The President's Problem: Faster Shortlists, Slower Decisions — A Leadership Playbook for AI-Led B2B Buying

              

Every company I’ve worked at, and according to research also, most companies are struggling with this same issue – falling conversion rates, and higher costs per lead. Those two powerful forces can absolutely pull a campaign apart, so I think it is worth exploring them in detail.

If I can break these two problems down into what’s always been a factor, and what is changing, I believe that will be the simplest way of getting to the root of the issue. 

In addition, I will demonstrate what actions you can take to alleviate these problems, and even, capitalize on them; to ensure that you are riding the wave of the major changes that are happening, rather than fighting upstream against them.

First off, why are high quality leads getting harder to deliver? There’s a myriad of reasons for this. One of the key problems is the constant war for people’s attention. Back in the day, there used to be a few key ad channels, and a sure fire way of delivering from them; Create new prospects with email, and google and linkedin ads. Then the Sales Development Representative would close out the first meeting, and pass the promising ones to sales to seal the deal.

I’m sure you can see the problem here; Nowadays there’s a plethora of platforms and channels that your prospects are scouring for information, as well as connecting with like-minded communities on: from Quora for in-depth b2b discussions, to review sites like G2, and Truspilot, to video channels, Podcasts (every thought leader seems to have one now), not to mention, Reddit, X, Facebook, Meta, Instagram/Tiktok (Yes, B2B companies are really using both these days, I’ve worked at some of them). 

Then there’s private communities like Whatsapp, Skool, Linkedin groups, Slack, Circle (this is a big one in Cybersecurity), Shopify community, AWS, Hubspot, Salesforce Trailblazer, GitHub discussions, blogs (like mine) and other niche channels.

Audiences have become ultra segmented (not in the traditional way by job title, country, company size or sector) but by the way they find and absorb information. And that is before we’ve even mentioned AI. 

And of course, the fact that it's harder to reach prospects by phone these days doesn't help either.

What can you do about this problem? I would use both feeback, qualitative research, and data, to discover what are the five or six most powerful channels (in terms of how your attribution model shows they drive sales revenue) and double down on them.

Secondly, I would ensure that you create content that is feeding directly into AI search engines. There’s plenty of research to show that you can accomplish this fairly simply and effectively: For B2B, AI will draw from key channels like Quora, reddit, Wikipedia, Linkedin, and surprisingly, your own guides, if they are well written, authoritative, and provide real answers. 

On the one hand, b2b content teams seem to often lack the experience or understanding of their audience to double down on these opportunities. I suggest spending time with prospects to understand what their business challenges are, and even what they do and how they spend their time. 9 times out of 10, content is too focused on what our company does, and who we are ‘Whizzletech is the leader in fintech solutions (it’s clearly not) and we want to make the world a better place (also hard to prove and unlikely, I think you just want to make money, right?)’

Where you can really make a positive impact and drive sales it to understand. What is their actual business objective? — revenue, growth, cost reduction, efficiency, market share, retention, etc. What would get them fired? (‘What keeps you up at night?) What would get them promoted? (A quantum leap in the efficiency with which they do their job). You get the picture! Ultimately you are also looking to find the prospects who are BANT qualitied, and who have a 9 or ideally 10/10 problem. Obviously you will struggle with those who think your solution is merely ‘a nice to have’. But companies have driven themselves out of existence trying to fool themselves into believing a lot of buyers with 5 or 6 out of ten pain points, will buy in this quarter.

Focus on the prospects who have the greatest need of your solution, when they are in market (only 5% of them will be at any one time), with a targeted personalised message (that solves their pain), in the channels that they operate in. 

Finally, I will add that AI is creating a massive opportunity here. It is like the first years of Google when only 5 or 10% of the market understood and capitalised on the changes, by running those first basic advertisements. If you can crack the AI code now, and keep innovating, you will likely reap a massive growing annual harvest from it. 

For those who manage to harness AI, they will cut down on the lengthening b2b sales cycle, and improve their conversion rates significantly. AI is condensing the vendor selection process. If you can categorically position yourself as the leader, and continue to persuade, your prospect won’t be felled by the two biggest reasons why they end up as closed lost (Insufficient Budget, and No decision).

How you get there is another challenge in itself. Gartner's newest CMO Spend Survey has a chart that should worry anyone setting a marketing budget this year. Marketing spend as a percent of revenue sits at 7.8 percent in 2026, up from 7.7 percent last year. Functionally flat. That number is also 18 percent lower than it was four years ago.

Here's what makes that flat line matter: 70 percent of CMOs in the same survey say becoming an AI leader is critical to their 2026 plan. Only 30 percent say their organization is actually ready to scale AI capabilities. Fifty six percent say their budget isn't enough to deliver on this year's strategy at all. Perhaps your best bet is to focus on those who are most passionate about solving these problems – who are prepared to take well calculated risks to achieve your goals?

Certainly it seems like with diminishing or flatlining budgets, and exponentially growing demands, some radical resets are necessary to accomplish CMO goals in the next five years.

Now that we’ve covered off on the lead generation challenges (making sure you have the right ‘raw materials’ to pass to your sales team), let’s move on to the biggest conundrum today; why are lead to sales conversion rates falling, and sales cycles lengthening at the decision stage?

Again, AI is partly to blame for this trend. And those who crack the AI code will also be in the prime position to drive higher revenue, with stronger conversion rates, and more efficient sales funnels. 

The best way I can describe the change is this: the funnel has been pinched at the top and stretched at the bottom. AI has collapsed discovery, comparison and elimination into a single step — prompt, compare, recommend — and a shortlist now forms fast, often before a seller ever hears from the buyer. You would think that would make everything faster. It hasn’t. It has made the start faster and the finish slower.

Faster to a shortlist. Longer to a signed decision. If you take one idea from this piece, take that one, because nearly every falling conversion rate I have investigated recently decomposes into those two halves: the buyer did their choosing before you knew they existed, and then their organisation took months to let them act on it.

Why the end of the sales cycle is slowing down

There are four drivers, and any one of them alone would stretch a sales cycle. Together, they are where all the elapsed time went.

