The state of B2B tech marketing 2026

Executive summary

The defining shift of 2026 is that the B2B technology buyer no longer starts on Google. They start in an AI assistant, a peer Slack channel or a private LinkedIn DM, and by the time they reach a vendor website they have already shortlisted. Marketing teams that still treat the website as the top of the funnel are paying premium CPMs to fill a leaky bucket, while teams that have rebuilt around being cited, recommended and remembered are seeing pipeline efficiency they have not seen since 2019.

That is the thesis of this report. Below we set out five findings drawn from public data and our work running marketing for MSPs, SaaS vendors, IT services firms and SAP partners, alongside five predictions for the rest of 2026.

The five findings:

AI search is reorganising the top of the funnel faster than most B2B teams realise. Across our client base, roughly a third of net-new opportunities now reference an AI assistant somewhere in the first-touch story, and the figure was negligible two years ago.
LinkedIn Ads remains the workhorse of B2B tech demand generation, but its CPMs have repriced the funnel. The channel still works. The economics have changed and most plans have not been rebuilt around the new numbers.
Most B2B tech websites still fail the technical buyer test in the first ten seconds. The buyer is more sophisticated than the brief and the homepage rarely catches up.
SEO investment is consolidating into fewer, deeper assets. The 200-page content factory is being replaced by 30 obsessively maintained pages that earn citations in both Google and AI answers.
The “content engine” of 2024, briefs out, drafts in, ship at volume, has been replaced by tighter, sales-aligned production where every asset has a named internal user before it is written.

The thesis sentence, for anyone short of time: B2B tech buyers in 2026 have moved their first three steps off your website, and the marketing teams winning are the ones that have moved with them.

About this report

This is not a primary survey. We did not poll 500 marketers and we will not pretend we did. What follows is a synthesis of three things.

First, public data and the published research we trust. We cite HubSpot State of Marketing, Gartner CMO Spend and CIO Tech Buyer studies, Forrester B2B buyer journey research, the LinkedIn B2B Institute’s work with Les Binet and Peter Field, Bain B2B buyer behaviour reports, Demand Gen Report surveys, 6sense and Bombora intent benchmarks, Statista industry data, and reporting from Search Engine Land, Search Engine Journal and the Ahrefs and Semrush blogs. Where a figure has a public source, we name it.

Second, the patterns we see across the 30-plus B2B technology accounts we run, ranging from sub-£10m MSPs to mid-market SaaS vendors and SAP services firms. Where a number is ours, we say so explicitly with phrases like “in our client base” or “across the accounts we run”.

Third, our predictions for 2026, which are opinions and labelled as such.

If you would prefer to discuss the underlying data, get in touch.

Finding 1: AI search is reorganising the top of the funnel faster than B2B teams realise

The single biggest change in B2B tech buying behaviour over the last eighteen months is not a new channel. It is a missing one. The classic top of funnel, a buyer types a query into Google, lands on a blog post, downloads a guide, enters a nurture, has been quietly emptying out.

In its place is a conversation with an AI assistant. The buyer asks ChatGPT, Claude, Gemini, Perplexity or Copilot to summarise the vendor landscape, recommend three options, draft a comparison table and explain the trade-offs. By the time a sales conversation begins, the shortlist already exists. The vendor either appears in the AI’s answer or it does not.

What we see in our client base

Across the B2B tech accounts we run we now ask, on every discovery call we are invited to listen in on, whether the prospect used an AI assistant during research. At the start of 2025 the answer was almost always no. Through the back half of 2025 it climbed. In the first quarter of 2026 it sits at roughly one in three of the deals we see, and closer to one in two for software buyers under 40. We do not claim that as a market figure. It is what we observe across roughly 30 accounts and several hundred discovery calls a quarter.

The HubSpot 2025 State of Marketing report puts AI-assisted search adoption among B2B buyers in the same broad zone, somewhere between a quarter and a third depending on segment, and Gartner’s 2025 CIO Tech Buyer work suggests technical buyers adopt AI tools earlier than the average B2B segment. The direction of travel is settled. The question is whether your category appears in the AI’s answer.

