Only 30% of CMOs say they have a clear view of marketing ROI.
According to Gartner’s CMO Survey, that number was 40% not too long ago. It’s moving in the wrong direction, and the pressure from boards to demonstrate revenue impact has never been higher.
The problem isn’t that marketing leaders don’t care about measurement; almost all of them do. The problem is how the conversation gets framed, internally, with the board, and with the wider business. And when that framing is wrong, measurement budgets lose out to almost everything else.
Stop Calling It “Analytics”
The reframe that changes everything is simple. Stop calling it “analytics” and start calling it “data monetisation”.
“Analytics” sounds like an IT project. It sounds like dashboards, tracking configurations, and things that take months before anyone sees results. When you walk into a board meeting asking for budget to fix your analytics, you’re competing against headcount, product investment, and sales tooling. You will rarely win that conversation.
Data monetisation sounds like something that grows the business, because that’s exactly what it is.
The practical version of this reframe is to stop asking “What is the ROI of fixing our analytics?” and start asking “What decisions can’t you make without it?” Those are different questions, and they land differently with the people who control budgets.
The Questions That Create Urgency
What we’ve found running this conversation with boards is that the framing that works is specific questions, not general capability arguments.
Rather than explaining what better measurement would enable in the abstract, put the unanswered questions directly in front of the room. What is marketing’s actual contribution to the pipeline? If we increased the marketing budget by a set amount this quarter, how much additional revenue would that generate? Which brand activity is influencing deals and helping other channels close them?
Boards want to know the answers to those questions. If you can’t answer them today, but you have a clear plan for how you get there, you will get more buy-in than any measurement capability argument. The acknowledgment that you can’t answer a question, paired with a credible solution, is a more powerful position than most marketing leaders realise.
One worth paying particular attention to is the budget-to-revenue question. Boards are almost always under pressure from shareholders to generate more. When they ask what another 500,000 this quarter would produce, and you can’t answer, that’s a real vulnerability. Getting to the point where you can answer it, even approximately, is a material strategic advantage.
The Brand Doom Loop
There’s a compounding dynamic here that doesn’t get named enough. Underfunded measurement leads to unclear impact, which creates rising scepticism about marketing, which produces tighter budgets, which means less measurement. And around it goes.
The reason this loop is hard to break is that the thing generating the value, the data, is always one step removed from the outcome. Data produces insight. Insight produces decisions. Decisions produce revenue. When the board looks at a measurement budget request, they are being asked to fund something that’s three steps away from the result they care about. That is why the reframe matters so much.
Once you connect measurement to specific decisions the business needs to make, you collapse that distance. You’re no longer funding analytics. You’re funding the ability to answer questions the business is already asking.
What This Is Actually Costing You Right Now
The hidden cost of weak B2B marketing attribution is most visible in paid media. When your paid team is optimising for leads rather than pipeline, you are almost certainly spending money on the wrong things, and you won’t be able to see it clearly until you measure deeper into the journey.
We had a client in the subscription space where this played out in a way that still makes a good illustration. Their Google Ads campaigns were optimised for a low-cost conversion, registrations that required a spend of as little as a dollar. The campaigns looked like they were performing. High conversion volumes, reasonable cost per conversion.
When we pulled their CRM data and integrated it with the ad account, a different picture emerged. The keywords with the highest conversion rates were generating customers with very low lifetime value. A separate group of keywords, longer-tail, more enterprise in nature, had modest conversion rates but produced customers who were spending 50 to 100 times more over their lifetime. Two months after reallocating the budget toward those keywords and away from the high-volume, low-value ones, revenue had tripled.
The data existed the whole time, but nobody had connected it.
This isn’t unusual. Research suggests 50 to 80% of companies have never implemented closed-loop reporting. At a conference presentation last year, fewer than 10% of the room had integrated their CRM with their ad platforms. The gap between what’s possible and what’s actually in place is wide enough that fixing it is genuinely a competitive advantage.
