B2B demand generation is having a genuinely good year, and the clearest sign is that marketing and sales have started arguing about the same number. Demand Gen Report’s 2026 benchmark, drawn from more than 250 marketing and go-to-market leaders, describes what it calls a lead quality reset: a deliberate move away from counting marketing qualified leads and towards measuring pipeline created, opportunity conversion and win rate. Around 73 per cent of B2B organisations have restructured their pipeline approach in the past eighteen months. A change that widespread, arriving that quickly, usually means teams have found something that works.
The evidence backs them up. Demandbase’s State of ABM 2026, built from 1,452 customer tenants covering 429,634 advertising campaigns, 38 million marketing activities and 9.7 million sales interactions, found that organisations working buying groups rather than individual leads achieve up to two to three times higher win rates. The opportunity here is larger than a metrics tidy-up. Teams making this move are getting a more honest read on demand, a shorter path from interest to opportunity, and a revenue conversation that finance can actually follow.
What revenue operations is accountable for now
Revenue operations is the function that unifies the systems, data and processes behind marketing, sales and customer success, so that a company can plan, execute and measure revenue as one motion rather than three. In practice a RevOps team owns the CRM data model, the routing and qualification rules, the forecast, and the reporting layer that leadership trusts. What changed in 2026 is the scoreboard. Where RevOps was once judged on the volume of leads passed to sales, it is now judged on pipeline created, conversion between stages and win rate. That is a promotion in everything but title, and the tooling to earn it has arrived at the same time.
The structural shift behind that is worth noting. Survey work published this year puts the share of B2B companies with a dedicated revenue operations function at 78 per cent, up from 48 per cent in 2023, and the VP of Revenue Operations title has grown sharply over the past eighteen months. Companies with a formal RevOps function report materially faster revenue growth than those without one. The function stopped being a reporting desk and became the place where the commercial model is designed, which is precisely why the metrics it reports on have been rewritten.
For anyone running this function today, the practical gain is leverage. When the number you are accountable for is pipeline rather than leads, you get a legitimate say in targeting, qualification thresholds, territory design and follow-up standards, because all four move the number. That is a much better position than being handed a volume target and asked to explain the shortfall afterwards.
What is pipeline velocity, and why has it become the headline number?
Pipeline velocity measures how much revenue moves through your pipeline in a given period. The standard calculation multiplies the number of qualified opportunities by average deal value and win rate, then divides by the average sales cycle length in days. The result is a figure expressed as revenue per day, which makes it unusually useful. It shows whether a quarter improved because more deals entered, because deals got larger, because the team closed a higher share of them, or because the cycle shortened. Lead volume can only answer the first of those questions, and frequently answers it misleadingly.
The reason revenue leaders have taken to it is that every input is something a team can run an experiment against. Tightening the definition of a qualified opportunity usually lifts win rate even as opportunity count falls, and the velocity figure tells you within a quarter whether the trade was worth making. Shaving five days off a ninety day cycle is worth about the same as a five per cent lift in win rate, and is often easier to achieve through better handover discipline and faster quoting. Marketing, sales and finance can each point at a specific input and say what they intend to do about it.
Buying groups are outperforming individual leads by a wide margin
The most useful finding in this year’s data concerns how buyers actually appear. Demandbase puts a typical B2B buying group at 13 to 17 stakeholders, and organisations that engage the group rather than the individual see up to two to three times higher win rates. Engagement depth compounds the effect: buying groups receiving 180 to 190 touches across the account reach a 94 per cent conversion rate. Two to three buying groups per product emerges as the sweet spot, with win rates peaking there before operational complexity starts to cost more than it returns.
This explains why the MQL served teams so imperfectly for so long. The model asked a single downloaded whitepaper to stand in for a committee of fifteen people, then routed the whole account on the strength of whoever happened to fill in the form first. The buying group model does not require anyone to guess. It scores the account on the collective pattern of engagement, which is both a more accurate signal and a far more defensible one when a deal is reviewed.
The encouraging part is that the platforms have caught up. Salesforce, HubSpot and Dynamics 365 all now support account-level and buying-group-level engagement natively, rather than requiring a custom object and a quarterly reconciliation script. What used to be an enterprise ABM project that took two quarters to stand up is now largely a configuration exercise on top of a CRM you already own.
