This article was based on the interview with Chris Golec, Founder & CEO at Channel99 by Greg Kihlström, AI and Marketing Technology keynote speaker for the B2B Agility with Greg Kihlström podcast. Listen to the original episode here:
As marketing leaders, we’ve become accustomed to a certain rhythm, a familiar set of metrics that have guided our strategies for the better part of two decades. We speak fluently in the language of clicks, conversions, and cost-per-lead. There’s a certain comfort in these numbers; they are tangible, easily digestible, and have long served as the bedrock of our performance dashboards. For years, we’ve relied on the comforting, if slightly misleading, glow of a healthy click-through rate to justify spend and demonstrate momentum. But we also know, with the certainty that comes from experience, that this is an incomplete story. The B2B buyer’s journey has never been a straight line from ad to click to form-fill. It’s a winding, complex path of discovery, influence, and consideration that mostly happens out of sight.
The simple truth is that our obsession with the click has created a massive strategic blind spot—what many now call the “dark funnel.” This is the vast, unmeasured space where prospects engage with our brands, consume our content, see our ads, and discuss our solutions with their peers, all without ever clicking on a UTM-tagged link. By focusing solely on the 1% who click, we are ignoring the 99% of our target audience who are influenced through other means. This isn’t just a measurement gap; it’s a fundamental misunderstanding of how modern B2B marketing works. Fortunately, new applications of AI and a more sophisticated approach to attribution are finally allowing us to illuminate this journey, moving us beyond last-click models to understand true influence and impact.
The 10% Signal Problem
The core issue with a click-centric worldview is that it dramatically overvalues a single, low-frequency action while ignoring a wealth of more subtle, but equally important, engagement signals. In a world saturated with digital advertising, the act of clicking has become less common, especially among senior decision-makers who are adept at finding information on their own terms. They might see an ad on LinkedIn during their morning coffee, search for the company directly later, and visit the website without ever being “tracked” in the traditional sense. In this scenario, last-click attribution would incorrectly credit “Direct” or “Organic Search” for the visit, completely missing the initial, influential touchpoint. Chris Golec frames this as a problem of signal versus noise.
“I think clicks feels good for marketers, right? Like paid search. It’s, you know, I only pay for the clicks, right? But, you know, 85% of those are from people or companies that will never buy anything. Number one. Number two, you know, clicks are probably 10% of the signal online. And so, you have to be able to capture not only what’s happening on your website, but what’s happening off your website.”
Golec’s point is critical for enterprise leaders. We are often making multi-million dollar budget decisions based on what amounts to, at best, 10% of the available data. The most valuable intent signals often happen off-site—a prospect viewing your company’s G2 profile, comparing you to a competitor, or engaging with an executive’s thought leadership post on social media. These are high-value actions that indicate genuine interest and consideration, yet they generate no clicks and are therefore invisible to traditional measurement frameworks. The strategic imperative is to shift our focus from capturing a single action to understanding the cumulative effect of all brand impressions and engagements across the entire digital ecosystem.
Illuminating the “Direct” Traffic Mystery
Every marketing leader is familiar with the “Direct” traffic line item in their analytics report. It’s often one of the largest sources of website visits, yet it’s also the most enigmatic. For years, we’ve accepted it as people simply typing our URL into their browser. The reality, as Golec explains, is far more nuanced. Much of this traffic is, in fact, the direct result of marketing activities that didn’t generate a click. This is where AI-powered view-through attribution comes in, connecting the dots between an ad impression or a social media view and a subsequent website visit, even if no click occurred.
“I’m willing to bet that every B2B marketer that’s listening to this podcast, the majority of their traffic gets thrown in this bucket called direct. Meaning they just came to the website. The reality is they probably saw an ad, read a white paper, did something and came to the site. And the source is really unknown… you’d be surprised, but it’s probably four to five times the amount of engagement or signal than looking at just clicks.”
This is a game-changer. The ability to de-anonymize “direct” traffic and correctly attribute it to the influencing channel provides a radically more accurate picture of campaign performance. Suddenly, a display ad campaign that had a low CTR but drove significant view-through traffic and engagement from target accounts is revealed as a powerful awareness driver. A thought leadership series on LinkedIn that received likes but few link clicks can now be directly tied to subsequent visits to high-value pages on your site. By uncovering this hidden influence—what Golec estimates to be four to five times more signal—we can finally start to measure the true ROI of our brand-building and demand-generation efforts, not just our lead-capture tactics.
Changing the Conversation with the C-Suite
Perhaps the most significant impact of this measurement evolution is its ability to transform the conversation between marketing and the rest of the C-suite. For too long, marketing has had to defend its budget using metrics that don’t always resonate with a CFO or CEO. MQLs, while useful for internal process management, are often seen as “marketing metrics” that don’t directly translate to the language of the business: pipeline and revenue. A more sophisticated attribution model allows leaders to shift the conversation from activity metrics to business outcomes.
“The reality is like marketers have always, you know, they care about MQLs and a lot of people still get paid on MQLs, but CFOs and CROs, CEOs, they don’t care about MQLs… What they do care about is pipeline. And do I have sufficient pipeline to hit my revenue targets? …what does it cost to engage a target account? And that is always correlated to the amount of pipeline influence per dollar spent, or return on marketing spend, as some people say.”
This reframing is powerful. Instead of reporting on the number of leads generated, a marketing leader can now report on the “cost to engage a target account” for each channel. By analyzing an aggregate of customer data, Golec’s team found that for every thousand dollars spent, LinkedIn engaged four times as many target accounts as Google Paid Search, once view-through attribution was factored in. This isn’t an argument about which channel is “better” in a vacuum; it’s a data-driven insight that allows for intelligent budget allocation based on efficiency and impact. Presenting the CFO with a clear breakdown of pipeline influence per dollar spent for each channel is a far more compelling and strategic conversation than simply showing a chart of MQLs. It elevates marketing from a perceived cost center to a provable driver of revenue growth.
This approach is not just an improvement; it’s a necessity in a future without third-party cookies. The reliance on account-level identification, rather than individual cookies, future-proofs the measurement strategy against privacy changes while aligning perfectly with the B2B focus on account-based engagement.
The era of relying solely on the click is drawing to a close. While it will always be a metric, its position as the ultimate arbiter of success is untenable in the face of the complex B2B buyer’s journey. As leaders, our challenge is to embrace the ambiguity of the dark funnel and equip our teams with the technology to bring it into the light. This requires a mindset shift—away from the immediate gratification of a click and toward a more patient, holistic understanding of influence and brand engagement over time. It’s about recognizing that the most valuable interactions are often the ones that happen quietly, without a click.
The tools to do this are no longer theoretical. AI-powered view-through attribution provides the lens we need to see the full picture, to connect our efforts to real business outcomes, and to speak the language of our C-suite peers. The future of B2B marketing measurement isn’t about finding a new vanity metric; it’s about building a comprehensive, defensible model that proves marketing’s role as the primary engine of pipeline and revenue. By moving beyond the click, we don’t just get better data; we become better, more strategic leaders.
