There is perhaps no more frustrating phrase in B2B marketing right now than “high intent.” Find the high-intent accounts. Target people showing intent. Prioritize buyers who are in-market. Give Sales the accounts most likely to buy. Every marketing platform seems to promise some version of this, and every demand generation conversation eventually arrives at the same place. It sounds wonderfully logical. Why waste money talking to thousands of companies when you can identify the few hundred that actually want what you sell? There is just one small problem: how in the world do you actually know who has intent?
Someone visits your website three times. Is that intent? Someone downloads a whitepaper. Intent? A company suddenly starts researching “data governance.” Intent? A CIO likes a couple of LinkedIn posts about AI. Someone attends your webinar but leaves after twenty minutes. Someone else visits your pricing page but never returns. A company you’ve never spoken to suddenly has four different employees visiting your website in the same week. Which of these people wants to buy? Which is merely curious? Which is a competitor? Which is doing research for a presentation? Which is a consultant researching on behalf of somebody else? And which is quietly six months into a buying process you know absolutely nothing about?
This is what makes intent so frustrating. We have never had more data about buyer behaviour, yet understanding what buyers actually intend to do remains remarkably difficult.
Marketing technology can tell us an extraordinary amount today. We know which pages people visit, which emails they open, which ads they click, which webinars they attend and which content they download. Third-party intent platforms can tell us which topics companies appear to be researching. Review platforms can show when buyers are comparing categories and vendors. LinkedIn gives us engagement signals. Search tells us what people are looking for. Our CRM contains years of interactions, opportunities, lost deals and conversations. And increasingly, there is another enormous part of the journey happening inside ChatGPT, Gemini, Perplexity and other AI interfaces that marketers may barely see at all.
The problem is that none of these things are actually intent. They are signals.
A website visit is behaviour. A search is behaviour. A download is behaviour. Reading a Gartner report is behaviour. Following a company on LinkedIn is behaviour. Even visiting a pricing page is behaviour. Intent is the meaning behind all of those behaviours, and meaning is much harder to put into a dashboard.
Think about how you buy something yourself. Imagine your company needs a new CRM. Perhaps the thought first occurs to you in January after another frustrating sales meeting. You read an article about CRM problems. Nothing happens. In February you notice a LinkedIn post from somebody describing exactly the problem you’re experiencing. You save it. In March you’re too busy to think about it. In April someone on your team mentions HubSpot. In May you ask ChatGPT to compare modern CRM platforms. In June you visit three vendor websites. In July you bring the issue up with your CFO. In August you ask two vendors for demonstrations.
When did your intent begin?
January, when you recognized the problem? April, when someone suggested an alternative? May, when you started actively researching? June, when you visited vendors? Or August, when you finally raised your hand?
The uncomfortable answer is that there probably wasn’t a moment. Intent accumulated.
And this is where I think much of B2B marketing gets intent wrong. We keep looking for a magical signal that tells us THIS COMPANY WANTS TO BUY, when buying intent is more likely to be a pattern that gradually becomes clearer. One website visit tells you almost nothing. One content download tells you slightly more. One person repeatedly researching a problem becomes interesting. Three people from the same company researching the same problem becomes considerably more interesting. Add competitor research, product-page visits, a recent leadership change and an increase in activity over the last fourteen days, and suddenly you’re not looking at a signal anymore. You’re looking at a story.
Gartner has written extensively about buying groups and the complexity of B2B buying decisions. Gartner — B2B Buying Journey
So how in the world do you figure out the best intent?
I think the answer begins by accepting that there is no single best intent signal. The best indication of intent is usually the intersection of several things: fit, behaviour, context, frequency, recency and change. A company researching your category means very little if it could never realistically buy your product. Twenty website visits from a 20-person startup aren’t particularly useful if you sell $500,000 enterprise software. Intent without fit is mostly noise. So before asking whether somebody is showing intent, marketers should ask a much simpler question: if this company wanted to buy tomorrow, would we actually want to sell to them?
Then comes behaviour, but behaviour needs hierarchy. Someone reading “What is data governance?” is giving you a very different signal from someone searching “best enterprise data governance platforms.” That person is different again from someone searching your brand, visiting your integration pages, reading a customer story and then looking at pricing. These actions represent different stages of thinking. One is learning about a subject. Another is recognizing a problem. Another is exploring solutions. Another is evaluating vendors. The closer behaviour moves toward solution and vendor evaluation, the stronger the conventional buying-intent signal becomes.
