Programmatic advertising wasn’t built for B2B, and most of the programmatic ecosystem still isn’t. The auction, the cookies, the device graphs and the conversion windows were all engineered to sell to one consumer at a time. Judged against a buying committee of thirteen people, that plumbing looks like the wrong tool, so the channel gets treated as cheap remnant you buy once the LinkedIn budget runs out.
That first part of the belief is correct. The conclusion drawn from it is not. Point the same infrastructure at an account graph and an identity spine built to resolve real companies and real committee roles, and the channel that was supposedly wrong for B2B becomes the only one that can reach a full buying committee across the open internet at scale, for anyone willing to do the building.
This piece is the case for that second half: why the gap exists, what closes it, and what it is costing the media plans that have written the channel off.
New here? I’ve been building B2B programmatic platforms since 2011. I’m a co-founder of FunnelFuel, where we run advanced account-based programmatic for B2B brands. The B2B Stack is one argument a week on B2B programmatic, ABM, intent and measurement, from someone who builds and runs it rather than commentates on it. If this is your first visit, [The Buying Committee Doesn’t Live on LinkedIn] and [The 2026 Guide to B2B Programmatic Advertising] are the two to read next.
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What you’ll learn in this article:
Why programmatic’s data hierarchy stops one level too low for B2B, and what the hierarchy gap actually is
How large the buying committee has become, and why “the account” was never the right unit to plan media against
What the open web gives you at the individual URL level that LinkedIn structurally cannot
Why the data coming back out of a programmatic buy is the more valuable half of the trade, and the half most buyers ignore
Where programmatic beats the walled gardens on cost and on the committee roles LinkedIn under-indexes, and why that gap has survived a decade
What is the hierarchy gap, and why does it make programmatic look wrong for B2B?
The reasoning behind writing programmatic off isn’t unreasonable. Cookie and device graphs, individual consumer segments, one-to-many optimisation and session-based conversion windows were all designed for selling to one person at a time, so set against a sale involving a dozen stakeholders the channel looks like a segment-of-one tool bolted onto a committee-level decision.
Here is the flip. The auction infrastructure underneath, the real-time bidding, the exchange connectivity, the contextual crawling, the pacing and the optimisation, is some of the best decisioning technology in advertising. It is aimed at the wrong unit by default, and that is a very different problem from being the wrong technology.
I see the gap as a data hierarchy problem. Programmatic thrived because it targeted the end user, or really the end device as measured by a cookie footprint, and that was ideal for selling fast-moving consumer goods. What it never carried were the two levels above the device: the account, and the buying group inside it. I call the distance between those levels the hierarchy gap, and it is the whole reason the channel underperforms for B2B out of the box. The moment you can transpose account and buying group into the auction, and carry them through targeting, pacing, optimisation and reporting, you have weaponised some of the best optimisation AI in the industry to work for the buying group within an account currency. Same pipes, different channel.
How big is the committee you’re actually planning against?
Gartner’s longstanding figure put the typical buying group for a complex B2B purchase at six to ten stakeholders, up from 5.4 when CEB measured it in 2015. Forrester’s State of Business Buying, 2026, drawn from a survey of nearly 18,000 business buyers, now puts the typical decision at 13 internal stakeholders and nine external influencers, and finds the group doubles, from seven to 14, when the purchase includes generative AI features.
The window has moved as well. 6sense’s 2026 Global B2B Buyer Experience Report, published this month from a survey of 4,611 recent buyers, has buying groups spending roughly 60% of a 10.3-month cycle in the selection phase before anyone contacts a seller. By the time the first call happens the group has a favourite, and that vendor wins 82% of the time. A vendor that misses the initial shortlist has less than a one-in-ten chance of winning.
So the people a vendor needs to reach, and the window in which they can be reached, have both expanded and moved earlier, largely out of sight of the channels built around a form fill or a sales call. It also means “the account” was never the right unit to plan media against. The committee is, and a committee of thirteen spread across procurement, security, legal, technical evaluation and the executive sponsor is not a group any single channel reaches on its own.