1. The buying group has roughly doubled — and gained an external layer. Gartner puts six to ten decision-makers around a complex purchase, each arriving with four or five pieces of research of their own. Forrester’s State of Business Buying now counts thirteen internal stakeholders plus nine external influencers — call it twenty-two people around one decision — with nearly nine in ten purchases spanning two or more departments. Every extra person is another calendar, another set of concerns, and another chance for someone to say ‘not yet’.

2. Finance has become a stage, not a signature. According to G2’s 2026 Buyer Behavior Report, finance involvement in buying decisions leapt from 31% to 46% in a single year, and nearly half of buyers have watched a CFO veto a deal that had already been approved — rising to 54% where there is a dedicated AI budget. Procurement now sits as a decision-maker in over half of buying cycles, engaged from the start rather than stamping the end. The uncomfortable implication: if your business case cannot survive a finance review you are not in the room for, you do not have a business case.

3. The payback window shortened while the approval lengthened. Three in four buyers who have been through a late-stage veto now expect positive ROI within six months of signing, and they push for contracts of under twelve months at more than double the usual rate. Read that as a single message from the market: prove it faster, and let me commit for less.

4. The real competitor is no decision. Dixon and McKenna analysed 2.5 million recorded sales conversations for The JOLT Effect and found that 40–60% of qualified pipeline is lost not to a competitor but to no decision at all — and 56% of those losses stem from indecision and fear of getting it wrong, rather than genuine attachment to the status quo. Forrester finds 86% of purchases stall at some point. Which brings me back to those two closed-lost reasons I flagged earlier. In my experience, ‘insufficient budget’ is rarely a price objection; it is usually a business case that did not survive an internal conversation you never saw. Budget losses and no-decision losses are mostly the same loss wearing different labels — and that matters enormously, because indecision is addressable in a way a genuine budget freeze is not.

Put the four together and the lengthening cycle stops being a mystery. Cheap, AI-assisted looking gives your champion more options and less proprietary insight, and the organisation compensates with scrutiny. Compression at the top is causing the expansion at the bottom. Which means the response has to work both ends of the funnel at once — and they need different tools.

The front end: win the shortlist you cannot see

Three numbers describe the new front end. 75% of US B2B technology buyers now complete the purchase journey in twelve weeks or less, against eleven months in 2024. 82% have sourced software recommendations from an AI chatbot in the last two years. And 94% of buying groups rank their preferred vendor before they ever speak to a seller — with that preferred vendor going on to win around 80% of the time. The shortlist is the new first meeting. Yet McKinsey finds only 19% of firms are actually implementing generative AI use cases for buying and selling — which is precisely the Google-in-2003 land grab I described above. Here is where I would start:

Shift the discipline from SEO to GEO (generative engine optimisation). Ranking is no longer the game; being retrieved and cited is. That means structured, machine-readable content — specification pages, honest comparison tables, question-and-answer guides that give real answers — written so a model can parse and quote them. This is the same point I made about your own guides feeding AI search at the top of this piece, now with a commercial reason to fund it.

Invest in third-party proof, not just your own claims. Review sites (38%) have just overtaken AI chatbots (37%) as the top shortlist-shaping source, and the models themselves lean heavily on third-party corroboration. Reviews, analyst mentions, community threads and peer evidence are now retrieval assets. Budget for earning them the way you budget for paid media.

Run a generative listening audit, then repeat it monthly. HBR’s 4C framework is the best structure I have seen: Coordination of the narrative across functions, Citability of content, Credibility of the sources citing you, and Calibration — auditing how you actually appear in AI answers. GSK ran roughly 6,000 prompts across nine decision points and discovered they ranked first on broad prompts but fourth on the specific prompt where they believed they were strongest. You cannot fix a shortlist you cannot see. Most companies have no visibility here at all, which is itself the finding.

The back end: shorten the approval you cannot control

Once you are on the shortlist, treat it as the starting line, not the finish line. Everything from here is about helping twenty-two people say yes — most of whom you will never meet.

Arm the champion. Your contact is one voice among many, and most of the decisive conversations happen without you in the room. So build every late-funnel asset to be forwarded without a rep present: self-contained, evidence-led, and written for the sceptic who receives it, not the fan who sends it.

Write the one-page business case a finance director can approve. Your numbers, framed to a six-month payback rather than an annual horizon, with verifiable references attached. Given that finance is now a stage in nearly half of deals, this single page will do more for your conversion rate than another nurture sequence ever will.

Offer phased or flexible commitment where the full ask cannot clear the gate. Buyers are demanding shorter terms and outcome-based structures at double historical rates. A smaller yes that survives the CFO beats a bigger yes that dies in the veto.

Triage ageing deals instead of waiting on them. Deals do not mature at stage like wine; win probability decays sharply the longer an opportunity sits still. Build a weekly review of anything stalled beyond thirty days at stage and treat it as an indecision problem — per The JOLT Effect, your job at that point is to help the buyer decide, not to keep helping them buy: narrow the options, make a recommendation, and take ownership of the risk of acting.

And keep the front-of-funnel discipline from the first half of this piece. Concentrate on the five or six channels your attribution model proves drive revenue, on the roughly 5% of your market that is in-market now, and on the prospects with a nine-or-ten-out-of-ten problem — because a doubled buying group and a CFO veto will kill a ‘nice to have’ every single time.

The funnel has not stopped converting. It is converting somewhere you cannot see, and stalling somewhere you do not control. Win the shortlist you cannot see; shorten the approval you cannot control. Do both, and the two forces I opened with — falling conversion rates and rising cost per lead — start running in your favour, while your competitors are still fighting upstream.

Credibility Is the Spearhead: What working at fast growing B2B SaaS companies on Enterprise ABM Taught Me About Winning Big Accounts

In a recent interview, Jeff Bezos, founder and long-time CEO of Amazon, made a point that has stayed with me.

Everyone, he said, asks, “What is changing in my industry?” But the far more interesting and useful question is, “What will stay the same?” You can build a business around the answer to that.

