From Visibility to Buyability: Why B2B Marketing Must Win the Decision Before Sales Arrives

For most of my career in B2B marketing, visibility has been treated as the starting point of almost everything we do. The reasoning is familiar: if prospects know you, they can consider you; if they find your website, read your content, attend a webinar, or engage with a LinkedIn campaign, some will eventually become leads. Those leads can then be nurtured, passed to sales and, with the right proposition and timing, converted into opportunities.

The technology around this process has changed enormously over the years, but the basic logic has remained surprisingly stable. Even when we moved from traditional lead generation towards account-based marketing, intent data and increasingly sophisticated attribution models, we were still largely trying to solve the same problem: how do we make ourselves visible to the right people, recognise when they show an interest and move them towards a commercial conversation?

Lately, however, I have started to think this view of B2B marketing describes only the part of the buying process that’s visible to us.

This is why I found the concept of Buyability, recently developed by LinkedIn and Bain & Company, particularly interesting. Their research on the principles of Buyability starts from a relatively simple idea. In complex B2B markets, being visible, or even being considered, is not enough. A brand needs to be credible, familiar and safe enough for a group of people inside an organisation to agree that buying from it is a sensible decision.

Many of the ingredients behind this idea are not new. Anyone who has worked in B2B for long enough knows that brand familiarity matters, that purchasing decisions involve several stakeholders and that perceived risk can be as important as product features. What makes Buyability interesting to me is the way these familiar realities come together at a time when AI is making an increasing part of the buying journey invisible to both marketing and sales.

A buying decision we never see

Imagine a multinational company deciding that its treasury infrastructure is no longer adequate. Its Head of Treasury begins investigating alternatives, perhaps because the company has grown internationally, existing processes have become too manual or management wants greater visibility and control.

Ten years ago, much of that research would probably have produced a reasonably visible digital trail. She might have searched Google, visited several vendor websites, downloaded a whitepaper, registered for a webinar and eventually requested more information. We would never have seen the complete journey, of course, but enough of it would have left traces for marketing to detect and, eventually, measure.

Today the same process can begin very differently.

The Head of Treasury might ask ChatGPT, Gemini or another AI platform to explain the main approaches available to a company of her size. She could ask about the advantages and disadvantages of outsourcing certain treasury functions, implementing new technology or expanding the internal team. She could then ask which providers operate in Europe, which ones work with multinational organisations, what the principal implementation risks are and what questions she should ask when comparing them.

Within half an hour she may have learnt a considerable amount about the market, yet from the perspective of every vendor in that market, absolutely nothing has happened. No website visit has been recorded, no form has been completed and no new contact has appeared in a CRM.

She then speaks to two treasury peers. One recommends Vendor A; another mentions Vendor B and sends her an article written by one of its senior consultants. She looks at both companies on LinkedIn, reads a discussion involving people from the two firms and asks an AI assistant to compare their approaches.

There is also a Vendor C. Its technology is excellent, its website is well designed and it ranks strongly on Google for several important terms. But it has not appeared in the recommendations, the conversations or the AI-generated comparison.

Vendor C has visibility. What it lacks, at least at this stage of the process, is Buyability.

This distinction sits at the centre of the LinkedIn and Bain research. Their work suggests that vendors are dramatically more likely to be selected when the whole buying group already knows them before the purchasing process properly begins. In their research, 81% of purchases went to vendors that were already known by almost everyone in the buying group, compared with only 4% for vendors known solely by the person recommending them.

At first sight, this might simply look like another argument for investing in brand awareness. But awareness and Buyability are not quite the same thing. Awareness asks whether people know you. Buyability asks whether there is enough collective confidence for them to choose you.

A company can be widely recognised and still have relatively low Buyability in a particular purchasing situation. The buying group may know the name without understanding its expertise, seeing relevant customer evidence or feeling confident enough to defend the decision internally. Familiarity matters, but Buyability describes what happens when familiarity is reinforced by credibility, evidence and trust.

That tells us something more interesting about how organisations make decisions, because in a complex purchase familiarity does not merely make a company easier to remember. Combined with the right evidence, it can make that company easier to agree upon.

When the best solution is not necessarily the easiest to buy

Our Head of Treasury eventually narrows the choice to three potential providers and develops a preference for Vendor A. Its technology appears to fit the company’s requirements, the initial discussions have gone well and, viewed through the conventional sales funnel, this looks like a promising opportunity.

