This article was originally published in 2017 and was last updated on June 28, 2025.
- Tension: Marketers want to reach real buyers—but still rely on shallow engagement signals instead of real purchase intent.
- Noise: Legacy metrics like pageviews and display impressions distort how brands measure interest and allocate budget.
- Direct Message: In today’s market, technology isn’t just the product—it’s the proof. The content that drives revenue is the one that shows buyers are already buying.
To learn more about our editorial approach, explore The Direct Message methodology.
For years, marketers have operated on the assumption that content equals awareness, and awareness eventually becomes revenue. But the cracks in that model are showing—and nowhere more clearly than in B2B technology.
What TechTarget understood back in 2017 is even more relevant today: in tech marketing, the content is the pipeline.
Not the ads, not the forms, not the nurture streams. The actual, editorial content buyers engage with reveals what they’re in-market for—right now.
John Steinert, TechTarget’s CMO, called it “purchase decision support.” But in practice, it’s a system of signals—a way to read buying behavior from behavior-rich content interaction.
If someone browses five unrelated blog posts, that’s interest. But if a named buyer from a target account spends 30 minutes across multiple pages on enterprise cloud migration? That’s intent.
This distinction is key: behavior without identity is noise. But when behavior is known, contextual, and repeated across buying committees, it becomes something else entirely—forecastable demand.
In a landscape where budgets are shrinking and scrutiny is rising, guessing is expensive. Sales teams can no longer afford to chase content-induced “maybe” signals. They need “almost certainly” ones.
The myths we still believe about digital engagement
Legacy marketing still leans heavily on high-funnel numbers: impressions, clicks, bounce rate. These KPIs may make dashboards look impressive, but they’re often divorced from what actually closes deals.
This disconnect persists partly because media channels—and many marketers—still sell reach as value.
But reach is cheap now. AI-generated content floods the feed. Display ads chase users across sites they didn’t consent to. Social metrics are inflated by bots and short attention spans.
Even “engagement” has been diluted. Someone liking a whitepaper teaser doesn’t mean they want a demo. A VP watching one webinar doesn’t signal budget approval.
Without deeper context—such as identity, repetition, and topic depth—engagement is just noise.
And it’s not just an issue of digital marketing metrics—it’s a mindset challenge. CMOs and CROs are often speaking different languages when reviewing campaign results. One sees MQLs; the other sees wasted outreach.
But when engagement is aligned with account-level behavior—tracked over time and across topic clusters—it becomes a translator between marketing and sales. It doesn’t just answer “who’s active?” It answers “who’s deciding?”
The Direct Message
In today’s market, technology isn’t just the product—it’s the proof. The content that drives revenue is the one that shows buyers are already buying.
A model that scales only with meaning
TechTarget’s model may not work for every industry—but the principle it’s built on absolutely does: meaningful engagement from identifiable users is more valuable than mass awareness from anonymous traffic.
Consider this: TechTarget’s “Priority Engine” doesn’t just track site behavior—it maps it to actual accounts, assigning tiers of intent based on depth, frequency, and topical relevance. These aren’t just leads—they’re deal signals.
When Cisco or McAfee look at those dashboards, they’re not asking “Who clicked?” They’re asking, “Who’s in the market?”
This approach helps shorten sales cycles, optimize SDR outreach, and align ABM teams on warm accounts instead of cold prospects. It also pushes brands to create content not just to “educate” the market—but to observe and respond to market signals in real time.
In sectors with long buying cycles—like healthcare, industrial tech, or enterprise software—this is gold. Content no longer functions as a message; it functions as a mirror.
From cost center to intelligence engine
Another reason TechTarget’s approach remains relevant today? It reshapes content’s role in the org chart.
Traditionally, content marketing is seen as a cost center: a branding play or top-of-funnel driver. But if your content reveals who’s most likely to buy—and which messages or formats are triggering that shift—then it becomes a revenue intelligence engine.
This is where modern CMOs need to lead. Instead of treating content as a separate discipline from sales enablement or pipeline forecasting, they should treat it as the connective tissue.
The story buyers follow is the trail revenue teams should study. And the trail begins with what they read, download, share, or rewatch—at scale, and with clarity.
Even better: this allows marketers to reverse-engineer high-converting content. If a piece consistently signals in-market behavior among decision-makers, it’s not just valuable content—it’s a predictive asset. That’s the difference between publishing and precision.
Why this still matters in 2025
In 2025, the buying journey is even more fragmented. Stakeholders are harder to reach. AI-generated “research” clouds every search. And buyers avoid sales calls until they’re nearly done deciding.
That means the only true early warning system you have is behavior—specifically, content interaction mapped to intent models. The marketers who win aren’t the ones making louder noise. They’re the ones listening harder.
And here’s where the headline becomes the deeper truth: technology isn’t just the thing being sold—it’s how we understand who’s ready to buy it. In this context, marketing tech isn’t separate from the sale—it is the sale.
So yes, TechTarget’s model is expensive. But so is guessing.