Two things, in my experience, will never change. The first is that companies will always want to reach larger, often enterprise accounts for big-ticket purchases. The second is that success in that pursuit will always depend on finding curious people: the ones forever exploring new ways of doing things, adopting new technology, and adapting to a business world that refuses to sit still.

With that framing in mind, consider Account-Based Marketing. ABM has existed, in substance, since B2B selling began. But it has been through many permutations — and several name changes: from “Major Account Selling” in the 1950s, to “Target Account Marketing” (TAM) in the early 1990s, to the “Strategic Marketing to Named Accounts” that I was practising at Visual IQ and Zscaler through the 2010s. The label “Account-Based Marketing” only took hold around 2015, pioneered by Jon Miller, founder of Marketo and later Demandbase.

Whatever you call it, ABM is here to stay. The newest chapter in this long-running need — to penetrate enterprise businesses at many levels and across many parts of an organisation in order to secure large recurring deals — is the application of AI.

The AI inflection point

Next week I’ll be attending a workshop with Demandbase built around exactly this question: how do we turbo-charge and extend an already strong understanding of ABM using AI? In my experience, AI can 10x — or more — what you’re already achieving in this realm. But the point is not that machines replace the craft; it’s that they amplify it.

The AI revolution is about leveraging and accelerating the best of what humans can do — by teaching machines how to perform tasks, and then using AI as an “Iron Man” suit to accomplish our goals, together as one unit.

— Teresa Barreira, CMO at Publicis Sapient (and a fellow Northeastern University MBA alumna)

That is the right mental model. The judgement about which accounts matter, why they matter, and how to reach the humans inside them remains stubbornly human work. AI simply lets you do far more of it, far faster, and with far better signals.

This is not a new interest of mine. About two years ago, content strategist Damien Seaman and I convened a virtual roundtable with leaders across B2B SaaS — CMOs, heads of demand generation, and others — to examine how this account-based approach was proliferating. 

A year later, in August 2025, I worked alongside AI go-to-market experts like Jasper Ruijs (the organiser), including senior leaders from Adobe and Semrush, together with Clay and ABM specialists, to understand how AI was reshaping the way large B2B deals get done: “fishing with spears” — precise, one-to-one marketing — as opposed to the “fishing with nets” typical of smaller, more transactional B2B.

As with everything AI touches, ABM is moving fast. Rather like the Red Queen in Through the Looking-Glass, you have to keep running simply to stay in the same place. Getting ahead of the curve takes even more talent, open-minded thinking, momentum, organisational backing, and investment.

Three stories from the field

I fear I’m getting too technical, so let me set the acronyms aside and tell some stories instead — because the principles are best seen in practice.

Visual IQ: 50 accounts, a pair of binoculars, and a category-defining survey

When I joined Visual IQ, in Boston, Massachusetts, in 2013, we had a crack team. On the sales side, most had been poached from Adobe by our Chief Revenue Officer, formerly head of sales at Omniture (which Adobe acquired). These were people with reams of experience closing multi-million-dollar-a-year accounts for digital marketing attribution with global names like TK Maxx, Walmart, Johnson & Johnson, Mastercard and P&G — where, incidentally, many of my fellow marketing MBAs had done their internships.

I learned an enormous amount about ABM from these people. Many times a week I’d sit down with a regional VP of marketing in the US, along with the VPs for Europe and APAC. We would draw up a list of the top 50 accounts they wanted to penetrate and debate the best way in: outbound calling? A physical promotion? An email campaign? LinkedIn InMail or sponsored content? Once the strategy was agreed, the hard, patient work of spear-fishing began.

The physical promotion is worth dwelling on, because it captures the essence of ABM better than any framework. Because we sold attribution — helping marketers see clearly — we had branded binoculars made, embossed with the Visual IQ logo, and sent them to the heads of marketing and digital at our 50 target accounts. 

In the US it did exceptionally well. The head of marketing at ESPN loved it, and it helped open the door to a roughly $1m deal. That is spear-fishing: a memorable, relevant, one-to-one gesture aimed at a named individual inside a named account.

Visual IQ also taught me the power of owning a category conversation. We published an annual State of Marketing Attribution survey report, built on the views of 500 CMOs. It generated a huge amount of SEO and some of the strongest leads we produced — because it made us the reference point for a question the whole market was asking. 

I’ve since replicated that playbook more than once, most memorably at a video-game advertising company where a segmented State of Video Game Advertising survey drew around 300 responses in what was essentially virgin territory, with tailored question sets for game companies, advertisers and agencies. The segmentation itself became a form of personalisation, and the response was excellent.

None of this was happening in a vacuum. The reason those spears landed was that the market already regarded Visual IQ as a leader. Forrester placed us in the Leaders segment of its Cross-Channel Attribution Wave — the analyst validation that made a cold outreach warm before a single word was exchanged.

The Forrester Wave™: Cross-Channel Attribution Vendors, Q2 2012 — Visual IQ positioned in the Leaders segment (Source: Forrester Research, Inc.).

What made the Visual IQ machine work was that ABM ran on two engines at once. The outbound engine penetrated named strategic accounts in defined regions; the inbound engine qualified the demand our category leadership and content were creating — web downloads, CMO reports, Forrester Wave enquiries, newsletter opens, referrals — and handed genuinely qualified opportunities to field sales. 

Marketing and sales weren’t two departments lobbing work over a wall; they were one motion. I still have the pipeline reviews from that period, and the discipline is striking: strategic accounts analysed for why prior efforts had won or lost, contact reach expanded through ZoomInfo (a list-building and sales intelligence tool I pioneered using at LMTech in 2011 and at Visual IQ in 2013), Salesforce and LinkedIn, and bespoke material built for specific verticals and named targets — never generic blasts.

Zscaler: the free security audit, and the confidence to be expensive

Zscaler taught me the same lesson from a different angle. Our whole proposition was cyber security delivered from the cloud — breaking companies free from the tangle of on-premise security appliances. Once again, we started with the biggest game. I worked at the Demand Generation HQ in Austin, Texas, before I moved over to the UK in 2015.

As at Visual IQ, I worked with some of the best salespeople in the business — typically from companies like Cisco, Palo Alto and Fortinet. Our ‘sales bible’ was The Challenger Sale, based on thousands of sales data points across hundreds of companies: a data-driven approach to enterprise sales success.

