Intent-Based Marketing: Stop Chasing Signals, Start Building Strategy

Intent-based marketing is the practice of targeting buyers based on behavioural signals that suggest they are actively researching or considering a purchase. Done well, it concentrates budget on high-probability prospects and reduces wasted spend. Done poorly, it becomes an expensive exercise in chasing the same finite pool of in-market buyers that every competitor is already bidding on.

The promise is real. The execution is where most marketing teams lose the plot.

What Intent-Based Marketing Actually Means

Intent-based marketing uses signals, typically browsing behaviour, content consumption, search queries, and third-party data aggregated across publisher networks, to identify buyers who appear to be in an active research or purchase cycle. The logic is straightforward: if someone has been reading comparison articles, downloading product guides, and visiting competitor websites, they’re probably closer to a buying decision than someone who hasn’t done any of that.

In B2B, this has become a significant industry. Platforms like Bombora, G2, and TechTarget sell intent data that tracks which companies are “surging” on specific topics. The idea is that if a company’s employees are consuming a lot of content about, say, marketing automation, that company is likely evaluating marketing automation vendors. You should reach them now, before they’ve already made up their minds.

In B2C and performance marketing, intent signals are more granular: search queries with commercial modifiers, cart abandonment, product page visits, comparison shopping behaviour. These are closer to the point of purchase and, in many cases, more reliable as predictors of near-term conversion.

Both versions rest on the same underlying assumption: that reaching someone at the moment of highest intent gives you the best chance of winning their business. That assumption is largely correct. The problem is what gets sacrificed in pursuit of it.

The Performance Marketing Trap I Fell Into Early On

Early in my career, I was a true believer in lower-funnel performance. The numbers were clean, the attribution was (apparently) clear, and the efficiency metrics looked excellent. When I was running paid search and performance campaigns for clients, we could show a cost per acquisition, a return on ad spend, and a clear line between spend and revenue. It felt like proper accountability.

It took me years to properly interrogate what those numbers actually meant. A significant portion of what performance marketing gets credited for converting would have converted anyway. Someone who types a brand name into a search engine and clicks a paid ad instead of the organic listing below it is not a customer who was won by the ad. They were already coming. We just charged the client for the click.

Intent-based marketing has the same structural risk. When you concentrate your entire budget on people who are already in-market, you’re not building demand. You’re harvesting it. And harvesting is not the same as farming. You can only harvest what you’ve grown, and if you haven’t been growing anything, you’ll eventually run out of crop.

I’ve seen this play out repeatedly across the agencies I’ve run. A business comes in with strong short-term numbers, excellent cost per acquisition, and a growing concern that their pipeline is thinning. They’ve optimised their way into a corner. The intent-capture machine is running efficiently, but the pool of people with intent is shrinking because nothing is being done to create it.

Where Intent Data Is Genuinely Useful

None of this is an argument against intent-based marketing. It’s an argument for using it correctly, which means understanding what it can and cannot do.

Intent data is most valuable in three specific situations.

First, it’s useful for prioritising sales outreach in B2B. If you have a list of 500 target accounts and limited sales capacity, knowing which 50 are currently showing elevated research activity lets you focus your team’s time where conversion probability is highest. That’s a legitimate and commercially sensible use of intent signals. The intelligent growth model Forrester has articulated for years is partly built on this kind of prioritisation logic.

Second, intent data improves the timing of outbound sequences. Sending a cold email to a prospect who has just been consuming content about your category is not the same as sending that email into the void. The signal doesn’t guarantee interest, but it improves your odds. It’s the difference between calling someone who has just walked into a showroom versus calling someone who has never thought about buying a car.

Third, intent signals can sharpen paid media targeting. In B2B programmatic specifically, overlaying intent data on top of firmographic targeting can improve the quality of the audience you’re reaching. You’re still doing broad awareness work, but you’re doing it against an audience that’s more likely to be receptive right now.

The common thread across all three is that intent data is being used to sharpen timing and prioritisation, not to define the entire addressable market. That’s the correct mental model.

If you’re working through how intent marketing fits into a broader go-to-market approach, the Go-To-Market and Growth Strategy hub covers the full framework, from audience segmentation to channel strategy to growth measurement.

The Problem With Third-Party Intent Data Specifically

Third-party intent data deserves particular scrutiny, because the marketing around it is considerably more confident than the underlying methodology warrants.

The way most B2B intent data works is that a data provider aggregates content consumption across a network of publisher websites. When employees at a particular company consume content related to a specific topic at a higher-than-normal rate, that company is flagged as “surging” on that topic. The assumption is that this signals active evaluation.

There are several problems with this.

Coverage is uneven. The intent signal is only as good as the publisher network the data provider has access to. If your buyers are consuming content on platforms outside that network, which is most of the internet, you won’t see it. The data you’re getting is a partial view at best.

Noise is significant. A company showing elevated activity on a topic might have a new analyst who’s been asked to research it, a journalist writing a piece about it, or an employee who’s just personally curious. Elevated content consumption is not the same as active vendor evaluation.