Citations are the new rankings

If you are not appearing in AI overviews and assistant answers, you are invisible to a growing share of buyers no matter where you rank in classic search. We have written a full primer on this in our AI search optimisation primer and the AI SEO guide. The short version: the assistants prefer structured, citable, unambiguous content. They like clear definitions, comparison tables, named figures, and a discoverable author.

Three patterns we see consistently in pages that earn citations:

A sharp definition in the first 60 words. If the answer to “what is X” is buried below a hero image and a CTA, the assistant will quote a competitor.
Comparison and trade-off content with named alternatives. Pages that say “X works for these scenarios, Y works for these others” are cited far more often than pages that only sell one option.
A real author with credentials, a real publication date, and links to primary sources. The assistants are getting better at filtering out anonymous AI sludge.

What it changes about the funnel

The implication for the marketing plan is uncomfortable. Spend that previously bought top of funnel awareness through Google search ads or generic blog SEO is buying less. Spend that buys citation worthiness, original data, original opinions, named experts, comparison content, is buying more. Our ranking, across the accounts we run, of channels that are growing in influence on shortlist inclusion looks like this.

Rank	Influence on shortlist inclusion in 2026	Direction
1	Peer recommendation, including private communities	Stable, very high
2	AI assistant answers and citations	Up sharply
3	Analyst and review site presence (G2, Gartner Peer Insights)	Stable, high
4	Branded organic search	Stable
5	Non-branded organic search	Down
6	Outbound SDR	Down

If you take one thing from this finding, it is that the shortlist is being assembled before you know the deal exists. You can book a call with us about an AI search audit or read more about our AI SEO service.

Finding 2: LinkedIn Ads remains the workhorse, but its CPMs have repriced the funnel

LinkedIn Ads is still the most reliable paid channel in B2B tech. It is also more expensive than at any point we have measured. Both statements are true and most 2026 plans are still costed against 2023 numbers.

The numbers, framed honestly

We do not publish absolute CPM benchmarks because the channel varies wildly by audience definition, geography and creative. What we will say is that across our UK B2B tech book, sponsored content CPMs in target ICP audiences have risen by something in the order of 30 to 50 per cent over the last 24 months. That is consistent with what LinkedIn’s own ad load disclosures imply and with the public Q4 2025 commentary from agencies like Wpromote and Tinuiti. Statista’s 2025 B2B paid social benchmarks show a similar trend at the segment level.

What that means in practice. A campaign that in 2023 hit a £180 cost per qualified MQL through LinkedIn might now sit at £260 to £320 for the same definition of MQL. Pipeline cost per opportunity has moved less, because conversion rates have held up where the offer is sharp, but the budget envelope at the top is bigger.

What still works

Three things are working harder than ever, and three things are losing money.

What is working:

Thought-led video from a named human. 30 to 60 second talking-head pieces from a founder, CTO or principal consultant outperform polished brand films by a wide margin in our data. They also collect comments, which feed the algorithm.
Document ads with genuinely useful frameworks. Not gated whitepapers. The full document, in feed.
Conversation Ads to existing first-party audiences only. Cold conversation ads have collapsed in performance in our book over the last year.

What is not working:

Lead Gen Form ads to cold ICP audiences with a generic ebook offer. The leads are real. They are also rarely buying.
Single image ads with stock photography. Performance has fallen off a cliff and we now treat them as a control, not a workhorse.
Brand campaigns with no measurable hypothesis. The 95-5 rule from the LinkedIn B2B Institute is real, but “build brand” is not a campaign brief. We expand on this in our Paid Media guide and the deeper LinkedIn Ads B2B tech playbook.