We drew up a list of 50 companies we wanted to penetrate and offered each of them something substantial: a free consulting engagement in which we would go in, examine their security posture, find the weaknesses, and hand back a report.

That offer is expensive to fulfil (up to $5,000 per company). You cannot make it to 5,000 companies; you can barely make it to 50. Which is precisely why account selection mattered so much.

We had to be genuinely confident that the accounts we approached were strong potential customers before we committed real consulting hours to them. Get the targeting wrong and you don’t just waste money — you burn your best asset, your experts’ time, on accounts that were never going to buy.

Here too, analyst standing did heavy lifting. When you walk into a global enterprise’s CISO office offering to audit their defences, the first unspoken question is “why should we let you?” Being named a Leader by both Gartner and Forrester answered it before we did. 

Gartner’s Magic Quadrant for Secure Web Gateways placed Zscaler firmly in the Leaders quadrant, alongside a very short list of credible names — and well ahead of the challengers and niche players.

Gartner Magic Quadrant, Secure Web Gateways, May 2015 — Zscaler positioned in the Leaders quadrant (Source: Gartner).

At Zscaler, in Europe, I also pioneered the use of Sales intelligence to aid us in spearing the top accounts. How it would work is this: We would identify five leads for Barclays Bank (A Key account). I would see in our Intelligence system, Discoverorg, that Barclays was looking to invest $5 million in various Cyber technologies this year. I would pass that on to the sales team, as well as crafting additional messaging around that proposition. 

Funnily enough, Discoverorg was acquired by Zoominfo (which I had been a big evangelist of before at several companies), a few years later. 

The through-line from Visual IQ to Zscaler is simple: in enterprise ABM, credibility is the spearhead. The binoculars, the free audit, the survey report — these are the conduit. But analyst recognition, category leadership and social proof are what let the spear actually penetrate. 

Both companies went on to strong exits — Zscaler to a landmark IPO, Visual IQ to acquisition by Nielsen — and in both cases the account-based motion was central to how the enterprise pipeline was built.

I think I’d be remiss if I didn’t also mention my time as Demand Generation Manager at Hansen Technologies. We provided CPQ solutions for the telco and media sectors. Our entire universe of accounts was under 1,000, and our average deal size was $1 million. It was a pure ABM play.

I still remember our star sales engineer closing the Australian telco Telstra for $5 million ARR, where they would also be paying a $250,000 switching cost. That sales engineer, Pedro Jose, is now the CTO at Snowflake.

What the practitioners told us

I don’t want to leave the impression that ABM is a solved problem, or that my own experience is the last word. It isn’t. The roundtable Damien Seaman and I hosted brought together eight senior B2B marketers — from a cyber-security demand-gen lead to a portfolio CMO to a private-equity Chief Development Officer.

What struck me most from this session was how early most organisations still are on this journey, and how mixed the results have been even for experienced hands. A few themes emerged that map almost exactly onto what I learned in the field a decade earlier.

Intent is the modern equivalent of my top-50 list

At Visual IQ and Zscaler we built our target lists from a blend of engagement data and, crucially, sales-team feedback, confirming that accounts which looked engaged were also accounts sales agreed were worth an opportunity. 

I’ve always liked the Bezos line that when the stories and the data disagree, trust the stories. John Blackmore, who leads demand generation at a cyber-security firm, described the modern, instrumented version of the same instinct: rather than cold-calling phone books, his team listens for intent signals — someone researching endpoint detection, or evaluating a competitor.

Marketing and sales then insert themselves only into conversations that are already live. In his words, intent now accounts directly for around a quarter of his pipeline and lifts the efficiency of his other tactics by 10–15%. This is the same philosophy as my top-50 list, but with far more advanced technology and sensors.

The tool is the assist, not the goal-scorer

The most quotable insight of the day was also the most important, and it validated something I’d seen go wrong more than once. John — a Canadian, so the ice hockey metaphor is fitting — argued that ABM platforms like 6sense and Demandbase are not the killer app but the assist:

ABM is the assist. It’s not necessarily the goal-scorer, but it sets up all your goal-scorers in a great way to put the puck in the net. It can improve the efficiency of every tactic by 10 to 20%. It’s worth its weight in gold, even if it never delivers one sale for you.

— John Blackmore, Global Director of Demand Generation

To extend the analogy: in ABM, you want to skate to where the puck will be, not where it is, to paraphrase Wayne Gretzky’s famous line.

I’ve also lived the counter-example. At Tricentis, the team had the full Demandbase package, but left it on the shelf. Rocio Sasson, VP of Demand Generation at Checkmarx, described the same trap from her seven years using both 6sense and Demandbase: the platform is only as good as the cross-team effort behind it, and personalisation “takes a long time and still doesn’t guarantee success.” A tool bought and unused is worse than no tool at all, because it tells the organisation that ABM doesn’t work when in fact ABM was never really tried.

ABM is really a sales-and-marketing alignment strategy in disguise

This, for me, is the deepest point, and it’s the one my Visual IQ pipeline reviews prove out in retrospect. Every roundtable participant with real success traced it back to alignment. Blackmore holds two standing weekly meetings with two different sales teams purely to interrogate lead quality — are these good, do you like them, who do you actually want to talk to? 

He put it memorably: you’re not buying 6sense; you’re buying collegial alignment, and the tool is simply the expression of it. Rocio was blunt about the failure mode: however beautiful the asset, if sales won’t work the leads, the whole effort collapses.

This reminds me of Jim Collins, of Good to Great fame, who made a similar point about using technology. Collins said that in his analysis of top-performing companies, technology was not even in the top ten of the most important factors driving their success. It was the utilisation of technology to enable other high-performing functions — so, just like Teresa Barreira’s ‘AI as Iron Man suit’ analogy.

John Blackmore’s point also matches my lived ABM experience exactly. I’ve produced thousands of leads that fell to the floor because sales wouldn’t pick them up. The reverse — the two-engine Visual IQ motion where marketing qualified and sales closed as a single unit — is what actually produced million-dollar accounts. ABM, done properly, forces that alignment because the model simply cannot function without it.

