CITABLE: The AEO content framework we use to get B2B brands cited by AI

Updated October 11, 2025

The evidence is clear: AI has fundamentally changed B2B discovery

Two realities collided that forced us to develop this framework as part of service delivery to clients.

Reality #1: AI is eating search real estate

13.14% of all queries triggered AI Overviews in March 2025, up from 6.49% in January. About one-in-five Google searches in March 2025 produced an AI summary. Some studies show Google's AI Overviews now appear in more than 50% of all search results. Google has expanded AI Overviews to 200+ countries and 40+ languages. Your brand needs to be in those summaries and in engines that always cite (Perplexity, ChatGPT with search).

Reality #2: B2B buyers have gone AI-first

Up to 90% of B2B buyers already use generative AI tools, according to Forrester. Even more striking: 94% of buyers now utilize ChatGPT, Claude, Perplexity or some other AI search engine in the buying process. Sales conversions driven by ChatGPT recommendations have skyrocketed by 436%. So this isn't something that we can expect in the future, the change is already here.

The problem is that when AIOs have been shown, both paid and organic CTRs trend down. Google users were less likely to click on result links when visiting search pages with an AI summary compared with those without one. Specifically, Individual sites' CTR dropped 34.5% when an AI Overviews appeared.

Also critical: AI Overviews don't just parrot organic results. Only ~54% overlap exists between AIO citations and top organic listings meaning nearly half of citations come from different pages. This is why "classic SEO only" misses buyers who start with AI. Read our other post for differences in SEO vs AEO or watch the video below.

Don't just take it from us, here's what others in the wild say:

“Buyers do 70% of their research before they’ll even talk to you… Where are they researching? ChatGPT, Google …” — discussion in r/b2bmarketing.

“Six out of ten buyers are asking AI about you before they ever ask you.” — VP at UserEvidence, quoting the 2025 Evidence Gap report

Meet CITABLE: The framework we ship with clients daily

CITABLE is an internal rubric we developed to ensure each piece of content we create for clients is optimal for LLM retrieval. We quickly realised that traditional SEO content wasn't going to cut it in the AI search era. So we combined my marketing skills with my co-founders engineering experience and got scientific.

This framework is fast to implement and designed to provide teams with direction in a period that still feels a bit scrappy. We also turned this rubric into a free AEO content grader that you can use or find a copy-paste prompt you can plug directly into LLMs at the end of this article.

And just so you know we're not making things up. This is the exact framework we operationalise for clients, recently helping a B2B SaaS company take their AI-referred trials from 550 to 2,300 in 4 weeks (a 4x improvement).

Let's jump in.

C — Clear entity & structure

Lead with a 2–3 sentence Bottom Line Up Front (BLUF): what it is, who it’s for, when to use it. Use semantic H2/H3s and a tidy hierarchy so models don’t guess and match copy to schema and never mark up what isn’t visible.

How to implement:

• Open with a definition (<120 words)
• Add an updated timestamp
• Include a key facts box with 3–5 numbers/dates LLMs can copy-paste
• Use semantic H2/H3s and tidy hierarchy so models parse without guesswork

I — Intent architecture

State the primary question clearly, then bridge to adjacent intents: alternatives, integrations, use cases, pricing, limits, benchmarks.

How to implement:

• Map your content to 5-7 adjacent intents, satisfying them logically with H2s and H3s
• Create a hub-and-spoke internal linking structure where each spoke answers a specific sub-query
• Use tools like AlsoAsked or AnswerThePublic to find the exact questions buyers ask around your category
• Structure each page with the question as the H1 and answer in the first 100 words

Why it matters: AI models often break user queries into sub-queries (called query fan-out). Meeting adjacent intents keeps the session on your content.

T — Third-party validation

Back claims with neutral comparisons, docs, reviews, and press. ChatGPT search's focus on prioritizing reputable sources such as Reuters, Reddit and G2 which enhances the transparency and credibility of its results.