The Dark Funnel Problem
The attribution challenge gets harder when you account for where B2B buying decisions actually happen. According to 6sense B2B Buyer Insights, 70% of the buying journey occurs before a prospect ever raises their hand with a vendor. By the time someone fills in a form, they have already been building a view of your brand and your competitors for weeks or months. Most of that activity is invisible to standard analytics.
The implication for content and brand investment is significant. If you are producing content, running a podcast, or building an executive presence on LinkedIn, you are influencing the early stages of that journey. When attribution can’t capture those touchpoints, the board will look at your content programme after two quarters and see no directly attributable revenue. They cut it. Then, two quarters later, branded search traffic starts falling because people who would have been researching you are no longer doing so. The cause-and-effect relationship is there, but the measurement gap made it invisible.
There is no perfect solution to this. Some of the dark funnel will remain dark. But there are practical steps that help.
Four Things You Can Do This Quarter
Map your decision gaps. Write down the five questions you wish you could answer but can’t because the data isn’t there. Treat these as your measurement investment thesis. When you can show the business that you can’t currently tell what drove pipeline last quarter, or trace a deal back to the first touchpoint, or calculate cost per qualified opportunity rather than cost per lead, you have the basis for a credible measurement roadmap.
Check your CRM and ad platform connection. This is the single fastest win on the list. Almost every major CRM now integrates natively with Google, Meta, and most other platforms. Connecting them means your paid campaigns can optimise against pipeline signals rather than just lead volume. If your paid team is optimising for clicks or form fills, that is where the conversation needs to start.
Audit your analytics honestly. Not a full rebuild. A genuine assessment of whether you can trust the numbers you’re currently making decisions on. Are conversions double-counted anywhere? Are there misfiring tags? Has anyone looked carefully at the tracking setup in the last year? Most of the issues we find when we audit a client’s analytics could have been found by their internal team. The audit just never happened.
Build one proxy metric for the brand. Attribution tools are good at measuring what can be measured. The dark funnel is real, and chasing perfect attribution is a distraction. A more useful approach is to build something defensible. Add a free-text field to your contact forms asking how someone heard about you. Cross-reference what they say with branded search volume trends. What you typically find is a meaningful gap between what analytics reports as the source and what people actually say. That gap tells you something important about where brand investment is doing work that tracking cannot see. Defensible numbers protect the budget. They don’t need to be perfect.
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The core issue is that data is always one step removed from the outcome. Data produces insight, insight informs decisions, and decisions drive revenue. When boards evaluate a measurement budget, they are funding something three steps away from the result they care about. Reframing the conversation around specific decisions the business cannot currently make, rather than analytics capability in the abstract, changes the dynamic significantly.
Connecting your CRM to your ad platforms is the quickest, highest-impact starting point. It allows paid campaigns to optimise toward pipeline signals rather than surface-level conversions, and the integration is now native in most major platforms. At a 2025 conference, fewer than 10% of attendees had done this. Doing so immediately puts you ahead of the majority.
A practical proxy combines self-reported attribution with branded search trends. Adding a free-text field to contact forms asking how someone heard about you surfaces channels, such as podcasts, LinkedIn, and events, that standard analytics misses. Tracking branded search volume over time gives you a directional signal on whether brand activity is generating awareness. Neither is precise, but both are defensible enough to protect the budget.
Closed-loop reporting means connecting your marketing data through to revenue outcomes in your CRM, so you can trace which marketing activities contributed to pipeline and closed revenue. Research suggests 50 to 80% of companies have never implemented it. Without it, marketing is optimising to intermediate metrics like leads or MQLs that may bear little relationship to actual revenue.
Three questions tend to generate immediate board engagement: What is marketing’s actual contribution to the pipeline? If we increase the budget by a specific amount, how much additional revenue will it generate? Which brand activity is helping deals close? These questions are ones the board already wants answered. Framing a measurement investment as the path to answering them is considerably more effective than presenting it as an analytics or infrastructure project.