The repricing forces a portfolio

Because the workhorse has got more expensive, single-channel paid plans look more fragile than they did. Across our client base we are seeing plans rebalance toward a portfolio. LinkedIn for ICP reach. Reddit Ads for niche technical communities, especially for developer-focused SaaS. Google Demand Gen for branded discovery beyond search. Programmatic display via 6sense or Demandbase for accounts already on the buying committee. Podcast sponsorships, often direct, for categories where the buyer listens in the car.

When clients ask whether they should “leave LinkedIn”, the answer is no, almost without exception. The question is whether LinkedIn is still doing the job you costed it to do, or whether it has been quietly demoted from sole workhorse to anchor channel. We work through that diagnostic in our guide to auditing the paid plateau, and you can request the same audit through our Paid Media service.

Finding 3: Most B2B tech websites still fail the technical buyer test in the first 10 seconds

The technical buyer is the most underestimated user in B2B marketing. They arrive on the homepage with a specific question, scan three things, and decide whether you are worth a second look. Most of the websites we audit fail that test, often before the brand team has even noticed.

The 10-second test

In every site audit we run, we put a representative buyer in front of the homepage for ten seconds and then close the laptop. We ask three questions.

What does this company do, in concrete terms.
Who is it for.
Why would I pick it over the obvious alternative.

If the answer to any of those is unclear after ten seconds, the page is failing the technical buyer. Across the audits we ran in the second half of 2025, somewhere around 70 per cent of B2B tech homepages we reviewed failed at least one of those three questions. The most common failure was question two, who is it for. The second most common was question three, why over the alternative.

Forrester’s 2024 B2B buyer journey research found something similar at the survey level. Around two thirds of B2B buyers report they “could not quickly understand” the value proposition of vendors they screened out. The technical buyer screens hard and screens fast.

Three failure patterns we see repeatedly

The same three patterns recur across MSPs, SaaS vendors and SAP partners.

First, the homepage hero is written for the founder, not the buyer. It says what the company believes about itself, not what the buyer should believe about it. We rewrite a hero an average of five to seven times before it lands. Founders almost always object to the version that wins.

Second, social proof is decorative. Logos with no context. Testimonials with no role, no firm size, no specific result. The technical buyer reads logos as decoration unless there is enough specificity to make them functional. A logo with a one-line outcome under it is worth ten without.

Third, the navigation tries to please everyone. The site map collapses if you ask “if I am a 200-person legal firm in Manchester looking for outsourced IT, which click do I make first”. We unpack the MSP version of this in why MSP websites fail to convert and the broader pattern in our Web Design guide.

What good looks like

In our experience, a homepage that converts a technical buyer has three properties that are easy to test for.

The first H1 is a concrete outcome, not a claim. “Cut SAP S/4HANA migration risk” beats “Your trusted SAP partner”.
The second screen names the buyer. “Built for finance teams in 200 to 2,000 person UK manufacturers” is more useful than “for ambitious mid-market firms”.
The third screen handles the obvious comparison. If the buyer is choosing between you and an in-house build, or between you and a named competitor, the page should answer that question without making them search for it.

If you want a fast read on whether your site passes the ten-second test, our Web Design service is where to start.

Finding 4: SEO investment is consolidating into fewer, deeper assets

Two years ago, the prevailing SEO playbook in B2B tech was volume. Brief out 200 articles. Ship them. Some will rank, some will not, the long tail will pay for itself. That playbook has stopped working in most categories we operate in, and the budget is consolidating fast.

The volume playbook is broken

There are three reasons. The first is that Google’s helpful content updates through 2024 and 2025 specifically targeted programmatic, low-effort content. The second is that AI assistants and AI overviews now sit on top of the SERP and quote a small number of sources, almost always the deepest one rather than the most numerous. The third is that the cost of producing thin content has collapsed, which means everyone is producing it, which means the differentiation is no longer in volume.

The Ahrefs blog and Search Engine Land both reported through 2025 that content velocity correlates less and less with traffic growth, and that traffic per page on sites that publish more than 10 pieces a month has been falling for two years. We see the same thing across our SEO clients. The accounts that grew traffic in 2025 published less than they did in 2023 and earned more.

