B2B tech marketers are under pressure to support sales by providing warm leads, buyer intent signals and create “pipeline velocity”. B2B intent data can support that work but only if marketers remember that buyer interest and buyer receptivity are not the same thing.

If a publisher or intent platform can identify the minority of enterprise tech buyers that appear to be actively researching a new product or service, paying to reach them can look like a smart use of budget compared to broader awareness-raising activities where it is hard to create attribution. But are B2B tech marketers getting good value for money? This access is not cheap and buyers may not actually be receptive given that they are already bombarded with propositions. Even if the marketing content they receive is relevant or useful, is it being well received? Is it even timely? 

What you can and cannot infer from B2B intent data 

B2B intent data is behavioural information that suggests an organisation or individual may be researching a topic, product category or business problem. It can come from first-party sources such as website visits, email engagement and form fills, or third-party sources such as publishers, content syndication platforms and data providers. In our view, it’s use is limited. Intent data can help marketers prioritise accounts, shape messaging and identify topics that may matter to a buying group. However, it does not prove budget, authority, timing or willingness to speak to sales.

Gartner estimates two-thirds of B2B tech buyers prefer a rep-free experience, and 45% said they used AI during a recent purchase. In other words, many buyers are actively trying to educate themselves on their own terms before they want outreach.

None of this means targeting is wrong. In complex B2B technology services, it makes perfect sense to tailor messaging for different buying roles, sectors, and account contexts. Different stakeholders need different messages, and targeted content can help sales and marketing focus effort where it matters most. But there is a difference between relevant content and the assumption that a detected intent signal makes contact welcome.

Why precision is not the same as relevance

Content syndication and intent monitoring are typically sold as precision tools, but their value depends on several things going right at once. The data has to be meaningful, the timing has to be right, the content has to feel genuinely useful rather than mechanical, and the follow-up has to match the buyer’s stage of research. And the cost of access has to be justified by outcomes, not just activity.

Some intent platforms can cost more than $10,000 per month and data quality and accuracy vary by provider and methodology. That does not make intent data useless but it does mean marketers should be wary of treating signals as the same as buying readiness.

There is also a market dynamic worth considering. If several vendors are buying access to the same supposedly in-market audience through the same publishers and data platforms, then everyone is paying a premium for the same attention. That can still work for a narrow set of strategic accounts. But as a broader content strategy, it does raise a question about diminishing returns.

From the buyer’s perspective, the experience can be intrusive. They read a few articles, download a paper, or spend time researching a problem, and suddenly they are being followed by ads, and sponsored content that highlights just how visible their behaviour has become. Even if the targeting is technically compliant because they ticked a box three years ago, it can still feel intrusive. And if the content itself is only lightly personalised, with a role title or industry label swapped in, the campaign has not become more relevant.

Using AI to create multiple versions of an asset for different roles or sectors is not inherently a bad idea. It can be useful when it reflects real differences in pressures, incentives, language, and decision criteria. But if the adaptation is mostly cosmetic, the result is still generic content. A CFO, CIO, operations lead and CISO may all care about the same technology decision, but they assess it through different lenses. Cost exposure, integration risk, operational disruption and governance all shape how the content should be framed. Swapping the job title in the introduction does not address those differences.

Self-service buying changes the role of content

AI does have a role in self-service, though. As buyers use AI search and conversational tools more often, marketers may get more value from being easy to find and easy to trust than from paying to interrupt a narrow audience at a premium. The opportunity may be less about producing more variations of the same asset and more about creating material that helps buyers frame the problem before they are ready to fill in a form or speak to sales.

And this will become more important as more transactions are performed digitally. Forrester predicted that more than half of large B2B transactions worth $1 million or more would be processed through digital self-serve channels in 2025. Human selling didn’t disappear but it does suggest that discoverability, credibility, and usefulness before direct contact matter more than many campaign plans admit.

We believe that strong thought leadership and well-judged educational content still have an advantage. Edelman and LinkedIn’s 2024 B2B Thought Leadership Impact Report found that 73% of decision-makers see thought leadership as a more trustworthy basis for assessing an organisation’s capabilities than its marketing materials and product sheets. The same report found that three quarters had researched a product or service they were not previously considering after encountering strong thought leadership. That is a reminder that good content can shape demand before a buyer is in a buying phase.

How to use targeting without alienating buyers

So the issue with hyper-targeted content is not that targeting never works, but many programmes are priced and positioned as if identification automatically creates permission, and as if precision automatically improves ROI, and clearly it cannot promise that.

A better approach is to use intent data as a guide to relevance but not as a carte blanche to hound your would-be customer. If an account is showing interest in a topic, ask what would help that buying group understand the problem more clearly. That might be a practical explainer, a decision framework, a comparison guide, a credible point of view, or content that helps internal champions explain the issue to colleagues.

The test should be simple: would the buyer choose to read this content even without being chased? If the answer is no, targeting may improve delivery but it will not fix the offer.

So can Futurity help me create content that will hit the mark?

Creating the right assets starts with the buyer’s question, not the campaign format. Futurity works with B2B technology companies to identify what buyers need to understand at each stage of the decision, then shapes the content around that stage. That might mean an ungated article for discovery, a white paper for deeper education, a role-specific ABM asset for a named account, or a sales enablement piece that helps account teams continue the conversation with more relevance and less pressure. Drop us a line at [email protected] or call +44 20 8323 3287 for a no-strings-attached chat.