Timing is imprecise. Even when the signal is genuine, you often don’t know where in the buying cycle the company actually is. They might be six months from a decision, or they might have already made one. The surge data doesn’t tell you that.

I’ve sat in enough agency reviews where intent data was being presented as near-certain buying signals to know that the gap between how it’s sold and how it performs is real. Use it as a directional indicator. Don’t build your entire go-to-market motion around it.

First-Party Intent Signals Are a Different Story

Where intent data becomes genuinely powerful is when it’s first-party. Behavioural signals from your own website, your own product, your own email engagement, these are far more reliable than anything a third party can sell you.

Someone who has visited your pricing page three times in two weeks is showing you intent. Someone who has opened every email in your nurture sequence and clicked through to your case studies is showing you intent. Someone who has started a free trial and reached the activation milestone is showing you intent. These signals are clean, they’re contextual, and they’re directly relevant to your specific product and buying process.

When I was growing an agency from 20 to 100 people, we didn’t have access to sophisticated intent platforms. What we had was careful attention to which prospects were engaging with our proposals, which clients were asking questions that signalled expansion opportunity, and which inbound leads were showing the kind of engagement patterns that correlated with conversion. That was intent-based marketing before it had a name. It worked because the signals were real and we understood what they meant.

The best intent-based marketing programmes I’ve seen are built on a foundation of first-party signals, with third-party data used selectively to extend reach into accounts that haven’t yet engaged directly. That sequencing matters.

Intent Marketing Without Demand Creation Is a Shrinking Strategy

There’s a version of intent-based marketing that works extremely well in the short term and quietly destroys growth potential over the medium term. It looks like this: a business identifies the in-market buyers in its category, concentrates budget on reaching them, converts at a high rate, and reports excellent efficiency metrics. The CMO is happy. The CFO is happy. Two years later, the pipeline is thin and nobody can quite explain why.

What happened is that the business stopped investing in the part of marketing that creates future intent. Brand awareness, category education, thought leadership, the kind of content that makes someone think of you first when they eventually do enter the market, all of that was deprioritised in favour of capturing existing demand.

There’s a simple way to think about this. At any given moment, a small percentage of your total addressable market is actively in-market. Various estimates put this at somewhere between 3% and 10% depending on category, buying cycle length, and market maturity. Intent-based marketing, in its pure form, is competing for that small slice. The rest of the market, the 90%+ who aren’t actively buying right now, is being ignored.

Those people will eventually be in-market. When they are, they’ll buy from whoever they already know and trust. If you’ve spent two years talking only to people who were already looking, you’ll have no presence in the minds of the people who are just now starting to look.

This is the fundamental tension in intent-based marketing. The more precisely you target existing intent, the less you’re doing to build future intent. A healthy go-to-market strategy requires both. The allocation between them depends on your category, your competitive position, and your growth stage. But the allocation should be a deliberate choice, not a default that happens because intent targeting is easier to measure.

BCG’s work on brand and go-to-market strategy makes a related point about the interplay between brand-building and commercial activation. The two functions are not in competition. They’re sequential. You build brand so that commercial activation has something to work with.

How to Build an Intent-Based Marketing Programme That Actually Works

If you’re going to invest in intent-based marketing, here’s how to do it in a way that drives genuine commercial outcomes rather than just flattering your short-term metrics.

Start with your own data. Before you spend anything on third-party intent platforms, audit what your own systems are telling you. Your CRM, your website analytics, your email platform, and your product data (if you have a product) contain intent signals you’re probably underusing. Map the behavioural patterns that correlate with conversion in your existing customer base, then build your targeting and scoring models around those patterns.

Define what intent actually means for your category. Intent signals vary significantly by industry and buying cycle. In a category with a three-month sales cycle, someone downloading a comparison guide is a meaningful signal. In a category with an 18-month cycle, that same action might be early-stage research with no near-term commercial implication. Calibrate your response to the signal based on what it actually means in your specific context.

Build a tiered response model. Not all intent signals warrant the same response. A prospect who has visited your pricing page and requested a demo gets a different response than one who has downloaded a top-of-funnel guide. Map your signals to response tiers and build the content, outreach sequences, and sales plays that correspond to each tier. This is where intent marketing becomes genuinely useful rather than just a targeting exercise.

Protect your demand creation budget. Set a floor for investment in brand awareness and category education, and protect it from being raided every time someone wants to improve short-term conversion metrics. The exact split depends on your situation, but if you’re spending more than 70% of your marketing budget on capturing existing intent, you’re probably underinvesting in creating future intent.

Measure the right things. Intent-based programmes tend to produce excellent conversion metrics because they’re targeting people who were already likely to convert. Don’t let those metrics become the primary evidence of marketing effectiveness. Track pipeline coverage, new logo acquisition, category share of voice, and the quality of your top-of-funnel alongside your conversion rates. A complete picture is more useful than a flattering one.

