Beyond the MQL: Why ABM Teams Need Feedback Loops, Not Just Metrics
B2B marketing teams face a growing challenge: the metrics they have relied on for years no longer reflect how complex buying decisions are made. Traditional measures like the marketing qualified lead (MQL) capture activity but fail to show true buying intent across account‑level committees. As a result, many account based marketing (ABM) programmes stall or shut down despite promising early results.
The real opportunity lies in moving beyond outdated metrics and building feedback loops that connect engagement signals to pipeline and revenue. By focusing on systems that learn and improve, organisations can transform ABM from a resource‑intensive experiment into a scalable growth engine.
The Measurement Trap Holding ABM Back
Account-based marketing programmes routinely fail to scale, not because the strategy is flawed, but because teams lack the feedback mechanisms to learn and improve. Whilst marketers invest heavily in personalisation and targeting, they struggle to connect those activities to commercial outcomes in ways that inform future decisions.
This disconnect creates a familiar pattern: ABM proves successful at small scale, but expanding requires exponentially more resources. Without quality signals about what's working and why, teams resort to adding headcount rather than refining their approach. The result is programmes that plateau or, worse, get shut down entirely despite promising early results.
Karen Lloyd, host of the Spotlight on B2B Marketing podcast, has seen this play out first‑hand: “In about 2023, a lot of companies we worked with really ramped up their ABM teams. And then in 2024 and 25, they closed them down again.”
Nick Mason, who recently appeared on an episode of the Spotlight on B2B Marketing podcast, has spent years helping organisations solve this challenge. As co-founder of Turtl, a revenue-generating content platform, Nick has witnessed how the right measurement frameworks transform ABM from a resource-intensive experiment into a scalable growth engine.
The MQL Problem Everyone Acknowledges but Can't Solve
The marketing qualified lead has long outlived its usefulness, particularly in account-based approaches where buying committees average eleven people. Yet most organisations remain stuck with this metric despite recognising its limitations.
Nick observes this challenge directly in his work with clients. As he notes: "The MQL is, I wouldn't say it's alive and well. I think it's trying to be phased out, but there are various different challenges with that."
This isn't merely an academic concern. When your primary success metric captures individual form fills rather than account-level buying signals, your entire programme optimises for the wrong outcome. You chase volume over quality, mistake research activity for purchase intent and struggle to coordinate marketing and sales efforts around genuine opportunity.
The shift to account-based metrics requires more than updating dashboards. It demands rethinking how your team captures signals, what those signals indicate about buying readiness and how that intelligence flows through to action. This includes website engagement patterns, intent data from research activities and content interaction across multiple stakeholders within target accounts.
Creating Feedback Loops That Drive Improvement
The organisations achieving breakthrough results with ABM share a common characteristic: they've built systems that learn. Rather than executing campaigns and hoping for results, they've created feedback loops that continuously refine their approach based on real engagement data.
Nick describes the power of this approach through a client example: "They were able to, in a 9, 12 month period, double their win rate from 13 to 26% because they were able to put their salespeople on the right opportunities at the right times."
This improvement didn't come from more aggressive outreach or larger budgets. It came from understanding which accounts were engaging, what topics resonated and using that intelligence to prioritise sales efforts. Instead of chasing hundreds of accounts, sales teams worked from the top of an engagement-graded list, focusing energy where genuine buying interest existed.
The feedback loop extends beyond immediate conversion. When you track which content drives engagement and ultimately pipeline, you gain insight into what your next content should address. You discover which topics resonate with which segments, where messaging needs refinement and which channels deliver the best return. This creates a flywheel effect where each campaign informs and improves the next.
Establishing these loops requires infrastructure. You need systems that capture granular engagement data, technology that connects content interaction to CRM records and processes that translate signals into action. But more fundamentally, you need organisational commitment to building this capability from day one, not retrofitting it later when asked to justify results.
From Lagging Indicators to Leading Intelligence
The most sophisticated ABM teams work backwards from commercial outcomes to identify the leading indicators that predict success. This inverted approach ensures every metric connects to business impact rather than serving as vanity statistics.
Nick outlines this framework clearly: "The ultimate lagging indicator that we always encourage to get in place really early is ultimately pipeline and revenue and all of the associated metrics. You need to have the ability to track through to that."
Once pipeline and revenue tracking exists, you can determine what level and type of engagement predicts these outcomes. This might include engagement per account, engagement per contact, number of topics explored, visit frequency and depth of interaction. These leading indicators help teams understand not just whether accounts are engaging, but whether that engagement signals genuine buying intent.
The earliest metrics focus on activity: your capacity and bandwidth for outreach, number of touchpoints and whether you're discussing relevant topics. These inputs determine whether you're creating enough opportunity for engagement to occur.
This three-tier framework, activity leading to engagement leading to commercial outcomes, allows teams to diagnose problems precisely. If pipeline isn't materialising, you can trace back to find the break in the chain. Perhaps activity was insufficient, engagement didn't occur despite outreach, or engaged accounts didn't convert because sales follow-up was poorly timed or targeted.
What Can Marketing and Business Leaders Implement for Their Teams?
The insights around ABM measurement and feedback loops present significant opportunities for marketing teams to improve both performance and efficiency. These strategic implementations can transform programmes from cost centres to revenue drivers whilst positioning teams for sustainable growth:
Establish pipeline and revenue attribution from day one of any ABM programme, as retrofitting this capability later proves exceptionally difficult and often impossible. Work with revenue operations and sales leadership to ensure your marketing automation platform, CRM and content systems all capture and pass the necessary data points. This foundation allows you to justify continued investment and make data-driven decisions about resource allocation. Consider whether your current team has the technical expertise to implement this properly, or if you need to recruit specialists in marketing operations and attribution.
Build engagement grading systems that prioritise sales efforts based on account-level signals rather than individual actions, moving beyond the limitations of MQL-based approaches. This requires aggregating multiple touchpoints across buying committee members, scoring accounts based on cumulative interest and topic engagement and creating clear handoff protocols between marketing and sales. Your sales development representatives need training on how to interpret these signals and personalise outreach accordingly. This may require upskilling existing team members or bringing in professionals experienced in signal-based selling.
Create systematic feedback loops that connect campaign execution to engagement data to commercial outcomes, enabling continuous programme refinement. Schedule regular reviews where marketing and sales jointly analyse which content drives the most qualified engagement, which accounts convert at the highest rates and what patterns emerge across successful deals. Use these insights to inform your content strategy, channel selection and targeting criteria for future campaigns. This requires cross-functional collaboration and may necessitate restructuring how marketing and sales teams interact and share accountability for results.
Invest in the technology ecosystem that enables personalisation at scale whilst capturing quality signals, recognising that manual processes will prevent you from expanding programme reach. Evaluate how your intent data platforms, marketing automation, content systems and CRM integrate to create a unified view of account engagement. Identify gaps where signals are lost or handoffs fail, then prioritise closing those gaps before expanding programme scope. When scaling your ABM team, look for candidates who understand both the strategic elements of account-based approaches and the technical requirements of modern marketing technology stacks.
Karen Lloyd, February 2026
About Karen Lloyd
As the founder and director behind our recruitment approach, I bring almost 30 years of unique expertise spanning both recruitment and marketing. Having placed my first candidate in 1996, I've since built 5 start-ups, served as a Board Director for 25 years and developed recruitment strategies that work in competitive talent markets.
I'm also the host of "Spotlight on B2B Marketing", where I explore B2B marketing trends with industry leaders. My passion lies in helping global businesses grow their revenue-generating teams through strategic hiring and fractional CMO services.
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