Getting B2B Content Cited by ChatGPT and Perplexity Is Not About Writing Better Content.
It Is About Formatting Existing Content So AI Engines Can Extract It.

Step 1 — Add FAQPage Schema to Every Service and Documentation Page

FAQPage schema is the single highest-impact change for B2B AI citation. It wraps your existing Q&A content in machine-readable JSON-LD that AI engines can extract directly. Every service page should have at least 3–5 FAQPage entries answering the questions buyers actually ask: "What does [service] cost?", "How long does [service] take?", "What results does [service] produce?"

The entries must be direct answers — not links, not "contact us for pricing." AI engines skip non-answers. If you don't want to publish exact pricing, answer the question differently: "Pricing depends on X and Y. Typical engagements range from $X to $Y based on scope." That is a citable answer. "Contact us" is not.

Step 2 — Structure Technical Documentation for ChatGPT Web Browsing

ChatGPT's web browsing visits individual pages and reads them. When a user asks "what is the best way to optimize my company's technical documentation so it is accurately summarized and cited by ChatGPT?" — the answer is: write each documentation page as if the first paragraph is the only paragraph a summarizer will read.

Practical documentation formatting rules:

• Start each page and section with a 1–2 sentence direct definition or answer
• Use explicit H2 and H3 headings that state the answer, not just the topic ("How X works" → "X works by doing Y")
• Include version dates and "last updated" timestamps — ChatGPT prioritizes fresh, dated content
• Name all entities explicitly: product names, integration names, API endpoints — don't use pronouns for technical terms
• Add an Article or TechArticle schema block with dateModified updated on every edit

Step 3 — Add ai:summary and abstract Meta Tags to Every Page

These two meta tags exist specifically for AI engine extraction. The ai:summary tag provides a 1–3 sentence answer that AI engines can surface directly without visiting the full page. The abstract tag serves the same purpose for platforms that look for it (Perplexity indexes both).

Every B2B page that should generate citations needs these. If you have 50 service and documentation pages without them, that is 50 missed citation opportunities per query.

Step 4 — Build E-E-A-T Author Signals on Content Pages

AI engines assess credibility before deciding whether to cite a source. For B2B content, credibility is signaled by: named authors with verifiable credentials (not "the [Company] team"), linked author bio pages with Person schema, external citations within the content (link to third-party data you reference), and publication + modification dates on every page.

The Person schema block is the most important piece. It connects the author to a URL, establishes their credentials via the jobTitle, knowsAbout, and sameAs (LinkedIn) fields, and allows the content to be attributed across multiple pages to the same entity.

Step 5 — Publish an llms.txt File

An llms.txt file at your domain root tells LLMs directly what your organization does, what your key pages are, and which URLs contain authoritative information on specific topics. Perplexity and some Claude deployments read it during web research sessions. It functions like a sitemap — but written for AI engines, not Google's crawler.

For B2B, the most important sections are: a 2–3 sentence company description, your top 5–10 service or product pages with one-line descriptions, and your primary research or case study URLs. Keep it under 500 words. Plain text, no HTML. See the llms.txt specification →

Step 6 — Rewrite Your Opening Paragraphs as Standalone Answers

The most underused change. The first 50–75 words of every B2B page are what AI engines extract first. Most B2B service pages open with brand story, mission statements, or vague value props. None of those are citable answers.

The formula: [What you do] + [Who it's for] + [How it works] + [What result it produces]. In two sentences or fewer. That is what Perplexity and ChatGPT extract when a user asks about your category.

Example — before: "We are a leading provider of enterprise data solutions dedicated to helping companies unlock the value of their data assets."
After: "AcmeCo's enterprise data pipeline automates ingestion from 200+ sources into a unified warehouse. Mid-market teams typically reduce manual data work by 60% within 30 days of deployment."