Personalise the message, not just the list

Damien shared the campaign I still think is the gold standard of spear-fishing: a Canon campaign targeting C-suite executives at listed companies across six European countries.The team printed each target’s annual report, found the passages where the company itself flagged document-management pain, and hand-wrote tailored messages on Post-it notes placed at exactly those pages — each package arriving under a cover letter from Canon’s country head, peer to peer. 

The result was an 80% response rate across more than 100 accounts. The lesson isn’t the Post-it notes; it’s that the value proposition to different personas for the same product is genuinely different, and the personalisation has to reach the message, not just the mailing list.

There is far more in the full write-up — including a candid debate on whether LinkedIn produces real pipeline or only brand awareness (referencing the notoriously long LinkedIn lead sales cycle), the mechanics of preferential paid-search bidding on target-account segments, and geo-fencing as an alternative to trade-show spend. I’d encourage anyone serious about ABM to read it in full: B2B SaaS Leaders ABM Roundtable.

Where this leaves us

Put the field experience and the roundtable side by side and the pattern is hard to miss. The fundamentals of ABM have not changed in decades: pick the right named accounts, reach the right humans inside them with a message that speaks to their specific pain, and make marketing and sales a single motion rather than two teams.

Spear fishing, with AI

What has changed is the instrumentation. Where I once built a top-50 list from engagement data and a weekly conversation with a regional VP, today’s intent platforms surface that signal continuously and at scale. And where personalising a hundred accounts once meant hand-writing Post-it notes, AI now makes genuine one-to-one relevance achievable across thousands of them.

That is the opportunity in front of us, and, per Blackmore’s hockey metaphor, we are still in the early, high-advantage days of learning to use it well. We are also in the early stages of AI, and so those two nascent approaches are combining to produce an effect that is both hard to replicate and potentially a quantum leap in sales and marketing performance for those rare companies able to harness them both effectively.

John Blackmore, a veteran marketer, likened the state of ABM today to the early days of Google Ads. The combination of formidable intent-capturing platforms — Clay, HubSpot, Demandbase, 6sense — with fast-developing AI means the opportunities in this field are enormous.

But the platforms are available to everyone; the advantage was never the tools. It belongs to the companies with the talent and judgement to aim them, and the discipline to make marketing and sales fire as one.

The 272-Day Problem*: Why Your B2B Sales Cycle Keeps Getting Longer, and What to Do About It

Image above, source: Demandbase

I’ve spent almost my entire career in b2b sales and marketing, most of it in software. And I am seeing changes in the business that are unprecedented, and are hitting companies like a perfect storm.

- Plummeting conversion rates and ROAS on advertising, compounded by the already existing issue of often very small target audiences (as compared to B2C)

- Difficulty in attributing revenue, since a sale involves such a flywheel of both marketing and sales collateral and channels, that sometimes it would take a marketing analytics genius to unpick what caused that sale.

- The continual march of new technologies, like ABM platforms, Intent, and list building tools, AI – the game changer, and now, often hard to fathom AI hybrids like Clay (try explaining that to someone unfamiliar with it – ‘its like a cross between zoominfo and seamless AI, except it also ingests data from lots of other intent and list building tools like bombara’).

- The unrelenting pressure, which I’ve never seen before in my entire career, to prove ROI on every single action. In the 'roaring' 1990’s you could throw money around to get sales, these days CFO’s want military precision in the way marketing (and sales) budgets are allocated. 

- Falling lead to sale conversion rates, which sometimes can accompany declining average order values at the same time – in countries or sectors with low or negative growth, for example. 

Yes, B2B sales has certainly changed dramatically in the last thirty years. Some of those changes have been slow and incremental, for example the changes in business intelligence, from using magazines and trade publications to research prospects (yes, that did happen in the ‘olden days’ as my 17 year old son Jack calls any time pre-2000), to basic computer research (but google was very basic back then), to the adoption of tools like zoominfo and discoverorg, that provided you with both list building and business intelligence features – this would take us from the 1990’s, up until say 2018.

Others have been dramatic and disruptive – with the adoption of AI, which hit us all hard at the start of the 2020’s. Continuing that business intelligence example,  where now where you can get a full breakdown on a prospect in seconds using a variety of AI tools. 

But possibly the most alarming change, and one that is baffling teams across the world, from small startups, to huge behemouth companies, is the lengthening of the sales cycle 

Dreamdata** just dropped their 2026 LinkedIn Ads Benchmarks Report, and the data confirms what we already felt:

• The B2B sales cycle is getting longer, more complex, and more demanding.
• The average B2B customer journey now takes 272 days — up from 211 last year*
• Each deal involves 10 stakeholders and 88 touchpoints across 4 channels.
• And 81% of that journey happens BEFORE a prospect ever enters the sales pipeline.

That means buyers are spending roughly 7 months doing their own research before they ever talk to you. This aligns with other research I’ve read that show that 80%+ of the sales evaluation is completed before a b2b prospect even talks to your sales person. With AI that number will no doubt increase. 

So what is going on, and why?.... and I’m sure an even more important question you are asking: How can I fight this trend, and start to shorten our sales cycles?

Firstly, Looking at the data across B2B (Saleshive) this is the pattern

What’s particularly interesting about this data to me is that it matches what I’ve seen in reality working at a variety of mainly b2b saas companies, from Zscaler, Visual IQ (Now part of Nielsen), and Hansen, working on average annual deal sizes of $1M -$5M, to working more recently at companies like Mention Me, or Mintago, where it was at the other end of the spectrum, $20,000-$75,000. But across the board I’ve seen slower sales cycles.

Why B2B Sales Cycles Are Stretching

Expanding Buying Committees: A typical complex B2B purchase now requires consensus from 6 to 10 distinct decision-makers (ranging from IT and security to finance and procurement). Every stakeholder added introduces another calendar, new objections, and internal misalignment

Intense Budget Scrutiny: Due to broader economic slowdowns, purchases that previously required a single manager's signature now need multiple sign-offs, often terminating in a strict review by CFOs or procurement teams

The "No Decision" Paradox: The fear of making a bad software or vendor decision has increased. Research shows that 40% to 60% of B2B deals end in "no decision" because champions cannot justify the business case internally, or because the team is overwhelmed by information.

