scale spend, we’re not scaling new customers, so something has to change.

I can judge whether this works by looking at the company data and not at your marketing results. I don’t need to perfectly isolate whether the impact comes from one specific marketing change or from multiple things happening at the same time.

Ultimately, the company is a system. When we are confident that multiple changes in the system will lead to profitable growth, we put our best foot forward and assess.”

That conversation changed the way I think about the balance between being informed and being accurate when placing bets. If your measurement approach makes teams afraid to take action, it will fail. The goal is not certainty. The goal is the confidence to make better bets more often in the pursuit of profitable growth.