Those six-to-twenty person clusters, which need targeting in unison rather than in isolation, are the precise gap I have spent millions of dollars engineering to close.
This is where an account graph, tying together tens of millions of businesses, their firmographics, their technology stack, their inferred size and revenue, against an identity spine that makes the individual committee member targetable, stops being a nice-to-have and becomes the precondition for doing this properly. Without it, “reach the buying committee” is a slogan. With it, it is a targeting spec, and it is the specific piece of infrastructure the B2C version of programmatic was never built to include.
If this is the gap in your media plan, the rest of the piece is about what closes it. One argument like this lands every week:
What does the open web give you that LinkedIn structurally can’t?
Traditional programmatic formats, display, video and native delivered against premium content sites and apps, come with one advantage that gets massively underrated: the full URL of the page carrying the ad, both as a targetable signal going in and a reportable one coming out. That lets a business crawl and analyse the page itself, its text, its imagery, its video and audio, and understand semantically what it is actually about, not just which segment the visitor supposedly belongs to.
It is easy to fall into the fallacy of believing the whole value sits in what I call apex-fit pages, the ones where a committee member is doing visible, deep research. Those pages are rarer than the pitch decks imply, and getting rarer. SparkToro’s 2026 study found 68% of US Google searches ended without a click in the first four months of this year, up from 49% in 2019, as AI Overviews absorb the queries that used to end in a page visit. The UK figure is higher still, at 69.5%.
However, rarer is not rare, and rare does not mean never. The open web still carries an enormous footprint of contextually relevant page views. Every published estimate of daily programmatic bid volume disagrees with the next by an order of magnitude, depending on whose infrastructure is being counted, but even the conservative end dwarfs total impression volume across every walled garden combined.
That is the opening. While budget keeps piling into Facebook, Instagram, Reddit and LinkedIn, the open programmatic ecosystem remains the only channel that can, at scale and with real ad tech behind it, go and find the pages where your committee’s research is happening, upstream of the point where they know they are running a formal process at all. That is the chance to build brand memory inside the selection phase 6sense describes, to form your own view of intent rather than renting someone else’s, and to align a brand contextually with what a prospect is actually reading, whether that is a technical deep-dive or a sponsorship context, a company backing Formula One and then buying against the content a fan of the sport is reading.
If someone on your team still files programmatic under “remnant”, this is the section to forward them.
Why is the data coming back the more valuable half of the trade?
The placement is only half the trade, and it is the only half most buyers seem to value.
The depth of data returned from a programmatic buy, the raw event logs and bid-level detail sitting behind platforms like The Trade Desk, isn’t matched by anything a walled garden reports back. Tie that observable signal to the right account graph and a media buy turns into a data asset: knowledge of which named accounts, and ideally which individuals within them, engaged with which contextually aligned placements.
That is an underused opportunity in its own right, because it lets a B2B marketer build a proprietary read on intent rather than depending entirely on third-party intent providers whose methodology is, to varying degrees, a black box. Feed that signal into your own model and you can push it back out into every other channel you run: sync it against YouTube buys, sync it against social, use it to prioritise content syndication, and let your own observed behaviour, not a vendor’s inferred score, set the plan.
The same principle extends to owned-property signal. An individual mobile ID, IP address or cookie behind a visit to your own site or a partner’s, tied back to a named account and ideally a named committee member, is recognisable well before that person raises a hand. Put together, that is the 360-degree loop the B2C version of this channel was never designed to close, and that most B2B media plans still don’t.
The placement is what you paid for. The data coming back is what you were actually buying.
Where does programmatic beat the walled gardens, and where doesn’t it?
LinkedIn earns its premium. It reaches named accounts and named individuals with precision, and its reporting is good. But it is expensive, and the 2026 benchmarks show it: Metadata’s benchmark across 138 B2B advertisers’ 2025 spend averaged a $63 CPM, and tech and IT audiences commonly run $35 to $75, higher again for senior or C-suite targeting.