What can we do about it? 

Gen AI is restructuring the entire B2B buying journey. AI is not just adding a new channel, but displacing the controlled channels (sales reps, distribution networks, owned media) that B2B go-to-market has always relied on. 

Buyers now use AI tools to discover vendors, compare options, and evaluate fit long before they ever talk to a salesperson, which means much of the influence happens before sellers even know a buyer exists. 

This means that the current ‘80%' of buying done before a prospect even talks to a sales person may move up to 90%, or even 95% over the next five years. 

Obviously, the sales person who can make the most of that 20%/10%/5% of influence they have at the end of the buying cycle is critical. 

If the sales person is not armed with all the buying information they need, they will loose out to better informed, and supplied sales people (even if those sales people are not as technically proficient or experienced).

How the funnel changes

The old funnel ran on controlled channels and a slow, resource-intensive evaluation phase. Buyers worked through offerings, use cases, pricing, and internal alignment over months. 

Gen AI is inverting the shape: the top widens because buyers can access a far broader set of vendors via AI synthesis, but options get eliminated much earlier and faster. 

75% of US B2B technology buyers now finish their purchase journey in 12 weeks or less, versus 11 months in 2024. That is a fast and dramatic compression. IDC's predicts that 62% of traditional B2B demand generation will be AI-led by 2028.

Buck the increasing Sales cycle trend with smart search strategies

You'll have no doubt spotted the contradiction. Everything above says B2B sales cycles are getting longer, yet here's IDC forecasting an AI-led buying surge that makes them dramatically shorter. Both are true. They're just describing different parts of the funnel.

The lengthening happens at the back end: more stakeholders, tighter procurement, CFO sign-off. That's structural and it isn't going away. But the front end, discovery, research, shortlisting, is where AI-led buyers move at a completely different speed. 

A buyer who once spent months researching now lets an AI assistant synthesise the options in an afternoon. The committee still takes its time; getting onto the committee's shortlist now happens in days.

That's the opening. The average cycle is lengthening, but a fast-growing pocket of AI-native buyers, concentrated in the US, where these shifts usually begin, is compressing the early stages hard. 

Get your content built for how those buyers actually search, and you don't just keep pace with the trend. You can pull your prospects through the slowest, most expensive part of the funnel before your competitors even surface as an option.

Two opposing truths in one market is a lot to hold at once. It feels like cognitive dissonance. But sit with it, and the contradiction dissolves: the cycle is lengthening and compressing at the same time, in different places, for different reasons.

From an SEO perspective, using a famous analogy, you don’t want to be the organisation producing the best buggy whips, as the age of the motor car begins. Yet so many organisations are stuck in the old models. 

McKinsey’s 2025 B2B Pulse Survey finds that only 19% of respondents are implementing use cases involving gen AI tools for B2B buying and selling.

A pilot study conducted by Digitas UK, a subsidiary of Publicis Groupe, examined B2B fintech payment solutions in the UK and U.S. markets. The findings revealed that more than 80% of the sources leveraged by LLMs originated directly from the brands themselves, such as Stripe, Adyen, PayPal, and Visa. 

Caitriona Gallagher, strategy partner at Digitas, said: “This makes sense because these brands have significant amounts of content on their sites to help support B2B buying journeys, including product comparison content and sector/audience led content".

So even if your industry is in a category that you don’t think warrants much of your own in-house quality technical content, AI will still be pulling search data for your prospects from the internet.

If you don’t have anything out there, content wise, your company will fall at the first discovery phase (Awareness/Consideration/evaluation) of your prospects AI driven buying journey. And as I already explained, the trend is moving to faster choice of vendor at the outset using AI research capabilities. 

If your content is not adapting to the new world, you could be left out in the cold, with your company not even being considered as an option at outset, let alone making it to the final decision stage, and eventual sale. 

When I first worked in sales over 25 years ago, there was complete information asymmetry on the part of the seller. The buyer had very little information to go on – trade magazines, perhaps some scraps of information on the then nascent internet. 

As time has passed, that balance has swung the other way completely. In the past, the sales person controlled perhaps 80% or more of the information that the buyer went on, but now, as discussed those numbers are reversed and may even move to 10% or less. 

We live in a world where the sales people have fast diminishing opportunities to make their mark on the prospect. So the sales person who is best informed will win most of the time. 

The Dark Funnel (AKA 'Iceberg'): Why 80% of Your Buyer's Journey Is Now Invisible to You

That is where tools like Demandbase, 6sense, clay, hubspot, alongside bespoke AI solutions, can make a decisive difference. These tools enable you to get into the heads of your buyers: 

Find out what problems they have (maybe even before they themselves can articulate them), what motivates them to buy, where they are in the buying cycle, and when the 95% of buyers finally jump to that sales nirvana of being ‘in market’. 

Some companies are sprinting ahead with these tools and methodologies; For example, in the Enterprise B2B SaaS markets I've worked, we started to transition  from the MQL-SQL-Sales model a long time ago, to the 'Buying groups' model 

This is where we recognise that it is (In Enterprise B2B) rarely one lead that drives a sale, but rather a group of decision makers - say, the initial sponsor, a mid management decision-maker, alongside, perhaps a CIO, a CFO, and a technology lead. 

To clarify - Retaining MQL as a metric, but adding an additional layer of insight around buying groups, for example on their intent dashboard.

Whilst many other companies are struggling to get the most basic data and insights, even from their own prospects and customers. You feel like saying 'hey, 2015 called and they want their Martech, and CRM stack back'.

- This joke originally came from the team at Akamai, who used to laugh at my wife, Catherine, still using a blackberry when everyone else was on Iphones already - I'm glad to say I was instrumental in securing that upgrade for her.

Peer to peer content, research, and review sites

When I purchase Hubspot CRM, and Marketing Automation for the UK and Italy arms of an international company just prior to its IPO, I was pretty nervous about making the right decision. 

