A B2B purchase is not one visitor, it is a committee of five to eleven people researching independently in Google and in AI chat long before anyone fills a form. They settle the shortlist on your comparison, alternatives, category, and integration pages. Those same pages now feed the answer ChatGPT and Google’s AI Overview hand back. We rank them, get them cited, and measure the whole thing to pipeline instead of sessions.
A B2B deal is decided by a committee, not a person. Five to eleven stakeholders each research independently, and almost none of them convert off a top-of-funnel blog post. They convert off the page that answers “is this the right vendor for us,” which in B2B means comparisons, alternatives, category explainers, and integration pages. That is where B2B SEO lives.
The twist in 2026: those are the exact pages AI engines read to build a vendor shortlist. Rank them and you win the click from the stakeholders who still search. Get them cited and you win the answer for the ones who ask AI first. They are the same pages, so the work converges.
Most engagements run all six together, because a committee leaves no single role uncovered. You can scope a single track if that is where the gap is. Each links to how we run it.
The pages procurement and the economic buyer settle the shortlist on. We build and rank your /vs and /alternatives pages, then win the third-party comparison threads AI engines pull from to break ties between vendors.
How we run it →The pages that frame the category on your terms and prove you fit the stack. A page per category cut, per integration, per use case, built on a programmatic system so the long tail ships without thin-content penalties.
How we run it →Mined from sales calls, RFPs, and won-and-lost deal notes, not a keyword tool. The specific, factual answers each stakeholder researches, and the kind of decisive content LLMs decompose complex buying prompts into.
How we run it →B2B buyers and AI engines trust third parties over your own domain. We place credible, non-promotional content on the publications, the G2 and Capterra category grids, and the analyst-adjacent surfaces near the Gartner Magic Quadrant and Forrester Wave that the committee and the models already read.
How we run it →AI cites Reddit and community threads more than vendor sites, and B2B buyers lurk there before they ever talk to sales. We earn genuine placements in the threads the engines pull from, without sounding like a vendor in someone else's discussion.
How we run it →One weekly dashboard: citation share by buyer prompt across five engines, organic demo requests by landing page, and influenced pipeline. The same committee pages, scored on both jobs.
How we run it →A generalist agency can rank your comparison page and never know whether the AI answer puts you on the shortlist a buyer reads at the start of the deal. We built the instrument that sees both: the ranking and the citation. Software plus done-for-you execution, not a dashboard you operate alone or a deck with no data behind it.
Geology tracks your citation share across ChatGPT, Perplexity, Gemini, Copilot, and Google AI Overviews every week, for the exact prompts your committee types. Every page we build is briefed from what the data shows, and every result is checked against it. You are never paying to rank a page while the model quietly leaves you off the vendor list a buyer reads first.
No junior hand-off, no separate content, technical, link, and GEO vendors who never talk to each other. One team owns the comparison and category pages, the programmatic build, the off-site citations, and the measurement on a weekly cadence, against one dashboard. That coherence is what makes a buying committee, and the models that summarize for them, trust the picture you present.
We inventory every high-intent page each role on the committee researches before deciding (comparisons, alternatives, category, integrations) and the prompts those stakeholders type into five AI engines. Most of that research happens in the dark funnel, the part of the buying journey you cannot see in your CRM, which is exactly why intent platforms like 6sense and Bombora exist. Then we score where you rank and where you are cited today, page by page and role by role.
Crawl, render, schema, Core Web Vitals, plus llms.txt and parser-friendly markup. Many B2B sites have deep product substance buried under a stack the engines cannot read cleanly, and the trust signals procurement looks for (your SOC 2 status, security and compliance pages) sit in PDFs the models never parse. This layer unlocks everything built on top of it.
Your /vs, /alternatives, category, and integration pages, written from sales-call and RFP truth rather than a keyword tool, plus the programmatic system to scale the long tail across the category without thin content. These are the pages a champion forwards to build the internal business case, and the ones AI engines read to assemble a shortlist.
B2B buyers and AI engines trust third parties over your own domain. We earn placements across the surfaces the committee already reads: your G2 and Capterra category grids and Leader placement, analyst coverage adjacent to the Gartner Magic Quadrant and Forrester Wave, the Reddit and Slack-community threads buyers lurk in, and the editorial the models pull from, without sounding like a vendor in someone else's discussion.
Organic demo requests by landing page, influenced pipeline and target-account engagement where your CRM and ABM platform can attribute it, branded-search lift, and citation share by prompt across all five engines. We report to the revenue line the board asks about, not the rankings page.
Run a Live Audit. We pull your brand against competitors on the buyer prompts your committee asks across ChatGPT, Perplexity, Gemini, Copilot, and Google AI Overviews, and send the full report to your inbox.