What we are putting budget into

In our client base, the SEO budget mix has shifted considerably. Roughly speaking, here is how the same SEO retainer spend has been redistributed.

Activity	Share of SEO budget 2023	Share 2026	Direction
New content production	55%	30%	Down
Updates and consolidation of existing pages	10%	25%	Up
Original research, surveys, data	5%	15%	Up
Digital PR and link earning	15%	15%	Stable
Technical SEO and Core Web Vitals	10%	10%	Stable
AI search optimisation	0%	5%	New
Internal linking and topical authority	5%	n/a	Folded into updates

Those are blended figures across the SEO programmes we run, not a benchmark.

Deep assets, not volume

The pages that earn rankings, citations and pipeline in 2026 share a profile.

They are long-lived, often 18 to 36 months old, and obsessively maintained.
They contain at least one piece of original input. A survey, a benchmark, a model, an opinion, a framework with a name.
They are written by a named author with credentials, with a real bio.
They link out generously to primary sources, including competitors, when it makes the page more useful.
They are part of a topical cluster, not a standalone post.

This is exactly what AI assistants prefer to cite, and exactly what Google’s quality systems are trained to reward. We expand on the pattern in our SEO guide, and the SaaS-specific benchmarks live in our SaaS SEO benchmarks for 2026. For ranking-grade comparison content specifically, see the comparison content that ranks playbook. The service overview is on our SEO service page.

Finding 5: The “content engine” of 2024 has been replaced by tighter, sales-aligned production

Through 2023 and 2024, “content engine” became shorthand for a particular workflow. Briefs out, drafts in, ship at volume, measure traffic, retrofit a story for the board. In our experience, that engine is being dismantled in 2026 and replaced with something smaller, slower and considerably more useful.

The named-user rule

The pattern we see across the marketing teams that are growing pipeline is what we have started calling the named-user rule. Every asset, before it is written, has a named internal user. Not “the sales team”. A person. The sales engineer who is sick of explaining the same integration question. The CSM who needs a one-pager for renewal calls. The founder who is going on a podcast next week. If no one inside the business will use the asset within 30 days of publication, it does not get made.

This sounds obvious. It is not how content was commissioned in 2024. The HubSpot 2025 State of Marketing report flagged that the share of content marketers reporting “alignment with sales” as their top challenge actually rose, year on year, despite three years of conversation about it. The Demand Gen Report 2025 content preferences survey found that buyers most value content that “answers a specific question I had during evaluation”, which is the inverse of broad-reach top of funnel content.

What sales-aligned production looks like

In the engagements where we run content for B2B tech clients, the production stack now looks roughly like this.

A live list of recurring sales objections, refreshed monthly from call recordings.
A short list of “deals we lost and why”, refreshed quarterly.
A weekly 30-minute editorial standup with sales, not marketing leadership.
A publication schedule that prioritises objection-handling assets, comparison pages and customer-led case stories over generic top of funnel.
Distribution baked in. Every asset ships with a sales enablement note, a LinkedIn cut-down, an email snippet and one or two AI-search-friendly definitions.

Volume falls. Asset usefulness rises. We covered this shift in detail in our Content Marketing guide.

AI in production, not authorship

A short note on AI-assisted content, because it is the question we are asked most. Across our client base, AI is now used in some part of nearly every piece of content we ship, but almost never as the author. It is used for outline pressure-testing, for first-draft scaffolding of structured sections, for headline variants, for summarisation and for translation. It is not used to ship under a named author’s byline without significant human rewriting and fact-checking. The reason is not principle. It is performance. Pages that read as machine-written get cited less, ranked less and shared less. We unpack the difference in our piece on AI-assisted vs AI-generated content. The service is on our Content Marketing service page.

By the end of 2026 we expect at least one of the major AI assistants, most likely Perplexity given its commercial positioning, to ship a public-facing dashboard that reports the share of answers in which a given domain is cited within a topic. Bing already exposes a partial version of this through its Webmaster tools and Profound and Ahrefs are already publishing third-party estimates.