There was a wide range of options available to us; from building in-house, keeping our existing, but rudimentary Pipedrive/Mailchimp infrastructure, or using combinations of Salesforce/Hubspot/Marketo/Dynamics and other providers out there. 

What helped me enormously in that critical final purchase stage, was the array of high quality peer-to-peer review sites, like trustpilot, google, and most importantly for me, G2  - the most professional and reliable of them all. That was in addition to reading the best research from companies like Forrester, Gartner and IDC.

I guarantee that your prospects will be doing the same. And the biggest trend of them all is the peer-to-peer content, which has skyrocketed - G2 crowd, Quora (I'm pretty active on that one), Linkedin, and to a lesser extent, reddit. These are also sites that AI use to drive their search answers. 

The best salesperson in the world won't sell your product as brilliantly as glowing customer recommendations. Win the reviews, win the revenue, and shorten your sales cycle.

Cracking the UK Productivity Puzzle

My family and I just got back from a week in Greece. It’s a beautiful country with wonderful people. But more importantly, almost all that we have today sprang from that vibrant, innovative, intellectually brilliant culture – Democracy, Mathematics, the Sciences, Philosophy, the arts. 

Sure there are other cultures that have influenced the word a great deal from the Romans (though they stole a lot of their ideas from Greece too), to ancient India, China, then later the French, Germans, Spanish, Portugese, Dutch and the British.

But the Greek culture has had a disproportionate impact on the world we live in today. My American wife, Catherine, often has quite a ‘new world' take on issues – On Greece, she also had a very thought-provoking insight; "it’s amazing that this country was the birthplace of so much that is exceptional in the modern world. Yet look at it today, mired in unemployment, poverty, and with a failing political and economic system".

And I got thinking – what caused that decline? I came to the conclusion that one powerful factor was declining productivity growth.

"Making the safe decision is the fastest way to become irrelevant."

Teresa Barreira, Global Chief Marketing and Communications Officer at Publicis Sapient, argues that growth comes from challenging the status quo: 

"Fortune favors the brave who are willing to disrupt, challenge, and change things. It applies to everyone and everything, from individuals to companies and brands." Teresa Barreira on LinkedIn

Countries need to keep innovating, taking risks (as in the quote above), challenging the status quo, and improving, to maintain their economic strength. And without economic strength, no other can really persist. 

No country can afford to rest on its laurels, otherwise they risk going from being the Greece of the ancient world to the Greece of today (still beautiful but certainly no one would claim it is a global powerhouse).

Then I started to think about three countries that I am most intimately acquainted with – I have lived and worked extensively in all three countries. The Netherlands, where I was born, and the home of my mother. 

The UK where I was raised for much of my life, and where I went to school, and university. And finally, the USA, the country I moved to by choice – first, to study for an MBA, and then raising a family and working there, for ten years.

But my experiences are one part of the story only. I will rely on data to inform me as to my thesis on falling productivity. But there are other, rather wonderful reasons why comparing the UK to the Netherlands, and the USA can provide such powerful insights.

The USA has the most free market Economy of the three – the lowest taxes, the highest inequality (though the UK is getting closer), and the least protective legislation.

It varies from state to state though – Massachusetts, where I lived, is closer to the UK in workers protection. Whilst States like North Carolina, Florida, or Texas are truly the ‘wild west’ with very little in the way of workers rights, paid vacation, or maternity/paternity leave).

The Netherlands is at the other end of the spectrum politically, and socially. It is very hard to fire someone (as in France, or Germany). Workers are far more protected than in the UK. 

Dutch employees also work some of the shortest hours in the world: 27 hours a week in the Netherlands versus 36 in the USA and 31 in the UK.  https://worldpopulationreview.com/country-rankings/average-work-week-by-country  - as you can see one way thay achieve that is by being super-productive.

It’s hard to talk about large macro economic issues like productivity, or innovation, without veering into politics. When you start to talk about solutions to issues like low productivity growth, it’s almost impossible to do so without talking politics.

However, I am aiming to, as far as possible, avoid taking a political position. That is one of the reasons why I chose two countries with much differing political outlooks, to compare to the UK.

 

The Problem – low productivity growth in the UK over the last twenty years, which has been exacerbated by each crisis – from the 2008 financial crash, to Brexit, to the Covid pandemic. 

UK productivity, already struggling, has been hit by each crisis, and not recovered from them (in the way that the USA, has, for example). Why is that?

So I have two theories backed with extensive evidence, why the UK is underperforming both a more free market economy like the USA, as well as a more planned economy like the Netherlands?

And one that is more of a conjecture, based on my personal experience and observations. However, I have provided some good data to support that theory as well. 

Lack of investment

My experience of working in the US and the Netherlands bears out the hard evidence, that business investment in the UK is very low and falling, and that this is a major factor in our poor productivity growth. 

I’m not just talking about investment in hardware, software or other work tools. There is very little on the job training in the UK, versus in the US, or the Netherlands.

The numbers behind that observation are stark:

Whole-economy investment in the UK was just 18.9% of GDP in 2025 — the lowest in the G7. The US sits at 21.6%. The Netherlands at 19.7%. 

A three-percentage-point gap against the US doesn’t sound like much. But sustained year after year for two decades, it compounds into a yawning chasm.

The Institute for Public Policy Research went further in their April 2026 analysis. They calculated a “capital gap” — how much less capital British workers have to work with compared to peer countries. 

The answer: British workers have 38% less capital per hour worked than the average of comparable economies. In manufacturing specifically, the gap rises to 47% — versus a peer set of the USA, Germany, France and the Netherlands. 

British factory workers are working with roughly half the machinery, equipment, robots and IT systems that their American, German, French and Dutch counterparts have. 

Of course they produce less per hour. They’re working with one hand tied behind their back. (IPPR press release, April 2026)

Somehow this fact made me come back to Greece again - They were using the state of the art equipment, three thousand years ago. 

But today, they sit significantly lower than any of the countries mentioned, including the UK (Greece is sub 18%, and they're more than half less productive than the Dutch or the Americans).

And it gets worse on intangibles. 

The US invests 6.7% of GDP per year in software, IP, data and organisational know-how. The UK invests just 4.2%. 

