In the event you’ve spent any time on a GEO or AEO Slack channel this 12 months, you’ve heard the identical recommendation on loop. Be on Reddit. Be on YouTube. Meet patrons the place the group already trusts. That recommendation just isn’t unsuitable for a purchaser who continues to be studying what a class even is. It simply just isn’t what the information reveals as soon as that very same purchaser begins evaluating named distributors as an alternative of searching the subject. Earlier than I put that discovering in entrance of you, I despatched the corporate behind it six pointed questions on the way it constructed the examine.
What Was Really Tracked
The examine, written up by Ten Velocity’s Nelson Brassell, pulled quotation information from Peec AI, a instrument that screens how ChatGPT, Perplexity, Claude, and Gemini cite URLs of their responses. Ten Velocity wrote 170 prompts designed to reflect how a purchaser talks to an AI assistant as soon as they’ve moved previous “what’s a CRM” and into “Pipedrive vs. HubSpot for sales-led corporations” or “how does X deal with SOC 2 reporting.” These prompts ran throughout Ten Velocity’s personal consumer base, spanning fintech, bodily safety, hospitality, and IT automation, plus look-alike opponents so the outcomes wouldn’t simply mirror the company’s personal purchasers. That produced 7,387 whole quotation appearances.
Product pages led at 24.1% of all citations, the only largest class. Articles, that means weblog posts, information, and PR, took one other 17.4%. Comparability pages and listicles every landed round 13%, how-to guides just below 9%, and homepages a shocking 7.8%. Listing profiles on websites like G2 and Capterra picked up 7.2%. Reddit, YouTube, boards, and dialogue threads mixed for 4.2%, with Reddit doing most of that work, and YouTube barely displaying up at round 1%. Add it up, and brand-controllable content material (the pages a advertising and marketing group writes and owns) accounted for 88.3% of every part the AI fashions cited when patrons have been deciding.
Comparability content material punched properly above its weight. Comparability format prompts made up 20% of the immediate set however generated near 27% of the citations, a 1.33 instances return that the majority B2B content material groups are leaving on the desk as a result of they deal with “X vs. Y” pages as a defensive afterthought relatively than an actual quotation floor.
See additionally: ChatGPT Typically Retrieves However Hardly ever Cites Reddit Pages, Information Reveals
6 Questions, And What Modified As a result of I Requested Them
The printed model of the immediate breakdown desk mentioned 220 whole prompts, whereas each different chart within the piece used 170 because the denominator. That’s not a rounding quirk; it adjustments each proportion within the report relying on which quantity you utilize. Ten Velocity confirmed 170 is the right determine and advised me the mislabeled visible can be corrected. A associated inconsistency, the place the “comparability” class was tagged two other ways in two completely different charts, acquired reconciled to the identical 34 immediate rely as soon as I requested which methodology really supported the headline comparability stat.
I additionally requested what number of distinct consumer manufacturers and verticals sit behind these 7,387 citations, as a result of that’s the actual pattern dimension query, not the quotation rely. Ten Velocity declined to offer even a variety, on the grounds that combining a consumer rely with the named verticals would danger re-identifying a small, confidential consumer base. I’ll take that as a professional boundary relatively than a dodge, however it additionally means exterior researchers can’t independently decide how broad the underlying pattern actually is.
Two different solutions matter greater than the primary two. Ten Velocity’s personal piece names the shortage of a per-platform breakdown as its largest open query, since ChatGPT, Perplexity, Claude, and Gemini virtually definitely don’t behave the identical manner on the backside of the funnel. After I requested straight, the reply was that the platform-level information merely wasn’t collected on this pull. And after I requested whether or not the 4% versus 24% cut up, the quantity the entire headline rests on, had been statistically examined or simply reported as a descriptive sample, the reply was plain. It was descriptive solely. The examine does use nonparametric checks elsewhere for quotation price comparisons throughout web page varieties, however not for the precise cut up that makes the pitch.
That’s the element that adjustments how I’d use this information. A examine whose group admits an information hole as an alternative of glossing over it earns extra of my belief, not much less, however a descriptive 88/4 cut up averaged throughout 4 AI fashions with very completely different quotation habits is a snapshot of 1 consumer base at one second, not a regulation of how B2B patrons use AI. Ten Velocity didn’t attempt to gown a directional discovering up as an business benchmark as soon as I pushed on it, and that restraint is rarer than it must be.
Ten Velocity is upfront about the remainder of what this isn’t. The dataset solely covers its personal B2B SaaS {and professional} companies purchasers, so client or ecommerce manufacturers might see one thing completely different fully. It’s a single point-in-time pull, not a tracked development, and quotation quantity just isn’t the identical factor as a click on, a demo request, or a closed deal. Ten Velocity mentioned plainly that it doesn’t have the information but to attach these citations to pipeline, and I’d deal with that because the sincere reply relatively than a hedge.
See additionally: AI Visibility Rankings Aren’t Steady – New Analysis Reveals It’s Principally Statistical Noise
What This Means For Your Content material Plan
None of this implies the Reddit and YouTube recommendation is nugatory. It means it’s aimed on the unsuitable stage of the funnel. Ten Velocity’s personal information suggests group content material should still carry weight earlier, when a purchaser continues to be forming an opinion a couple of class relatively than selecting between named distributors. What adjustments is the place you set your subsequent quarter of content material price range if the objective is displaying up when somebody is definitely about to purchase.
Rewrite your product pages and homepage like an AI mannequin is studying them chilly. Product pages and homepages collectively account for near a 3rd of citations on the analysis stage, and each work by answering “what does this do, who’s it for, what does it combine with” in plain language. Intelligent positioning provides the mannequin much less to work with than a flat, particular description does.
Construct comparability content material earlier, and towards greater than your two apparent rivals. A 1.33 instances return on comparability format prompts just isn’t a marginal edge. In case your comparability pages solely exist as a result of gross sales requested for a battlecard towards one competitor, you’re underinvesting within the format that’s already outperforming its share of purchaser questions.
Handle your G2 and Capterra profiles as content material, not simply as evaluate inboxes. At 7.2% of citations, listing profile copy, class tags, and integration lists are structured information the fashions lean on when a purchaser asks for choices in your class. A stale or miscategorized profile misinforms the mannequin at precisely the second it’s constructing somebody’s shortlist.
I’d add a fourth step that isn’t in Ten Velocity’s report, as a result of it’s the one I attempt to follow. Earlier than you repeat any AI visibility statistic in a consumer deck or a content material technique doc, ask the identical questions I requested right here. What’s the true denominator? Is that this a mean throughout platforms that is likely to be hiding one outlier? Was the headline quantity really examined, or simply described? Each AI quotation examine printed this 12 months, together with ones I’ve cited on this column, ought to survive that type of pushback earlier than it shapes a price range.
I’ve spent over 20 years telling purchasers and readers to not construct a technique round a single examine, and this one doesn’t change that recommendation. It confirms it. A examine that survives six annoying emails and a corrected chart is value extra to a working search engine optimisation than one which solely survives a press launch.
Extra Assets:
Featured Picture: Natalya Kosarevich/Shutterstock
