Read time: 4 minutes
Ask most B2B marketing teams where their pipeline problems come from and the answer is almost always the same: not enough leads. But that's rarely the real issue. The real issue is that teams are spending budget, time, and sales capacity on accounts that were never going to buy, while the ones that are genuinely in-market slip through unnoticed.
This isn't a volume problem. It's a prioritization problem. And intent signals combined with buyer intelligence are how you fix it.
The hidden cost of poor targeting
When your targeting is built primarily on firmographics — company size, industry, job title — you're making educated guesses about who might be in-market. And some of those guesses will be right. But a significant portion of your budget is being absorbed by accounts that look right on paper but have no active buying intent.
The knock-on effects compound quickly: MQL volumes inflate while conversion rates drop, sales teams lose confidence in marketing-generated leads, and the pressure mounts to generate more volume to compensate. It's a cycle that costs more with every turn.
Our B2B Buyer Intelligence Research shows that 17% already cite reaching the right accounts as a core demand generation challenge. But the issue isn't access, it's precision. The accounts are out there. The question is: which ones deserve your attention right now?
Why intent data alone isn't enough
Intent data was supposed to solve this. And to its credit, it did move the conversation forward: 98% of marketers now consider it fundamental to demand generation. But intent data has a fundamental ceiling.
It tends to surface researchers, not decision-makers. It favours content-rich industries where signals are abundant. In environments where teams operate via VPNs, a single loose signal can be attributed to an entire organization, inflating its significance and sending your targeting in the wrong direction. And it offers a snapshot, not a story: a momentary picture rather than a view of where an account actually sits in its buying journey.
Meanwhile, B2B buying has grown dramatically more complex. Decisions now involve anywhere from 5 to 13 people and the average process runs to 10.1 months. Buying groups are cross-functional, non-linear, and prone to stalling. They revisit earlier stages and move at their own pace rather than following a tidy funnel. Intent data wasn't built for this level of complexity.
Recommended reading: 5 reasons your lead quality is bad (and how human verification fixes it)
What buyer intelligence adds to the picture
Buyer intelligence goes further. Rather than surfacing a signal and leaving you to interpret it, it gives you the context to act on it with confidence. It operates at three levels:
- Account-level intelligence: what's happening across an entire organisation, not just an individual contact.
- Buyer-group visibility: insight into how the full buying group is moving, not just the person who clicked an ad.
- Contact-level targeting: precision for individual stakeholders combined with broad reach across the account.
This combination tells you not just what is happening, but why and, crucially, who you should prioritize right now versus who can wait.
Recommended reading: Inside the buying group: How to market to every stakeholder
Prioritization in practice
When intent signals and buyer intelligence are combined, the output is a clear, evidence-based prioritization model. Accounts showing demonstrable, solution-level intent rise to the top. Low-propensity accounts are deprioritized, not ignored, just not consuming your best budget and your sales team's most valuable time.
The practical results are measurable:
- Engagement rates improve (compared to purely firmographic approaches).
- MQL quality increases, which means sales teams regain confidence in the accounts they're receiving.
- Movement from first touch to meaningful engagement accelerates because you're starting the conversation with accounts that are already primed for it.
Predictive analytics takes this further still, using patterns in behaviour to forecast which accounts are likely to progress, rather than just reacting to signals once they appear. With this kind of visibility, you can tier accounts by readiness and match your activation to where they actually are, rather than where you hope they might be.
Recommended reading: How to build a target account list that actually works
The shift worth making
The move from volume-based targeting to intelligence-driven prioritization isn't just a tactical adjustment. It changes the relationship between marketing and sales. It changes how you measure success: shifting from MQL count to MQL quality, from spend per lead to revenue influence. And it changes the conversation you're able to have with the business about what demand generation is actually delivering.
Lead volume will always feel like progress. But if the accounts behind that volume aren't in-market, you're spending to stand still. Buyer intelligence changes the equation, giving you the confidence to focus where it counts, and the evidence to prove why.