That gap is hugely significant because intangibles — software, design, brand value, training, R&D — are increasingly what drives productivity in a modern economy. 

The US has been quietly out-investing us in the very things that compound the fastest, and the gap is widening, not closing.

Then there’s the on-the-job training I mentioned. The hard numbers: British businesses spend roughly half the EU average per worker on training and development. 

Anecdotally, when I attended a US business school, half of the MBA part-time class were funded by their employer, and around a ten percent of the full time. 

80% provide financial support to employees pursuing MBA programs specifically (Georgetown CEW / GMAC). In the UK, that would be unthinkable. 

And that, ultimately, is the point: if we invest less in our people, our tools, our skills and our future, we shouldn’t be surprised when productivity flatlines. One way to look at this problem, is that the countries that out-innovate us are simply out-investing us.

The Chartered Management Institute reports that around 82% of UK training spend is funded by employers themselves 

— and naturally, employers prioritise senior and professional roles, not the middle managers and frontline workers who actually run day-to-day operations. 

And that is born out anecdotally by myself. I got a tremendous amount of on-the-job training when I worked in the USA. In the UK, I've had virtually zero. 

I have had an immense amount of training in the UK - but almost all of it has been self-funded, and self-directed. So my anecdotal story of working in the UK fits the data. 

The result is a workforce that doesn’t get developed beyond what each individual chooses to invest in themselves.

In the States, every employer I worked for had a real training budget — actual money set aside to develop me. In the UK, that is rare, or even non-existant. 

Poor management

If I’m honest, this is the one that surprised me most when I started digging. I’d always vaguely assumed British management was a bit stuffy but basically fine. It turns out, it isn’t.

There’s a serious field of academic work measuring management quality across countries, called the World Management Survey. It’s been running since 2002, led by Nick Bloom (Stanford), John Van Reenen (LSE/MIT), and Raffaella Sadun (Harvard). 

They’ve trained interviewers to score firms across 18 management practices — things like target-setting, monitoring, talent development, and how firms deal with poor performers — using structured interviews with middle managers. They’ve now covered around 13,000 firms in 35 countries.

The results aren’t kind to us.

The US comes in first. Then Japan, Germany, Sweden and Canada. The Netherlands ranks sixth, at 3.04 out of 5. The UK ranks seventh, at 2.95. The gap to the Netherlands is small. 

The gap to the US is roughly half a standard deviation — which sounds technical, but Andy Haldane (then chief economist at the Bank of England) translated it in a memorable 2018 speech, “The UK’s Productivity Problem: Hub No Spokes.” 

UK management practices, he said, are about half a standard deviation lower than comparator countries, and these management skills are statistically significant determinants of productivity.

But here’s what really matters: the headline average understates the problem.

Haldane showed that the UK has TWICE the share of firms with low management scores compared to the US and Germany. 

We have plenty of world-class firms at the frontier — but a long, fat tail of badly-managed companies that other countries simply don’t have to anything like the same extent. 

Notice in the chart below, how UK productivity growth has plummetted from 1980-2007 (2.2%) to  2008-2023 (0.4%). That's a productivity growth drop of 5.5x.

If a company exhibited that trend, leadership would be asking some serious questions. It would be what the americans call 'A come to jesus moment'.

And that tail has been growing. Between 1997 and 2023, the number of UK firms below the 25th productivity percentile nearly doubled, from around 444,500 to 873,000.

Why? My theory — and this is where it gets uncomfortable — is that we’ve created a class of “accidental managers.” The Chartered Management Institute estimated in 2023 that 82% of UK managers had no formal training before being put in charge of people. In 2019 the figure was 68%. So it’s getting worse, not better. 

The downstream economic effects are brutal. A UK SME generates roughly £147,000 of output per worker per year. A German SME generates £335,000. That’s more than double. 

A UK business with ten employees could theoretically add £1.9 million in annual turnover if it operated at German productivity levels. 

Now think about how many small British firms are scraping by, when with better management they’d be thriving.

How much of the international productivity gap does management actually explain? 

Bloom and colleagues estimated in 2016 that management practices account for roughly a third of the productivity gap between the US and other countries.

Management isn’t a soft factor. It’s a major component of why the UK is falling behind.

When I worked in the US, most of my managers had been trained — through MBAs, or rotational programmes, or formal leadership development.The Netherlands has also has built-in formalised training for all employee levels.

Lack of cognitive diversity

Scott Page (Michigan, complex systems) published the foundational paper with Lu Hong in PNAS in 2004 showing, with proofs, that a randomly-selected group of diverse problem-solvers outperforms a group composed of the highest-ability individual solvers, on sufficiently complex tasks. 

Page shows that various types of cognitive diversity — differences in how people perceive, encode, analyze, and organize the same information and experiences — are linked to better outcomes. https://www.pnas.org/doi/10.1073/pnas.0403723101

My experience working in both the USA and the Netherlands is that neither country treats conventional wisdom as sacred.

In America especially, the belief that one person with a better idea can overturn the status quo sits at the heart of the culture. 

I think that used to be the case in the UK. But I'm not so sure anymore in the last fifteen years or so. It seems like UK companies are more risk-averse than they used to be. 

From the revolution against King George III to Moneyball, where a young economist transformed baseball by ignoring decades of accepted thinking, Americans have long admired people who challenge established assumptions.

That culture doesn't just produce entrepreneurs and innovators. It creates an environment where different viewpoints are encouraged, disagreement is accepted, and new ideas are more likely to emerge.

Interestingly, the Netherlands, despite its many differences, resembles the USA in one important way: Typically everyone speaks up. In a meeting, most Dutch colleagues will offer their view, and no one assumes their opinion matters less because of rank or title.

The Dutch and Americans share a striking directness, especially compared with the famously oblique British style.

Their meetings can occasionally feel blunt, even bruising, but they’re rarely short on ideas. 

            

By contrast, the UK’s hesitancy sometimes feels cultural, a mix of deep-rooted elitism, and an over-reliance on conventional wisdom. 

It’s a british tendency that thinkers from Napoleon to, more recently, Elon Musk have pointed out, and commented on.