Less than most reports suggest. Dreamdata's 2026 benchmark puts the average B2B journey at 272 days from first touch to closed deal, with 81 percent of it happening before a sales conversation starts. A 30-day attribution window covers about a ninth of that. So assume more is happening out of view, keep funding what feeds it, and measure the signals that surface: branded search, direct visits to key pages and what buyers tell you in their own words.
How long does a B2B buying journey take now?
Longer every year. Dreamdata, a B2B attribution platform, analyzed 3.5 million customer journeys across 66 million sessions for its 2026 LinkedIn Ads Benchmarks Report. The average journey grew from 211 days to 272. Its CEO, Nick Turner, told CMOtech that the typical sales cycle of 78 days represents just 19% of the whole journey, and that a buying decision now involves 10 to 12 stakeholders.
Worth noting: Dreamdata sells attribution software, so it has a stake in this finding. The direction still matches what I've seen in long-cycle B2B. At Johnson Matthey I supported deals in the eight and nine figure range, and those buyers did a great deal of homework before anyone on our side heard from them.
Why does short-window attribution mislead you?
Because it rewards whatever happened last. Evan Hughes, COO of the agency Refine Labs, walks through a clean example:
Picture a $25K product with a nine-month sales cycle. The buyer spends eight months seeing your people post, reading an article a colleague forwarded and watching a webinar without filling out a form. Then they search your company name, click an ad and book a demo. Paid search gets the credit, and the budget follows the credit.
Amanda Natividad of SparkToro, who wrote Zero Click Marketing, describes the modern path the same way: a buyer sees you, moves on with life, sees you again, hears about you from a friend in a group chat, then searches and arrives as direct traffic.
None of those early moments show up in a click report. All of them did the work.
Why I'd rather overestimate the dark funnel
The two mistakes cost different amounts.
If you overestimate how much happens out of view and keep funding content, community and brand a little longer than a spreadsheet would like, you spend some money you can see.
If you underestimate it and cut that spend, nothing breaks right away. The pipeline looks fine for a quarter or two, because buyers already in motion keep arriving. By the time the drop shows up, you've lost months of runway, and restarting takes just as long.
I'll take the visible cost every time.
Here's a humbling example from my own work. The lead behind more than $20M in CRM-attributed pipeline at Johnson Matthey came through a web page I owned and ran paid ads for, about one to two months after our new lead capture form went live. The form recorded the moment that buyer raised a hand. I'll never know how many months of reading, conversations and conference visits came before it. Neither will the CRM.
How do you show dark funnel value to a CFO who wants hard numbers?
Give them patterns they can check, alongside the click report.
Plot spend against unattributed demand
Track your content, social and brand investment against inbound that arrives through direct, organic and branded search, over a rolling three to six months. Look for the lag: when the investment rises, hand-raisers tend to follow weeks or months later. It's correlation (so say so) but it's still evidence.
Run a holdout when you can
If you sell across regions, pause or reduce a program in one and keep it running in another, then compare inbound over the following months. It's one of the most honest tests available, and finance teams respect it.
Watch the mix of your pipeline
Track how much pipeline comes from people asking to talk to you versus people who downloaded something. A growing share of direct hand-raisers usually means the work upstream is landing.
Which signals reveal what's happening out of view?
No single one of these is perfect. Together they give you a much better picture than a last-click report alone.
Does this mean you should stop using attribution?
Keep it. Hughes makes the same point: he still wants UTMs and channel data in pipeline reporting. He just doesn't want a click report deciding where the next million dollars goes. That's the balance I'd aim for. Use attribution to tune the channels you can measure, and use judgment, signals and tests to protect the work that happens before anyone clicks.
FAQ
What is the dark funnel?
The dark funnel is the part of the buying journey your analytics can't see: private conversations, shared links in Slack or text threads, podcasts, social posts read without a click and research done inside AI tools.
Should we ungate our content?
Test it with your strongest piece. Open content travels further through the dark funnel, and a buyer who later raises a hand tends to arrive better informed. Keep a light, optional way to subscribe.
Is self-reported attribution reliable?
It's imperfect, since people misremember. It's also the only source that captures conversations software can't see. Pair it with your analytics and look for patterns over time.
Sources
Dreamdata, 2026 LinkedIn Ads Benchmarks Report, as reported by Demand Gen Report
Nick Turner, Dreamdata CEO, interview with CMOtech
Amanda Natividad, SparkToro, LinkedIn post on zero-click marketing
Trying to make the case for work you can't fully track?
If you're heading into a budget conversation and need to defend the work that happens before the click, I'd be glad to help you build the case. We can look at which signals you already have and which ones are worth adding this quarter. Connect with me on LinkedIn, read about my background on my About page, or see how ongoing help works on my Advisory page. Let's talk.