How to implement:

• Create a Wikipedia presence (start with Wikidata, then build notability for main Wikipedia)
• Launch quarterly review campaigns on G2, Capterra, and TrustRadius with specific customer segments
• Engage in Reddit discussions by answering questions, seeding comments and posts (or hire us to do it for you)
• In every piece of content try to pull in third-party opinions and evidence

Key sources that matter:

• Wikipedia mentions
• Review platforms (G2, Capterra, TrustRadius)
• News coverage
• Industry forums and Reddit discussions
• Academic papers and case studies

A — Answer grounding

Write complete, accurate, verifiable answers with source links and next steps. Google's AGREE research shows models cite better when claims are explicitly grounded. Include 1–2 sentence "quotable facts" that can stand alone.

How to implement:

• Start every answer with a 40-60 word direct response that could work as a featured snippet
• Add inline citations using brackets [Source, 2025] that link to authoritative third-party sources
• Include a "Quick Answer" box at the top of long-form content with the core facts
• End each section with one quotable statistic or customer quote that validates the point

B — Block-structured for RAG

Retrieval Augmented Generation (RAG) is a technique that improves a model’s responses by injecting external context into its prompt at runtime.

Format for extraction: TL;DR boxes, bullets, short tables, FAQs, and 200–400-word blocks. AI engines still start with a web crawl similar to Googlebot. They fetch pages, parse HTML, and store text, metadata, schema markup, and structured data into an index.

Anthropic's Contextual Retrieval research shows this can reduce failed retrievals by up to 49%.

How to implement:

• Break content into self-contained sections of 200-400 words with clear H2/H3 headers
• Add a TL;DR box after your intro with 3-5 key takeaways
• Use comparison tables for features, pricing, or alternatives (keep under 10 rows)
• Create jump links/table of contents for pages over 1,500 words to improve navigation

L — Latest & consistent

Time-stamp pages ("Last updated: YYYY-MM-DD") and version key facts. Keep numbers consistent across your site, docs, G2/Capterra, partners, and press. Conflicts are a top negative factor for AEO.

How to implement:

• Add "Last updated" timestamps to all pages, visible above the fold
• Create a source-of-truth spreadsheet for all company facts (pricing, features, stats)
• Audit quarterly: search "[your brand] pricing" and fix any inconsistencies across the web
• Set up Google Alerts for your brand name + key facts to catch outdated information

Ensure content accuracy and freshness: Answer engines favor content that is authoritative and up-to-date.

E — Entity graph & schema

Map related entities (integrations, industries, use cases, competitors) and make relationships explicit in copy. Add JSON-LD that mirrors visible content (FAQ/Organization/Product).

How to implement:

• Create an entity map showing your product's relationships (integrations, alternatives, use cases)
• Write explicit relationship statements: "Alternative to [X]", "Integrates with [Y]", "Used by [Z]"
• Implement Organization, Product, and FAQPage schema that exactly matches visible content
• Use Google's Rich Results Test to validate schema before publishing

Critical: There's no special schema required for AI Overviews. Focus on helpful, reliable content that can be indexed and quoted. Never mark up what isn't visible on the page.

The CITABLE checklist

• BLUF (≤100 words): What is X? Who is it for? When to use it?
• Key Facts: 3–5 crisp, source‑linked numbers/dates
• H2s for adjacent intents: Alternatives, integrations, pricing, limits, benchmarks, FAQs
• Quotable facts: 1–2 sound‑bite sentences per section with a source
• Tables & lists: At least one short table and one bulleted list
• FAQ: 3–5 questions with self‑contained answers (and matching JSON‑LD)
• Timestamp + version notes: “Last updated” + what changed
• Schema: Organization/FAQ/Product (mirrors what’s visible)
• Internal links: Connect to deeper pages for fan‑outs

How we apply CITABLE at Discovered Labs

Discovered Labs is a pure‑play SEO/AEO partner for companies. Our cadence is unusual (we ship daily for clients), we prioritize third‑party validation as much as owned content, and we continuously test content formats directly against AI systems to see what actually gets cited.