But this is the point at which something I have seen repeatedly in B2B becomes important: the person most interested in buying the solution is not necessarily the person who will determine whether the organisation buys it.

The proposal begins moving through the company. The CFO knows Vendor B. He has never worked directly with it, but has seen the company at industry conferences and remembers reading some of its research. Procurement has dealt with Vendor B before, while somebody in IT recalls hearing one of its customers speak positively about an implementation.

The Head of Treasury still prefers Vendor A and nobody actively objects to it. The problem is simply that the other stakeholders know much less about the company.

This apparently small difference changes the decision. Vendor B is easier to explain internally because several people already possess fragments of evidence that make the company feel familiar. If the project subsequently encounters difficulties, everyone can understand why an established provider with visible customers, recognised expertise and a familiar name was selected.

Choosing Vendor A requires somebody to make a stronger case.

At this point, the question is no longer simply which provider has the best solution? It is also which provider can this group of people most comfortably agree to choose?

That is where Buyability becomes more useful than brand awareness as a concept.

LinkedIn and Bain describe a related phenomenon as FOMU, or Fear of Messing Up. Their research found that around 40% of B2B deals stall not because another supplier wins, but because the buying group cannot reach agreement. The expression may sound slightly informal for enterprise procurement, but anyone who has been close to a large B2B purchase will recognise the underlying behaviour.

Recommending a supplier involves professional as well as financial risk. If everything works perfectly, the organisation benefits; if things go badly, somebody may eventually have to explain why that particular company was selected. Under those circumstances, the safest decision is not always the cheapest provider or even the one with the objectively strongest product. It can be the provider whose selection is easiest to defend.

Does Buyability kill the marketing funnel?

No. But it does expose some of its limitations.

The familiar B2B funnel still describes useful operational stages:

Awareness → Consideration → Conversion → Opportunity → Customer

I still find those stages useful. Marketing teams need a way to organise activity, understand progression and measure commercial outcomes, and nothing about Buyability makes leads, opportunities or conversion rates suddenly irrelevant.

The problem begins when we mistake the funnel for a complete description of how a company buys.

Return to our treasury example. By the time Vendor A knew that the prospect existed, the Head of Treasury had already researched the category, consulted AI, spoken to peers, encountered expert content and formed an initial shortlist. Then, after the opportunity became visible to sales, several people who had never appeared anywhere in the marketing funnel acquired enormous influence over the final decision.

The CFO had never downloaded an ebook. Procurement had never clicked an advert. IT had never become an MQL. Nevertheless, each could contribute to Vendor A winning or losing the business.

The traditional model can be simplified as:

Visibility → Traffic → Lead → Nurture → Sales → Opportunity → Revenue

There is a comforting logic to it. Marketing attracts an audience, identifies interested prospects and progressively influences them until sales can take over. The prospect becomes increasingly visible to us as they move through the process.

An AI-mediated buying journey increasingly looks different:

Visibility + Reputation + Evidence → AI/Peer Discovery → Buying Group Familiarity → Defensibility → Shortlist → Sales → Revenue

The difference between those two models is more significant than the diagrams might suggest.

In the first, marketing progressively influences an identifiable prospect. In the second, marketing is also building an environment of confidence before the prospect becomes identifiable.

That environment may consist of a brand someone already recognises, research they have encountered, a customer recommendation, a conference presentation, an expert they follow, an independent mention or information that an AI system can retrieve and synthesise. None of these things needs to generate a lead at the moment it occurs. Their combined effect is to make the company easier to include on a shortlist and easier for a buying group to approve later.

None of this means that the dark funnel has suddenly appeared. It existed long before generative AI. What AI changes is the scale of the invisible territory. Research that once required ten Google searches, six website visits and perhaps a couple of downloaded reports can increasingly happen within a single AI conversation.

The funnel therefore remains useful for managing what happens once demand becomes visible. Buyability asks us to pay much more attention to what has to be true before that visibility occurs.

Marketing before there is a lead

For me, this is the most interesting implication of Buyability. A significant part of effective B2B marketing may increasingly need to happen before there is an identifiable prospect to market to.

