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Introduction
In 1975, Kodak built the world’s first digital camera. But their current revenue depended on film sales. Rather than threaten that model, they shelved the innovation — and missed the future.
Most B2B marketing teams find themselves in a similar position today.
For over a decade, we’ve optimized marketing for efficiency and volume of MQLs produced — tracking MQLs, lead scores, and conversion rates like gospel. We built lead factories and still measure them using assembly-line KPIs. We think of this as the industrialization of B2B marketing.
Data from our buyer experience research clearly show that buyers have opted out of this industrialized approach. They are reluctant to complete our forms, remain anonymous as long as possible, and rarely respond when our BDRs attempt to to reach them. The industrialize, MQL factory approach to B2B has alienated the very buyers we are trying to attract and engage.
We know from the research that buyers have opted out of being funnel fodder. Instead, they build short lists and vet options on their own and only engage with vendors who’ve earned it.
We also know that a person who fills out a form isn’t necessarily in-market — or that you’re being considered. Conversely, buying groups that have not become leads for you may very well be evaluating you against your competitors.
Marketing’s job isn’t to hand off dead-end leads. It is to earn early inclusion in short lists and build preference with buying groups — well before Sales gets involved.
So, this report asks a simple question:
Have our metrics evolved to match this reality?
To find out, we surveyed over 600 B2B marketers across industries, company sizes, and go-to-market strategies. We examined ABM and demand gen teams, attribution models, compensation plans, and board-level reporting.
Three years of data tell a consistent story:
Marketing strategy may be evolving, but measurement remains stuck in the past.
Across nearly every finding, the same pattern emerges: modern approaches like ABM are being layered on top of lead-centric infrastructure. Teams say they’ve moved on from MQLs, but MQLs still drive reporting, compensation, and perceived performance.
If marketing wants to claim strategic relevance, it has to measure like it. That means moving beyond sourced/influenced labels, dropping vanity metrics, and aligning KPIs to how buying actually works.
Otherwise, like Kodak, we risk perfecting the wrong model—until it is too late to pivot.
Tracking Performance: What Marketing Teams Measure, Report, and Incentivize
ABM Adoption Is Widespread — but Possibly Overstated
B2B marketing has changed. Or so the strategy decks say.
A decade ago, SiriusDecisions found that 20% of B2B organizations had an ABM program in place. Today, that number has grown to 80%. On the surface, that seems to signal a near-universal move away from leads and toward buying groups and accounts. But widespread adoption doesn’t guarantee depth or consistency in execution.
While there are undoubtedly organizations that have built mature and successful ABM programs, much of the data in this report suggests that many ABMers are still being measured against traditional lead-based KPIs. In other words, simply having an ABM program does not indicate that a marketing organization has matured to address how buying really works. A substantial share of teams are either in transition or have stalled in their efforts.
(Just) Talking the Talk
We have also discovered that there is also a smaller segment of marketers whose responses reflect more aspiration than reality— socially desirable responders. These individuals, prone to a well-documented survey bias, tend to answer in ways they believe will be viewed favorably. In this case, that meant being more likely to say they have an ABM program, and far more likely to report strong financial performance. In other words, the 80% ABM adoption rate we found is padded by a small but meaningful group of “Inflators” whose answers likely reflect intent or ambition more than actual practice.
Even Those With the Smallest Deal Sizes Report Relatively High ABM Adoption
To get a better read on how teams perceive their own maturity, we drew on findings from a separate study conducted with Sloane Staffing, where nearly 200 B2B practitioners in ABM or ABX roles were asked to assess the state of their programs:
- 51% described their ABM program as “somewhat developed”
- 27% were just getting started
- 15% said they had a well-established ABM program
- Just 4% said their program was fully scaled across the organization.
Budget allocation offers yet another indicator of maturity. Those just getting started or “somewhat developed” devote an average of 26% of their marketing budgets to ABM. That rises to 34% among “well-established” programs and jumps to 66% among the small group that describe themselves as fully scaled.
Legacy Metrics Are Holding ABM Back
Early ABM simply rerouted the MQL machinery toward target accounts.
Nearly half of ABM adopters still measure success by MQLs, even from non-target accounts. That is not strategic alignment; it is legacy habit. True post-industrial ABM should prioritize progress through the buying journey and business outcomes—not arbitrary qualification thresholds. Yet only a third track pipeline from target accounts, and even fewer measure revenue impact.
Until we shed MQL-era thinking and retool around intent and influence, we’re just putting new labels on decrepit machines.
Most Tracked
- Marketing Qualified Accounts from ABM/Target Accounts – 49%
- Marketing Qualified Leads from non-target accounts – 44%
Middle of the Pack
- Opportunities from ABM/Target Accounts – 35%
- Pipeline from ABM/Target Accounts – 33%
- Closed-won deals from ABM/Target Accounts – 22% or fewer
Bottom of the List
- Non-MQL Leads from non-target accounts – 13%
- Non-MQL Leads from target accounts – 11%.