Check out our AI Search Playbook for role-specific implementation guides, or browse our blog for more tactical frameworks.

Frequently Asked Questions about AEO content

Q: How is AEO content different from traditional SEO content?
AEO content leads with direct answers in 40-60 words, uses more structured blocks (200-400 words), and prioritizes third-party validation over keyword density. While SEO content often builds to an answer, AEO content provides the answer immediately, then expands with evidence. The biggest difference: AEO content must be "quotable" - formatted so AI can extract and cite specific facts without losing context.

Q: Can I convert my existing SEO content for AEO, or do I need to start fresh?
You can retrofit existing content by adding CITABLE elements: a BLUF opening, quotable fact blocks, structured data that matches visible content, and third-party source citations. However, content originally written for keywords often needs substantial restructuring. Start by auditing your top 10 pages - add clear definitions, TL;DR boxes, and FAQ sections. Most companies see better results creating new AEO-first content while gradually updating existing pages.

Q: What content formats get cited most by AI systems?
Comparison pages, problem-solution guides, and definitive glossaries perform best. Specifically: "[Product] vs [Competitor]" pages, "How to [solve specific problem]" guides, and "What is [concept]" definitions. AI systems also frequently cite FAQ pages, pricing pages with clear tables, and integration documentation. Avoid: blog posts without clear structure, marketing fluff pieces, and pages that don't directly answer a specific question.

Q: How long should AEO content be for optimal AI visibility?
Target 1,500-2,500 words for comprehensive topics, broken into 200-400 word sections. Each section should be self-contained and answer one specific sub-question. Shorter content (500-1,000 words) works for narrow queries but include at least 3-5 quotable facts. Length matters less than structure - a well-structured 1,000-word page outperforms a rambling 3,000-word article.

Q: Should I create different content for ChatGPT vs Perplexity vs Google AI?
No - focus on universal AEO principles that work across platforms. All AI systems value clarity, accuracy, freshness, and third-party validation. However, you can optimize distribution: ensure Wikipedia presence for ChatGPT, maintain fresh review profiles for Perplexity, and use structured data for Google AI. The CITABLE framework works across all platforms because it addresses fundamental AI needs.

Q: What topics should I prioritize for AEO content creation?
Start with high-intent comparison queries ("[Your product] alternatives"), problem-focused content ("how to [achieve outcome without your product]"), and category definitions. Use your search console data to find questions with featured snippets - these same queries often trigger AI summaries. Prioritize topics where you have unique data, customer proof, or differentiated expertise that competitors can't easily replicate.

Q: How do I know if my content is properly optimized for AI citations?
Test directly: search your target queries in ChatGPT, Claude, Perplexity, and Google (with AI Mode enabled) using new/incognito sessions. You're optimized when: (1) Your content appears in responses for target queries, (2) AI accurately represents your key facts, (3) Your unique differentiators are mentioned, (4) Citations link back to your site. Use tools like our AEO Content Evaluator to score content before publishing.

Q: How often should I update AEO content to maintain visibility?
Update quarterly at minimum, monthly for competitive topics. Every update should include: refreshing timestamps, updating statistics, adding new third-party validations, and fixing any information inconsistencies across the web. Set Google Alerts for your key topics to monitor when competitors update their content. Remember: AI-generated traffic is growing at over 40% monthly, so freshness increasingly matters.

Q: What's the minimum viable AEO content strategy for a small B2B team?
Start with 10 pages: 5 comparison pages (you vs. top competitors), 3 problem-solution guides, 1 comprehensive glossary/definition page, and 1 integration/compatibility guide. Ship one new page weekly using the CITABLE framework. Simultaneously, fix information consistency across review sites and update your Wikipedia/Wikidata presence. This foundation typically generates initial AI citations within days.