We have always had a name for part of this activity: brand building. But the emerging model goes further, because the confidence surrounding a supplier is rarely created by brand activity alone. It accumulates through customers, experts, research, industry conversations, previous experience and the wider reputation of the company.

Look again at Vendor B. Its advantage did not come from one brilliant campaign or an exceptionally sophisticated piece of marketing automation. It had accumulated gradually. The CFO recognised the name, procurement already knew the company, a customer had spoken publicly about working with it and its expertise existed beyond its own website.

That wider body of credible information may also increase the likelihood that Vendor B is surfaced when an AI system is asked to identify or compare providers in the category. There is no simple formula guaranteeing that an LLM will recommend a particular company, but the underlying principle is increasingly important: a brand’s digital presence is no longer defined solely by what it publishes about itself. LinkedIn has explored this wider shift towards reputation as an increasingly important factor in AI-mediated B2B discovery.

None of these individual interactions necessarily generated a measurable lead when they happened. Together, however, they created something commercially valuable: they made Vendor B easier to buy.

This connects closely with something I have written about before. In complex B2B markets, trust is accumulated rather than captured. AI does not invalidate that principle; if anything, it makes it more important.

Once we look at marketing in this way, the roles of brand marketing, customer marketing and thought leadership begin to change.

Brand marketing becomes revenue infrastructure

For years, one of the most persistent tensions in B2B marketing has been the division between brand and demand generation. Brand creates awareness; demand generation creates leads; sales converts them into revenue.

It is an administratively convenient distinction, particularly when budgets and KPIs need to be allocated, but Buyability makes it increasingly difficult to defend as a description of how marketing actually creates commercial value.

Consider Vendor B again. The CFO’s familiarity with the company did not generate the opportunity. It did something that may ultimately have been more valuable: when the opportunity arrived, it reduced uncertainty around the decision.

This is where brand moves from being something that happens at the top of the funnel to becoming part of the infrastructure that allows the bottom of the funnel to work.

If several members of a buying group already recognise a vendor, understand roughly what it does and associate it with credible expertise, the internal discussion begins from a different position. The champion has less explaining to do. The unfamiliar supplier has to establish both its capability and its legitimacy; the familiar supplier can concentrate more quickly on proving fit.

This is particularly important in high-consideration B2B categories, where the perceived cost of making the wrong decision can be substantial. Familiarity does not guarantee that a supplier will win, and it certainly cannot compensate indefinitely for a weak product. But it can reduce the perceived risk of putting that supplier forward.

Seen in this way, brand marketing is not simply creating future demand. It is creating some of the conditions under which future demand can convert into revenue.

Customer marketing becomes acquisition marketing

The same logic changes the role of existing customers.

Most organisations still divide the customer journey quite neatly. Acquisition sits with marketing and sales; after the contract is signed, attention shifts towards onboarding, retention, expansion and customer success.

But in our example, one of the most influential marketing moments happened when somebody in IT remembered hearing a customer speak positively about Vendor B.

That customer was not part of the campaign. They did not generate a conventional conversion and may never appear in an attribution report. Yet their experience became evidence for another company’s buying group.

This is why I increasingly think the distinction between customer marketing and acquisition marketing is becoming artificial in B2B.

A good customer case study has always been useful sales collateral, but Buyability suggests a broader role for customer evidence. References, testimonials, conference appearances, peer conversations, independent reviews and customers simply being willing to associate their names publicly with a supplier all contribute to the environment of confidence surrounding that supplier.

This matters even more as AI becomes involved in discovery. A company can say almost anything about itself on its own website, and generative AI makes producing polished corporate claims easier than ever. Evidence that the market can corroborate elsewhere carries a different weight.

There is a considerable difference between a vendor repeatedly saying, “We are excellent at implementing complex treasury projects”, and a visible body of customers effectively saying, “We chose them, and this is what happened.”

The second does not merely support retention or advocacy. It can help create the next customer.

Customer marketing, in that sense, becomes part of acquisition.

Thought leadership changes purpose

Something similar happens with thought leadership.

I have always believed that good B2B thought leadership should do more than manufacture traffic, but the Buyability model gives that belief a clearer commercial explanation.

In a conventional content funnel, an article has an obvious job. Someone finds it through search or social media, reads it, perhaps downloads something else and eventually becomes a lead. The closer we can connect that sequence to an opportunity, the easier it is to demonstrate the article’s value.