What Gets Reported Up: Progress Measured in the Wrong Currency
If you want to know what a company values, look at what gets reported to up the management chain.
In B2B marketing, there’s finally some movement: more than a third (39%) of ABM programs report MQAs to the board. That is notable. MQAs are, at least in theory, more aligned with account-based strategies than MQLs ever were.
So that is good news.
The bad news?
- Opportunities from target accounts: reported by just 21%
- Pipeline from target accounts: 22%
- Closed-won revenue: a mere 13%.
Marketing is not reporting outcome metrics. But, we can be certain that sales is. In other words, outcome metrics—pipeline and revenue—remain the domain of sales. As long as these outcome metrics remain “sales-only” territory, marketing remains the junior partner in revenue production.
Company Size and What Gets Reported Up
In small companies, board members tend to see everything—often the same reports as senior leadership.
But as company size grows, reporting narrows:
- Senior leaders see less detail
- Boards often get a single number from marketing – usually MQAs.
The larger and more complex the company, the thinner the marketing story that is told at the top. This is to be expected when organizations are operating established processes. However, as we have seen, most organizations are still in transition – in limbo between the old industrial, lead-focused way of working and the more modern account- and buying-group centric models.
Compensation: Strategy Modernized, Rewards Stuck in the Past
How ABMers Are Paid:
- 40% say MQAs are tied to the variable compensation
- 28% say none of their ABM metrics influence compensation
- 65% tie just 1–3 metrics to pay—mostly MQAs (40%) or MQLs (31%)
- Only 7% tie 4+ metrics to incentives
That 40% of marketers have MQAs tied to the variable compensation is a great step forward. However, there is a substantial drop-off when it comes to opportunities and pipeline – more revenue-adjacent metrics.
Attribution
Attribution Practices: Broad Adoption – but Shaky Foundations
Everyone does attribution. Almost no one does it well.
That is the headline from three years of data. Despite near-universal adoption of attribution models—92% of ABM teams and 68% of legacy teams say they use one—the foundation underneath is still shaky. The models in use may be more complex than in the past, but complexity isn’t the same as insight.
What We Mean by Attribution
Marketers generally track two kinds:
- Sourced attribution: “This deal started because of us.”
- Influenced attribution: “We touched that deal at some point.”
Both rely on an optimistic assumption: that we can identify a meaningful starting point or moment of influence in buying journeys that are anonymous, messy, and fragmented.
The Mirage of Multi-Touch
The most popular model is multi-touch attribution, which is used by:
- 58% of ABM organizations
- 60% of non-ABM organizations
That may sound like progress. Adoption is up substantially from several years ago. It is not, however, progress.
Multi-touch usually means crediting three or four visible interactions. That is still a rounding error on the actual number of interactions buying groups have with vendors. A typical buying group of 11 people generate 150–200 digital touchpoints per vendor. Multi-touch isn’t measuring influence. It is cherry-picking.
Attribution Model% Using It (ABM)% Using It (Non-ABM)What It Actually DoesReality CheckMulti-Touch58%60%Credits a handful of visible touchpointsCandy for dashboardsFirst Touch22%38%Credits the first detectable interactionRearview logicLast Touch31%19%Credits the last thing before salesThe “race finish” fallacyStatistical Modeling20%18%Analyzes all activity patterns to estimate real impactActual measurementFigure 9. Attribution reporting has shifted from single-touch methods to multi-touch methods. This is not a meaningful improvement.
The Least-Used Model Is the Only One That Works
Just 20% of ABM programs and 18% of legacy teams use statistical attribution — the only model that can account for the full pattern of interactions over time. That is because it is harder to implement and harder to explain. But it is the only approach grounded in actual impact.
Until statistical attribution becomes the default, attribution will remain what it is today: a story we tell ourselves to justify the intuition- and preference-based decision-making.
Sourced vs. Influenced: Attribution’s Mirror Images
If sourcing is about origin stories for deals, influence is about plot twists. And, both are flawed—but in different ways.
- Sourced Revenue: Marketing claims credit because a deal started with a marketing activity.
- Influenced Revenue: Marketing claims credit because a tactic touched a deal at some point.
Neither model can reliably track what caused a buying group to act—only that marketing was visible somewhere along the way. The logic assumes cause where there’s often only coincidence.
We know from research on how buyers buy that most buyers enter a journey with prior experience with brands. And we know that only 3 in 10 buying group members of a buying group that will buy from you will fill in a form. Most of those evaluating you will stay anonymous. There’s no evidence that the person or the moment who first fills out a form is special or decisive in any way.
The origin of the opportunity – why you got on the list at all – is almost certainly not the first time you saw a form fill.