Growth hacking literature often treats intent signals as a shortcut to scale. The growth hacking playbook has its merits in specific contexts, but it tends to optimise for speed at the expense of sustainability. Intent marketing done right is not a shortcut. It’s a precision layer on top of a broader growth strategy.

Intent Marketing in B2B Versus B2C

The mechanics of intent-based marketing differ significantly between B2B and B2C, and conflating them leads to poor decisions.

In B2C, intent signals are generally cleaner and closer to the point of purchase. Search queries with transactional intent, product page visits, cart abandonment, these are high-signal behaviours that reliably predict near-term purchase intent. The gap between signal and action is short. The challenge in B2C intent marketing is usually competitive: everyone is bidding on the same signals, which drives up costs and compresses margins.

In B2B, the picture is messier. Buying cycles are longer, buying committees are larger, and the signals are more ambiguous. A contact downloading a whitepaper might be a junior analyst with no purchasing authority, a consultant doing background research, or a genuine decision-maker in active evaluation mode. The signal looks the same. The commercial implication is completely different.

This is why B2B intent marketing requires a more sophisticated response model than B2C. You need to layer intent signals with firmographic qualification (is this the right type of company?), persona qualification (is this the right type of person?), and engagement depth (how much have they actually engaged, and with what?) before you can make a confident judgement about where to invest sales time.

I’ve judged the Effie Awards and reviewed hundreds of marketing effectiveness cases. The B2B cases that consistently perform well are not the ones that have the most sophisticated intent targeting. They’re the ones that have the clearest understanding of their buying process and have built their marketing to support every stage of it, not just the stage where intent is already visible.

BCG’s work on go-to-market strategy in complex categories illustrates how even highly technical, long-cycle B2B markets require a multi-stage approach that doesn’t rely solely on capturing late-stage intent.

The Measurement Problem Nobody Talks About

Intent-based marketing has a measurement problem that the industry is largely reluctant to discuss openly.

When you target people who are already showing buying intent and they convert, how much of that conversion is attributable to your marketing? Some of it, certainly. You were in the right place at the right time with the right message. But some of those buyers would have found you anyway. Some would have converted regardless of whether you’d targeted them with intent-based ads. The counterfactual is unknowable, which means the attribution is always an approximation.

This doesn’t make intent-based marketing worthless. It makes the measurement of it imprecise, which is true of most marketing. The mistake is treating the attribution as exact when it isn’t. I’ve sat in too many board meetings where intent-based campaign results were presented with a precision that the underlying data simply didn’t support.

Honest approximation is more useful than false precision. If your intent-based programme is generating pipeline at a cost that makes commercial sense, and your overall business is growing, that’s a reasonable signal that it’s working. You don’t need to claim that every converted prospect was solely won by your targeting to make the case for the investment.

The businesses I’ve seen get this right are the ones that hold their measurement frameworks lightly. They use the data to make better decisions, not to construct narratives. There’s a difference between using analytics as a perspective on reality and treating it as reality itself. Intent marketing data, like all marketing data, is the former.

If you’re thinking about how intent-based marketing connects to your broader growth architecture, the Go-To-Market and Growth Strategy hub covers the strategic foundations that make individual tactics like intent targeting actually pay off.

What Good Intent-Based Marketing Looks Like in Practice

The best intent-based marketing programmes I’ve encountered share a few characteristics that are worth making explicit.

They’re connected to sales. Intent data that sits in a marketing platform and never informs a sales conversation is wasted. The programmes that work have tight integration between marketing’s intent signals and sales’ outreach priorities. When a target account starts surging, the relevant account executive knows about it, knows why it matters, and has a relevant reason to reach out. That requires process design, not just technology.

They’re built on a clear ICP. Intent data is most useful when you know exactly who you’re looking for. If your ideal customer profile is vague, intent signals become noise because you can’t distinguish between a high-value prospect showing intent and an irrelevant company showing the same signal. Sharpening your ICP before investing in intent data is not a prerequisite that can be skipped.

They have a content infrastructure to support them. Reaching someone at the moment of intent is only valuable if you have something relevant to say. If your content library consists of generic thought leadership that doesn’t address the specific questions a buyer in active evaluation mode would have, your intent-based targeting will drive traffic to content that doesn’t convert. The content has to be built for the moment, not just the audience.

Creator-led content strategies, as explored in resources like Later’s go-to-market with creators framework, are increasingly relevant here. When intent signals suggest a buyer is in active research mode, authentic content from credible voices in your category can be more persuasive than brand-produced content. The format matters as much as the targeting.

They treat intent as a starting point, not a closing argument. The best programmes use intent signals to open conversations, not to assume the sale is imminent. A buyer showing intent still needs to be convinced that your solution is the right one, that your company is trustworthy, and that the timing is right for them. Intent gets you in the room. What you do in the room is still the work.

About the Author

Keith Lacy is a marketing strategist and former agency CEO with 20+ years of experience across agency leadership, performance marketing, and commercial strategy. He writes The Marketing Juice to cut through the noise and share what works.

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