How are B2B buyers using AI in 2026?
The pattern we observe across client engagements: buyers use ChatGPT, Perplexity and Google AI Overviews as an analyst layer. Early stage: what should I look for in a category, what are the approaches to a problem. Shortlist stage: best vendors for our size and industry, A versus B versus C. Diligence stage: is vendor X reliable, what are the complaints about Y. The engine answers from your site’s explainers and comparison content, third-party review platforms (G2-class), practitioner forums and communities, and whatever press and analyst coverage exists. Deals are increasingly influenced before the first form fill — and your analytics see none of it, which is why AI referral traffic data understates AI’s real influence.
What gets a B2B vendor named?
- Definitional authority. Engines cite whoever explains the category best. Vendors who publish genuinely educational category content — not product pitches — get cited as sources, which pulls the brand into the answer.
- Comparison honesty. A versus B pages that state real tradeoffs (we are stronger for X; they are stronger for Y) are citation magnets; one-sided comparisons are discounted. The engine’s job is synthesis, and honest comparative structure is the easiest to synthesize.
- Evidence content. Published methodology, benchmarks with stated samples, pricing shape, security and compliance facts. B2B engines quote specifics; marketing adjectives are uncitable.
- Third-party corroboration. Review-platform presence with texture, practitioner-community reputation, and earned coverage. Engines cross-check claims; uncorroborated leadership claims get hedged.
Where does GEO sit relative to ABM and demand gen?
Upstream of both. Account-based marketing and demand generation work on accounts already in motion; the AI answer layer increasingly decides which vendors enter consideration in the first place. Practically, the programs share assets: the honest comparison pages, benchmark studies and category explainers that win AI citations are the same assets that arm your sales team and anchor webinars. GEO does not replace demand gen — it makes sure demand gen has someone to talk to.
The entity discipline in B2B
B2B entities fragment: product names versus company names, acquired brands, regional sites. One Organization entity with consistent naming, sameAs to LinkedIn and review profiles, and clean hreflang across regional sites is the load-bearing fix. If the engine cannot tell whether X Corp, X Platform and X.io are one thing, your authority splits three ways.
What about analyst relations?
Analyst coverage, review platforms and practitioner communities function as the corroboration layer engines cross-check — so classic AR and GEO reinforce each other. The adjustment is content form: engines quote specific, dated, verifiable statements, so press releases and analyst summaries that contain concrete facts (customer counts you can substantiate, certifications, methodology) travel further into answers than positioning language.
Measuring B2B GEO
Fixed question set across the buying stages — category education, shortlist, versus, diligence — run monthly across engines, scored on the four-dimension standard with screenshots. Connect to pipeline honestly: tag self-reported attribution (how did you hear about us) and watch branded-search trends alongside the scorecard. Do not promise pipeline numbers from GEO alone; promise verifiable visibility movement against baseline.
First moves
- Baseline measurement of the buying-stage question set.
- Entity consolidation audit across brands and regions.
- Honest versus pages for your top three competitor pairings.
- Review-platform operations restarted with real customer asks.