GEO & AEO: get cited when B2B buyers ask AI first

The buyer journey moved upstream of your website

In 2026, a meaningful share of your market forms a vendor shortlist before ever visiting your site. Gartner projects traditional search volume will drop about 25% in 2026 as AI agents take over product research, and 6sense's buyer research found that 94% of B2B buyers use generative AI tools during their purchase process. eMarketer estimates nearly a third (31.3%) of the US population will use generative AI search in 2026.

When a buyer asks an AI assistant 'which agencies build high-performance B2B websites?', the answer is assembled from content the model trusts enough to cite. GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) are the disciplines of becoming one of those cited sources.

What GEO and AEO actually change

Classic SEO optimizes pages for clicks. GEO optimizes content to be selected as a source inside synthesized answers; AEO structures content so answer engines can extract it accurately. In practice they are the same underlying work — clear structure, specific claims, and machine-readable context — applied to a world where zero-click visibility is common.

The referral economics are different: AI platforms often cite you while sending little traffic. That is not a flaw. A citation is pre-sold trust — the buyer arrives already carrying your framing. Optimize for being the answer, and the visits you do get are late-stage, high-intent, and far easier to convert.

1. Structure every page as extractable answers

Answer engines lift passages, not vibes. Write in self-contained blocks: a direct answer in the first two sentences, then supporting detail. Use real headings for real questions — 'What does a SaaS MVP cost?' as an H2 with a 40–60 word direct answer underneath is exactly the shape models quote.

This is also why FAQ sections on service pages matter twice: once for the human scanning the page, once as structured data (FAQPage schema) that engines can read without guessing.

2. Make claims specific, dated, and attributable

Models prefer sources that are precise enough to be wrong. 'Fast websites convert better' is unquotable. 'Sites loading in 1 second converted 2.5x better than sites loading in 5 seconds across 100M+ page views (Portent)' is quotable, because it carries a number, a scope, and a source.

Cite your own sources on-page. A page that links to primary data signals the kind of provenance that generative engines reward when choosing between two similar answers.

3. Keep your entity facts identical everywhere

AI engines cross-reference. If your services page says 'six service tracks', your llms.txt says five, and a directory listing says seven, you become an unreliable narrator and citations drift to competitors with consistent facts.

Maintain one canonical description of what you do, who it is for, and how engagements work — then mirror it across the site, sitemap, robots policy, llms.txt, and structured data. Consistency is a ranking input now, not just brand hygiene.

4. Allow the AI crawlers you want to be found by

If your robots.txt blocks GPTBot, ClaudeBot, PerplexityBot and similar agents, you have opted out of the channel entirely — a common, invisible mistake. Name the agents you want to allow, and remember that robots.txt user-agent groups are matched exclusively: each named group must restate your disallow rules, or the wildcard's exclusions stop applying to it.

5. Publish depth that general models cannot paraphrase away

Thin listicles get summarized into oblivion. Original frameworks, decision checklists, priced-out comparisons, and worked examples survive retrieval because they contain information that exists nowhere else. One deeply useful guide earns more citations than thirty generic posts.

The budget logic follows: fewer pages, more substance, refreshed when facts change. Conductor's CMO research found 94% of marketing leaders plan to increase AEO investment — the winners will be the ones publishing what AI answers are missing, not adding to what they already repeat.

The GEO/AEO readiness checklist

• Every money page opens with a direct, quotable answer to its core question.
• FAQ blocks carry FAQPage JSON-LD; articles carry Article and BreadcrumbList schema.
• Claims include numbers, scope, dates, and on-page source links.
• robots.txt explicitly allows the AI agents you want citing you — with per-group disallows restated.
• llms.txt and sitemap describe the same canonical page set the site actually serves.
• Entity facts (services, positioning, process) are identical across every surface.

How this applies at Kiwi

Our technical SEO track now ships GEO/AEO as part of the foundation: structured data, crawl policy for AI agents, answer-shaped content architecture, and an llms.txt that keeps your canonical facts consistent. It is evidence-led work — we measure citation readiness and indexation, and we never promise rankings or guaranteed AI placement.

If your buyers are asking AI about your category and you are absent from the answers, send us your site. The review takes 24 hours and names exactly which structural gaps are keeping you out.