According to new research, only 22% of marketers strongly feel they have enough data to justify value to their CFOs. That means three-quarters of marketing teams are measuring success using a measurement model based more on belief than on data-backed proof, with real consequences for their strategy, budget, revenue impact and their relationship with the rest of the organization.
In fact, only 21% of CMOs today are aligned with their CFO around marketing budgets and metrics. Why? Because one party is measuring success and strategizing based on assumptions, while the other demands measurable, causal proof.
As media becomes more fragmented, traditional attribution leaves CMOs with an incomplete view of impact, and AI risks scaling decisions based on those flawed inputs. If marketing leaders are going to win over their CFO and deliver ROI, they need a new approach, one built on causal measurement rather than belief.
Why Marketers Have to be More Prepared Than Ever to Defend Spend
Marketing budgets are shrinking. The latest CMO Survey finds that marketing budgets have fallen to their lowest share of company revenues and budgets in several years. Overall marketing spending grew just 1.7% over the prior 12 months, the smallest rate increase since 2021.
When profits fall short of expectations, the C-Suite starts looking at what to cut rather than where to invest. And marketing often takes the hit, with expenses getting cut just over 45% of the time.
As inflationary pressures and reliance on AI increase, every dollar and cent invested in marketing needs to deliver proof of value, or the C-Suite will start holding budgets accountable. You can no longer just demonstrate activity. CMOs need to start proving impact.
The core of the problem? Marketers continue to speak a different language from their CFOs, bringing isolated attribution data and channel activity into the boardroom rather than defensible ROI.
Marketing, Budget Priorities Continue to Be in Conflict
But finance teams never operate on a maybe. They look to the facts: What revenue is being generated? What does it cost? What are the margins? To your CFO, marketing efforts are just another financial investment that needs to produce a clear outcome.
Further complicating things, marketing teams are being forced to comply with a financial reporting standard that their systems were never designed to support. In a recent study on the relationship between marketing and finance, as many as 71% or respondents believe fragmented tech and the disconnect between their ad tech and martech systems have at least somewhat limited their ability to prove their marketing value.
Without the technology and accurate forms of measurement, marketers and their budgets will keep getting pushed aside.
Operating on Belief: The Problem with Attribution
Attribution used to make sense as the primary form of measurement. In the early days of digital marketing, when a prospect clicked a search ad, landed on a page and made a purchase, the cookie connected the three events, and credit flowed to the channel that earned the click. We could see a path, assign value and move budgets accordingly.
But all of that measurement relies on multiple assumptions being true:
- That the purchase was made by a single user on a single device and in one sitting
- That we can track the entire buying journey in that one window of time
- That the platforms reporting the data had no stakes in the outcome
As channels have grown more complex and fragmented, those assumptions don’t hold up.
Attribution can’t measure the extended purchasing cycles of buyers today. Meta, Google, Amazon and retail media increasingly distort our view of what is really happening in a buyer’s journey — from first touch to final purchase. Consumers jump across devices. And offline influence to validate purchases blurs the line.
What you get is correlation, not causation. Under an attribution model, marketers spend more time guessing, optimizing towards credit rather than impact and operating on belief rather than building strategies around facts and data.
AI is Making the Problem Worse
Speed was supposed to be marketing’s advantage in the AI era. But right now, for many organizations, it’s just a faster way to be wrong.
AI use in marketing has more than doubled in the past two years, and companies project AI will account for more than half of all marketing activities within three years. And for good reason. AI helps teams work faster, automate tedious workflows and generate significantly more content. But the rapid adoption of AI isn’t positive when automation is simply layered on top of a measurement system that already mistakes sequence for cause.
An AI agent doesn’t pause to question the data it’s handed. It optimizes toward whatever the data tells it to, at a speed and scale no human team could match. So when AI is layered on top of the same broken attribution model marketers defer to, it won’t just produce a slightly flawed decision. It will produce a fully confident, fully executed, badly wrong one, and do so before anyone notices there was a decision to double-check.
The Solution: Embracing the Shift to Causal Marketing
No matter what the latest AI tool presents as your strategy, a marketing measurement stack built on belief and broken attribution models will leave CFOs unconvinced. It’s time for marketers to prove the cause of an outcome. Not just the sequence of events or activity.
Here’s what that takes.
Stop reporting clicks and start running incrementality testing. Hold out a geographic market (a “geo holdout”), an audience segment or a channel entirely and watch what actually changes without it. That’s the only way to know whether a channel is doing anything at all, and it’s the one method that answers the question your CFO actually wants answered: What happens to revenue if this spend goes away?
Let marketing mix modeling make your big calls. No more trusting your gut or letting a belief system run your marketing program. Instead, feed MMM your spend, revenue and the outside factors that move both, like seasonality, pricing, promotions. Then let the model tell you where the next dollar goes furthest before you touch a single channel’s daily budget.
Stop walking into budget reviews with three numbers that don’t agree. Combine incrementality, MMM and causal attribution in one unified marketing measurement stack, allowing them to check each other.
The pressure coming from your CFO isn’t going away. When the next board meeting comes around, and budgeting decisions have to be made, finance will keep asking their marketing leaders to speak in their terms: cause and effect, dollars in, dollars out.
Incrementality, MMM and a unified measurement stack that demonstrates causality are how marketing finally shows up to that conversation ready to defend their ROI and protect their budgets. Marketing leaders who make that shift will be able to walk into the next budget review with an answer instead of an argument and a CFO who’s already convinced before the meeting starts.
Tobin Thomas is the CEO and co-founder of Lifesight, a unified marketing measurement platform that helps brands prove the causal impact of their marketing through incrementality testing, marketing mix modeling and causal attribution. A longtime measurement practitioner, he writes The Decision Desk, a newsletter on marketing measurement and decision-making, and leads Lifesight’s research program and Scientific Advisory Council. He serves on the IAB Measurement board, where Lifesight leads the Project Eidos industry-standards initiative.