But consider the article from Vendor B that one treasury peer sends to our Head of Treasury. Perhaps it was published eighteen months earlier. Perhaps the person who originally read it never became a lead at all. Its value lies elsewhere: it has become portable evidence of expertise.

The same article may also have been referenced by another industry website, discussed on LinkedIn, used by a salesperson in a conversation or surfaced by an AI system trying to understand which companies have credible expertise in that particular area.

Its purpose therefore extends beyond attracting an audience. It helps establish what the company knows.

This distinction becomes increasingly important as generative AI makes competent but generic content almost limitless. If every B2B company can publish ten perfectly acceptable articles a week, publishing ten perfectly acceptable articles a week stops being much of an advantage.

Original research, genuinely informed analysis, distinctive expertise and useful points of view become more valuable precisely because they are harder to manufacture.

The strategic question for thought leadership therefore changes from “How much traffic will this content generate?” to something closer to “Does this add credible evidence that we understand the problem we want to be hired to solve?”

Traffic still matters. Search visibility still matters. GEO matters increasingly too. But they become distribution mechanisms for something more fundamental: authority. This is also consistent with LinkedIn’s recent guidance on AI search visibility for B2B marketers, which places particular emphasis on original expertise and distinctive points of view rather than simply producing more content.

A substantial body of credible thought leadership becomes part of the evidence that future buyers encounter when they investigate a company, whether they find it directly, receive it from a colleague or encounter it indirectly through an AI-generated answer.

This is also why I would resist the temptation to respond to AI by simply producing more AI-generated content. As content production becomes cheaper, evidence becomes more valuable than volume.

And then there is measurement

There is an obvious problem with all of this, particularly for marketers who have spent years trying to demonstrate measurable contribution to revenue.

If Vendor B eventually wins our hypothetical contract, which activity deserves the credit?

Perhaps it was the conference the CFO attended eighteen months earlier, the customer recommendation, the article forwarded by a colleague, the LinkedIn discussion, the AI recommendation or procurement’s previous experience with the company. Eventually somebody will probably visit Vendor B’s website and request a meeting, at which point our analytics platform will produce a reassuringly precise attribution path.

The precision should not fool us.

We risk optimising B2B marketing towards the interactions that are easiest to measure while some of the interactions that actually make a company easier to buy happen elsewhere. This does not make attribution useless, but it should make us more modest about what attribution can genuinely tell us.

It is also why I do not see Buyability as a replacement for the funnel, ABM, demand generation or brand marketing. I find it more useful as a way of understanding how those disciplines connect.

The funnel describes progression towards a sale. Buyability describes the conditions that make that progression possible.

From being found to being chosen

There will inevitably be attempts to turn Buyability into another B2B marketing buzzword, and after enough years in marketing I have become instinctively sceptical whenever an old reality acquires a new name.

Buying committees are not new. Brand familiarity is not new. Peer recommendations are not new, and neither is risk reduction. Even the idea that much of a B2B buying journey takes place beyond the reach of marketing attribution has been discussed for years.

What has changed is the environment in which all of these things operate. Buyers can now conduct much more research without identifying themselves. AI increasingly mediates discovery and comparison. Buying groups remain complicated and, in markets where several competitors appear capable of solving the same problem, familiarity, evidence and confidence can become decisive.

That is why I think the move from visibility to Buyability matters.

The traditional B2B model assumes that marketing succeeds by attracting the right prospect and progressively influencing that prospect towards a commercial outcome. The emerging model asks marketing to do something in addition: create an environment in which the company is already credible before the prospect appears, already familiar to more than one member of the buying group and already supported by enough external evidence to make choosing it feel defensible.

Visibility therefore still matters. A company nobody knows is unlikely to become anybody’s preferred supplier. But visibility is increasingly the beginning of the process rather than its objective.

The question I find myself asking is no longer simply whether the right buyers can find a company. It is what they discover once they do, what their colleagues already know about it, what its customers say, whether its expertise exists beyond its own claims and, increasingly, what an AI system understands about its reputation.

Because eventually the buying group will have to make a decision, and at that point being found is not enough. The company has to feel like a choice that everyone around the table can defend.

That is the difference between being visible and being buyable.