Once that data exists in a reliable form, it will move from marketing dashboard to board pack, the same way share of search did between 2018 and 2022. Marketing leaders will be asked to report citation share alongside organic traffic and pipeline contribution. We expect the first awkward board meetings inside larger B2B tech firms to happen in Q3 and Q4 2026.

The defensive version of this prediction is that, even if no major assistant ships a perfect dashboard this year, the third-party tools will be good enough that competitive citation share becomes a quoted metric in agency pitches and analyst reports. Either way, “are we being cited” stops being a niche SEO question. We expand on what to track in our AI SEO guide.

Prediction 2: Paid channel diversification stops being optional, and Reddit becomes a serious B2B channel

For most of the last decade, the honest answer to “which paid channel should we run” for a B2B tech firm was LinkedIn, with Google search as an intent layer. That is no longer enough.

We expect 2026 to be the year mid-market B2B tech firms run, on average, four to five paid channels rather than two. LinkedIn remains the anchor. Google search remains the intent layer. Programmatic via 6sense or Demandbase becomes standard for any firm doing ABM. The interesting addition is Reddit Ads, which through 2025 quietly became a serious option for developer-focused SaaS, security vendors and infrastructure firms. The audiences are dense, the CPMs are still well below LinkedIn, and the AI assistants increasingly cite Reddit threads as primary sources, which means a strong Reddit presence has a search second-order effect.

The contrarian within this prediction. We do not think TikTok becomes meaningful for B2B tech in 2026, even with the rise of B2B creators. The buying committee is not there in the volumes that justify the production cost. We will revisit this in 2027.

Prediction 3: AI-assisted production becomes the norm and “thin” listicles disappear from rankings

By the end of 2026 we expect the share of B2B tech content shipped with at least some AI involvement to pass 90 per cent. That is not a controversial number. The HubSpot 2025 State of Marketing report had it close to 70 per cent already.

The non-obvious part is what happens to the bottom half of search results. The thin listicle, the ten-tools-for-X post, the regurgitated “what is” piece, will not just rank less. It will stop being indexed in any useful way. Google’s quality systems, AI assistants and the social algorithms are converging on the same signal, which is original input plus a real author. Pages without either will lose ranking and citations together.

The implication for marketing teams. The defensive moat is not “we use AI”. Almost everyone does. The moat is original research, original opinion, named experts and structured, citable assets. In other words, exactly the assets that AI cannot produce on its own. We have written about how to tell the difference in production in our piece on AI-assisted vs AI-generated content.

Prediction 4: Server-side tracking and modelled conversions become a baseline, not an upgrade

The measurement story of 2026 is not exciting and that is the point. The combination of iOS privacy changes, the long, multi-touch B2B tech buying cycle, the slow death of third-party cookies and the rise of agentic browsing means that client-side, last-click attribution has finally stopped working well enough to defend.

We expect server-side tagging via GA4, GTM server containers, and consent-mode-aware modelled conversions to move from “advanced” to “baseline” across mid-market B2B tech firms in 2026. Gartner’s 2025 CMO Spend Survey already showed measurement and analytics as the second-fastest-growing line item in the marketing tech budget. We see the same shift in our client base, where measurement work that used to be quoted as a one-off project is now quoted as a permanent line.

The downstream effect we expect is more interesting. Once measurement is honest about modelled, multi-touch contribution, the conversation about “which channels work” gets quieter and the conversation about “which channels reinforce each other” gets louder. We have written about the long-cycle version of this in our conversion tracking guide for long sales cycles.

Prediction 5 (contrarian): “AI agents will buy from each other” is overhyped for 2026 and you should ignore it

The contrarian one. There is a thread of marketing commentary that runs roughly as follows. In the near future, AI agents will conduct B2B procurement on behalf of their human owners. Vendor selection will be machine-to-machine. Marketing will need to be optimised for agents, not humans. Therefore your 2026 plan needs an “agentic readiness” workstream.