For the intent-data Bombora is particularly relevant because its business is built around company-level intent signals. Bombora
But there is something important hidden at the other end of that journey. The person reading “What is data governance?” may not have buying intent yet. But something they read today could make them realize that the problem they’ve been tolerating for two years is actually solvable. That realization can create intent. And that brings us to a distinction I think B2B marketing needs to spend much more time thinking about.
Finding intent and creating intent are not the same thing.
The B2B marketing industry has become extraordinarily good at hunting for existing demand. We buy Google Ads against high-intent keywords. We retarget website visitors. We monitor review sites. We buy third-party intent data. We identify accounts researching our categories. We score leads and accounts. We send SDRs after anyone whose digital behaviour suggests they might be getting close to a purchase.
All of this can work.
But if everyone is chasing the same high-intent buyer, something interesting happens. Ten vendors discover the same account at roughly the same time. Ten sales teams start prospecting. CPCs rise because everybody wants the same keywords. Review sites become battlegrounds. LinkedIn audiences overlap. Your supposedly wonderful high-intent prospect suddenly has fourteen vendors trying to schedule a meeting.
If you’re only targeting people showing intent, you’re often competing for demand somebody else created. That, to me, is the much more interesting marketing problem.
How do you make someone who wasn’t searching start searching? How do you make a CFO recognize a cost they had previously accepted as normal? How do you make a CIO question an architecture they thought was good enough? How do you give a CEO language for a problem they could feel but couldn’t articulate? How do you take someone from “this isn’t a priority” to “we should probably look into this”?
That is intent creation.
A provocative piece of research can do it. A great LinkedIn post can do it. A customer story can do it. An analyst report can do it. A conversation with a peer can do it. An event can do it. A regulatory change can do it. A competitor’s success can do it. Increasingly, an answer from an AI system can do it. Great marketing doesn’t merely stand at the bottom of the funnel waiting for people to arrive. It changes what people think about before they enter the funnel.
Also read. https://sociallistener.in/we-buy-identity-not-products-why-product-positioning-is-identity-design/
And perhaps this is why brand and demand generation were never as separate as we made them appear. Brand creates familiarity before the search. Thought leadership creates the problem vocabulary. Content creates understanding. Social creates repeated exposure. Search captures curiosity. Intent data identifies acceleration. Sales converts that momentum into a conversation. These aren’t separate marketing activities. They are different moments in the formation of intent.
The signal I would watch most closely is change.
If I were trying to identify the best B2B intent today, I wouldn’t simply rank accounts by how much activity they generate. I would look for acceleration. A company visiting your website thirty times over six months might simply know your brand. Another company might have visited once three months ago, twice last month, four times last week and twelve times this week. The second account interests me much more because something has changed.
The same principle applies outside your website. A new CIO joins. The company raises money. It announces expansion into another country. It starts hiring data engineers. A new regulation affects its industry. It acquires another company. Its technology stack changes. Several employees suddenly begin researching the same category. Three people from different departments engage with your content within two weeks. Individually these events may mean very little. Together they can suggest that something is moving inside the organization.
This is particularly important in enterprise B2B because companies don’t buy; groups of people inside companies buy. The person who first discovers your content may never speak to Sales. The analyst researching your solution may not control the budget. The CIO who eventually signs off may never download your ebook. Procurement may arrive at the very end. Finance may appear only when the business case is presented. Looking for intent at an individual level can therefore hide what is happening at the account level.
One person researching your category could be curiosity. Five people from the same company, across business, technology and leadership, researching the same problem over three weeks is something else entirely.
That’s why I think the future of intent marketing isn’t going to be about finding the signal. It will be about connecting hundreds of weak signals well enough to recognize the pattern.
And AI should make this considerably more interesting. Instead of simply saying Account X has an intent score of 82, imagine a system explaining: Interest from this account has increased 4x in the last 21 days. Three senior employees have engaged with content around the same problem. Two product pages have been visited repeatedly. The company recently appointed a new CIO and is hiring for five roles related to the category. Similar accounts historically entered an opportunity within 60 days.
That is much closer to something a marketer can actually use.
Because an 82 isn’t insight. The story behind the 82 is.
And maybe that’s where B2B intent needs to go next. Less obsession with scoring every click. Less pretending that downloading an ebook means someone wants a sales call. Less chasing isolated signals across fifteen different platforms. Instead, understand the company. Understand the people. Understand what changed. Connect the behaviours. Look for acceleration. Look for multiple people moving around the same problem. And then ask the question that perhaps matters most:
Are we seeing intent or are we creating it? The best B2B marketers will probably learn to do both.