Why CRM data quality is where the conversion gains show up
CRM data quality matters because every downstream revenue decision inherits it. Routing, scoring, forecasting and reporting all read from the same account and contact records, so a duplicated company or an unmapped domain does not cause one error, it causes the same error repeatedly and invisibly. The 2026 data quantifies this clearly. Teams with connected CRM, marketing automation and predictive models achieve conversion from qualified account to pipeline of 22 per cent or better, against a 14 per cent baseline for less integrated teams. Mature programmes post a median of 22.33 per cent versus 14.19 per cent for the rest.
That is roughly eight percentage points, or more than half again as much pipeline from the same demand. It is also the most attractive number in the whole dataset, because closing that gap does not require new budget, new headcount or a new platform. It requires the account records to be deduplicated, the domains to be mapped correctly, and the marketing automation platform and the CRM to agree on what an account is.
That work is ordinary and it pays more than once. A tidy account hierarchy improves routing accuracy, makes territory planning defensible, cleans up the forecast roll-up and removes most of the manual reconciliation that RevOps teams do before every pipeline review. Teams that treat it as foundation rather than housekeeping tend to find the conversion lift arrives faster than they expected, because the integration was rarely the hard part.
How to align sales and marketing around one pipeline number
Aligning sales and marketing starts with a shared definition rather than a shared meeting. Agree a single written definition of a qualified account that both teams sign, covering firmographic fit, buying group coverage and engagement threshold. Give both teams the same pipeline target for the period instead of separate lead and quota targets. Set a mutual service level on follow-up, commonly a response inside one working day, and measure both sides against it. Then report from one dashboard that shows pipeline created, stage conversion and win rate by source, so neither team can maintain a private version of the truth.
The reason this works better now than it did five years ago is that the shared number is finally one both functions can influence. Under the MQL model, marketing controlled volume and sales controlled conversion, and each could reasonably blame the other. Under a pipeline model built on buying groups, marketing influences coverage and engagement depth while sales influences progression and cycle length, and both show up in the same calculation. Alignment becomes a consequence of the measurement rather than something you have to schedule.
How to measure the return on this change
Measuring the return on a CRM or RevOps investment is more straightforward than it is often made to sound. Take a clean baseline before you change anything, covering conversion from qualified account to pipeline, average sales cycle length, win rate and the hours your team spends each month reconciling data by hand. Re-measure the same four figures one and two quarters later. Convert the conversion and win rate movements into incremental pipeline at your current average deal value, add the recovered hours at a loaded cost, and compare that against the implementation and licence cost. Most teams find the data work pays back inside two quarters, because the gains land on volume that already exists.
It is worth setting the baseline before the project starts rather than reconstructing it afterwards, and worth keeping the measurement window long enough to cover a full sales cycle. Teams that do both end up with a business case they can reuse for the next phase, which is usually how a successful data project turns into a funded programme.
The Sirocco perspective
We work across Salesforce, HubSpot and Dynamics 365, and we are glad to see buying group and account-level engagement shipping as standard capability on all three rather than as a premium add-on. It removes the argument our clients used to have about whether the model was affordable, and moves the conversation to where it belongs, which is whether the account data underneath it is ready to carry the weight.
Our experience is that the teams getting the most from this shift do the unglamorous part first. They fix the account hierarchy, agree one definition of a qualified account across both functions, and instrument pipeline velocity before they touch the scoring model. That sequence takes a few weeks rather than a few quarters, and it is what turns an eight point conversion gap into pipeline rather than into a slide. Being independent of the vendors means we can tell you when your existing platform already does what you need, which in this particular case it very often does.
This is a good moment to make the change. The benchmark data is public, the platform support is native, and the work required is the same work that improves routing, forecasting and reporting regardless. If you would like to talk through what the shift looks like on your stack, schedule a consultation and we will map it out with you.
Get in Touch
If you are moving from lead volume to buying groups and pipeline velocity, and want the account data in Salesforce, HubSpot or Dynamics 365 ready to support it from the start, tell us where you are and we will take it from there.