We think this is wrong, or at least wrong on this timescale. Two reasons.

First, the actual buying committee in B2B tech is human and political. The CFO sign-off, the IT director’s preferences, the legal review and the procurement haggle are not delegating to an agent in 2026 or 2027. They might be agent-assisted. They are not agent-decided. Bain’s B2B buyer behaviour work shows the average buying committee has grown, not shrunk, and human-to-human dynamics dominate.

Second, even where agentic procurement does start to bite, it will start in low-consideration, high-volume categories. Office supplies. Cloud capacity reservations. Specific commodity SaaS line items. Not £250k-a-year MSP contracts or £1m-plus SAP migrations.

So the contrarian call. If a vendor is selling you “agentic readiness” as a 2026 line item for your B2B tech firm, push back hard. Spend the money on being cited by AI search, on sharper sales-aligned content and on measurement that actually works. Those will pay off in 2026. Agent-to-agent procurement will not.

What this means for marketing leaders

If you lead marketing in a B2B tech firm in 2026, four practical implications follow from the above.

First, treat AI search as a real channel with a real owner, not a side project. Audit which AI assistants quote you for the queries that matter, fix the citation gaps, and put a quarterly target against it. The work overlaps with SEO but is not the same work. Our AI SEO guide is a good starting point.

Second, reprice your paid plan against current CPMs and stop assuming LinkedIn alone will carry the funnel. Add a second and third paid channel before you are forced to. Audit performance against opportunity cost, not against last year’s CPM. The diagnostic is in our guide to auditing the paid plateau.

Third, give your homepage the ten-second test, in front of someone who is not in your industry. If the answer to “what does this firm do, who is it for, why over the alternative” is not unambiguous in ten seconds, fix the homepage before you fund another campaign. The cheapest pipeline gain available to most B2B tech firms in 2026 is a homepage rewrite.

Fourth, audit your content production against the named-user rule. If more than a quarter of the assets shipped in the last quarter do not have a named internal user, you are running a 2024 content engine in a 2026 market.

The teams winning in our client base are not doing more. They are doing fewer things, more deliberately, and measuring them more honestly.

Methodology

This report is a synthesis, not a primary survey. The findings draw on three sources.

External published research, cited by name in the body. Sources include HubSpot State of Marketing 2024 and 2025, Gartner CMO Spend Survey 2024 and 2025, Gartner CIO Tech Buyer studies, Forrester B2B buyer journey research, the LinkedIn B2B Institute’s work with Les Binet and Peter Field including the 95-5 rule, Bain B2B buyer behaviour reports, Demand Gen Report content preferences surveys, Statista paid social benchmarks, 6sense and Bombora intent data benchmarks, and reporting from Search Engine Land, Search Engine Journal and the Ahrefs and Semrush blogs. Where we cite a figure from these sources, we use a range consistent with their published work rather than a fabricated specific.

Agency observations from the 30-plus B2B technology accounts we run, spanning MSPs, SaaS vendors, IT services firms and SAP partners, primarily UK with some EU and US presence. Where a figure is ours we say so explicitly with phrases like “in our client base” or “across the accounts we run”. Numbers like the share of discovery calls referencing AI assistants are drawn from our internal account reviews and are estimates, not survey data.

Predictions are opinions and labelled as such. We will revisit them in the 2027 edition.

If you would like to discuss the data behind any specific finding, get in touch.

About techmarketing.agency

We are a specialist marketing agency for B2B technology firms. We run web design, SEO, AI search optimisation, paid media and content marketing for MSPs, SaaS vendors, IT services firms and SAP and ERP partners across the UK and beyond.

We publish this report annually as part of our commitment to honest, useful marketing research for the B2B tech sector. The full set of pillar guides covers web design, SEO, AI SEO, paid media and content marketing. You can learn more about us or start a conversation.