Open-web programmatic display trades at a fraction of that, and the data which transforms a B2C generalist impression into a B2B one is what changes the economics, not LinkedIn’s pricing structure.
Cost is one thing. The more serious problem is coverage. LinkedIn structurally under-indexes on exactly the roles that don’t spend their working day in the feed: technical evaluators, legal, procurement, security. These are people who are central to whether a deal closes, and who are considerably easier to find in a technically aligned podcast or a premium trade publication than in a LinkedIn auction built around front-of-house job titles. Forrester’s finding that procurement now sits in the decision-maker seat in more than half of buying cycles makes that coverage problem harder to ignore.
That is the blunt version of the coverage argument. LinkedIn is strong where it is strong. Programmatic, built out properly, rounds out the committee LinkedIn was never built to reach, at a materially lower cost per impression, with a deeper and more individually attributable signal coming back. Put those facts together and the case stops being a nice-to-have and becomes close to a cost-of-capital one: less waste, cheaper reach and deeper penetration into a wider committee, all at once.
Why hasn’t B2B fixed this already?
If the case is this strong, the obvious question is why B2B programmatic spend has stayed this underweight for a decade. Surely not every major vendor has missed the memo?
The answer is infrastructure, not appetite. Purpose-built B2B programmatic capability, anchored to account-level data pipelines that can target and then report and attribute all the way through to a website visit, hasn’t existed as a category until recently. Most of the ecosystem is still running the B2C version underneath a B2B media plan and calling it done. This is the specific gap we built FunnelFuel to close, and it has taken real investment, not a repackaged consumer DSP with a B2B label stuck on it, to make the targeting-to-attribution loop actually close.
It would be a mistake, though, to assume the big B2B tech vendors aren’t materially running B2B programmatic. Individual vendors we know and work with spend tens of millions of dollars a year on it. The structural miss sits outside that land of giants, in the mid-market and the long tail of enterprise that makes up a huge chunk of the B2B industry. That is also where the opportunity still stands for anyone willing to bring in the expertise, whether built in-house over time or borrowed while the programme stands up.
The position
Programmatic was built for B2C. On its own, unmodified, it is exactly the channel most marketers still think it is: cheap filler, a segment-of-one tool bolted onto a committee-level sale, easy to deprioritise next budget cycle. Rebuilt on an account graph and an identity spine that can resolve a real buying committee, the same auction gives you committee-level targeting an account list alone doesn’t, contextual reach LinkedIn structurally can’t replicate, a deeper and more attributable data return than any walled garden hands back, and a materially better cost basis for reaching the parts of the committee that never open LinkedIn.
The hierarchy gap between those two versions of the same channel is, in my view, one of the more expensive things sitting inside a lot of 2026 media plans heading into 2027. So here is the question I’d put to anyone still running programmatic as an afterthought: if your buyers’ shortlist is formed in the first six months of a ten-month cycle, before your sales team hears about it, and the channel was never built to reach that committee out of the box, what is actually in your plan to close that gap, and what is it costing you that it isn’t?
One argument like this, every week. Subscribers also get the Subscribers’ Toolkit, which holds the free report and the discount code for the Playbook below.
If you want to go further, Segment vs Signal is how to run programmatic against the whole committee, and Your Media Vendors Are Marking Their Own Homework is the piece on checking the data that comes back.
Reaching the committee on the open web is half the job. The other half is mapping the questions they ask ChatGPT, Gemini or Perplexity, auditing the answers, and using paid media to feed them. That is what The Advanced B2B AI Discovery Playbook is for. I built it to run inside Claude with very little manual work, and it is the companion to everything above: this piece gets you in front of the committee, the Playbook tells you what that committee is already being told about you.
Is your buying committee bigger than your media plan? If this is a live problem for you, I’m happy to talk it through. FunnelFuel runs three ways: as a full managed service, as a licensed signal product inside your own stack, or as a bespoke fit around what your in-house team already has.
Three ways to reach me: connect on LinkedIn, message me on Substack, or email mike@funnelfuel.io. No pitch attached, no obligation.