McKinsey Interviewed 50 Marketing Leaders. None Could Prove ROI.

A relatively new McKinsey study on marketing technology landed on my desk last week, and I need to talk about it. Not because it says anything I didn't already know. But because it finally puts hard numbers behind what I've been telling clients about their marketing for years.

The finding that stopped me cold:

Researchers interviewed more than 50 senior marketing leaders at Fortune 500 companies. Not one could clearly articulate the ROI of their martech investments.

Companies spending millions on customer data platforms, journey orchestration, personalization engines. And when asked how it translates to business results? Nothing.

This is exactly why CFOs treat marketing as a cost center. We've earned that reputation. Not because marketers don't want to prove ROI, but because the tools are complex, the stacks are fragmented, and nobody taught marketing teams how to tie their work to revenue.

What the Study Actually Found

McKinsey reports the martech market hit $131 billion in 2023. It's projected to reach $215 billion by 2027. Companies keep pouring money in, expecting transformation.

What are they getting instead?

According to the study, roughly two-thirds of B2C organizations rate themselves as "developing" or merely "operational" in martech maturity. And when researchers conducted deeper interviews, that number got worse. Companies that thought they were doing well discovered they weren't.

Here's the data that matters:

• 47% of martech decision-makers cite stack complexity and integration problems as the main blockers

• 34% point to under-skilled talent as a key hurdle

• Most organizations still rely on basic tactics despite sophisticated tools

None of this surprises me. I've written before about the 33% martech utilization rate that Gartner found. About the 64% of B2B marketing leaders who don't trust their own measurement frameworks, according to Forrester. The pattern is consistent across every credible study.

Why This Matters for the Revenue Conversation

McKinsey identifies the core problem as measurement disconnected from business outcomes. Marketing teams track email sends, open rates, impressions, reach. Operational metrics. None of it connects to revenue growth, customer lifetime value, or margin contribution.

I've been having this exact conversation with clients for years. Marketing walks into budget meetings armed with engagement stats. CFOs want to know customer acquisition costs and return on investment. These are two different languages, and marketing keeps wondering why nobody's listening.

The study found that only 22% of CMOs have truly collaborative relationships with their CFOs. That number shows up in other research too. It's not a coincidence. When you can't prove you're making money, you get treated like an expense to minimize.

This is the gap that keeps marketing stuck as a cost center. It's not just the technology. It's the combination of stack complexity, tool overload, and the simple fact that most marketing teams were never taught how to connect what they do to revenue impact. The tools don't make it easy, and training is poor or doesn't exist.

Where McKinsey Gets It Right, and Where They Could Expand

The study frames AI as marketing's "second chance" to deliver on martech's original promise. The authors suggest AI can create intelligent systems that learn, orchestrate, and personalize in real time.

They're not wrong. AI does have the potential to finally make martech work the way it was supposed to. Intelligent orchestration. Real-time personalization. Adaptive systems that respond to customers in days instead of six-month campaign cycles.

But there's a critical step McKinsey should have expanded upon: None of that works unless the foundation is solid first.

1. AI is an amplifier

It makes whatever you already have more powerful. If your foundation is strong, AI accelerates your results. If your foundation is broken, AI accelerates your failures.

2. Bad data?

AI will make decisions based on that bad data at scale.

3. Misconfigured attribution?

AI will optimize for the wrong metrics and destroy your budget faster than any human could.

4. Sales and marketing not integrated?

AI will generate more sophisticated reports that still don't match, making the trust problem worse.

The companies that will actually benefit from AI are the ones doing the unglamorous foundation work right now. Clean data. Proper integrations. Trusted measurement. Clear processes. Sales and marketing alignment.

If that's not you, AI isn't your next investment. Your foundation is.

McKinsey touches on foundation first but doesn't emphasize it enough. AI can actually help you fix the foundation, not just build on top of it. AI tools can clean messy data, identify duplicate records, flag integration failures, and surface which tools in your stack aren't being used. It can audit your attribution setup and find where the gaps are.

The problem is that most companies skip straight to the flashy AI use cases like personalization and predictive modeling without using AI for the boring infrastructure work first. Start there. Let AI help you build the foundation, then let it help you scale what's working.

The Real Path to Revenue Center Status

McKinsey's recommendations focus on C-suite sponsorship, stack simplification, ROI measurement, and capability building. Those are fine. But they miss the fundamental shift that has to happen.

Marketing becomes a revenue center when it operates like one.

That means measuring total cost of ownership across the technology lifecycle. License fees, integration costs, maintenance, and the people required to run it. Then connecting that investment to actual business outcomes. Incremental revenue from better targeting. Customer lifetime value improvements. Margin contribution.

It means marketing and sales operating as one function with shared accountability. When marketing generates leads that sales can't close, that's a marketing problem. When sales ignores qualified leads, that's a marketing problem too. The customer journey doesn't care about your org chart.

It means proving contribution to closed deals, not just leads generated. Revenue influenced, not impressions delivered.

Can AI help with this? Absolutely. Once your foundation is solid and your data is clean, AI can deliver real transformation. It can orchestrate customer journeys, personalize at scale, and optimize in ways that weren't possible five years ago.

But the tool isn't the transformation. The foundation is. And the measurement discipline that proves marketing drives revenue.

What I'm Telling Clients Right Now

The McKinsey study validates what mid-market companies should already know: Bigger martech budgets won't save you. More tools won't save you. And AI won't save you if your foundation isn't ready for it.

What will get you to revenue center status is the boring work of fixing your foundation and proving ROI. Then AI becomes the accelerant it's supposed to be.

Audit your stack. Cut what you can't prove is working. Configure what remains properly. Build measurement that ties to revenue. Train your team to use what you have before buying anything new.

Then, once you can walk into a CFO meeting and show exactly how marketing investment translates to customer acquisition and revenue growth, you'll have the credibility to ask for more.

That's how marketing becomes a revenue center. Not by buying better technology. By operating like a business function that's accountable for results.

The companies that figure this out will have a significant advantage over competitors still reporting vanity metrics. The McKinsey data suggests that's most of the market.

Sources: 

• This analysis references "Rewiring martech: From cost center to growth engine," published by McKinsey & Company, October 2025.

• Additional statistics cited from Gartner and Forrester research.