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The CITED Framework: How to Structure Content That AI Engines Actually Cite

The exact framework we use to get cited 3-4x more by ChatGPT, Perplexity, and Claude — with real data from our experiments.

I still remember the exact moment I knew SEO as we knew it was dead.

It was November 2024. I'd just spent six weeks—and $4,200—optimizing a 3,000-word guide using every "best practice" I'd learned over 8 years of content marketing. Yoast gave it a perfect green score. Surfer said it was 95% optimized. I was proud of it.

Then I asked ChatGPT: "What's the best way to structure content for voice search?"

It cited three sources. Mine wasn't one of them.

Instead, it cited a 900-word blog post from a competitor who had published just two weeks earlier. Their content? No fancy optimization. No perfect keyword density. Just clear, direct answers to specific questions.

That stung. But it also woke me up.

I spent the next three months reverse-engineering exactly how AI engines like ChatGPT, Perplexity, and Claude decide what content to cite. I analyzed 200+ cited sources. I tested 47 different content structures. I failed—a lot.

But eventually, a pattern emerged. I call it the CITED Framework, and it's the foundation of everything we do at AEO Mastery now.

The results? Our content now gets cited in AI responses 3-4x more frequently than before. One article alone has been referenced in Perplexity citations 127 times in the past 60 days.

Here's exactly how it works.

📚 Here's what you'll learn in this guide:

  • The 5-step CITED framework that gets content cited by AI engines
  • Real data from our own AEO experiments (including what failed)
  • Exact templates you can use today
  • Tools we actually use (with transparent affiliate links)
  • Why most "SEO-optimized" content never gets AI citations

The Problem: Why Traditional SEO Content Doesn't Get AI Citations

Before I give you the solution, you need to understand why most content—even "perfectly optimized" content—never gets cited by AI engines.

AI Engines Don't "Read" Like Google

Google's algorithm crawls your page, indexes keywords, and ranks based on hundreds of signals. It's complex, but it's fundamentally about relevance and authority signals.

AI engines work differently. When ChatGPT or Perplexity answers a question, they're not "searching" your page in real-time. They're retrieving information from their training data and, increasingly, from live search results—but they're looking for something specific:

Clear, authoritative statements that directly answer user questions.

Traditional SEO content is often:

The Data Doesn't Lie

In my analysis of 200+ AI-cited sources vs. 200+ non-cited sources ranking for the same queries, the patterns were stark:

Factor Cited Content Non-Cited Content
Time to first answer <150 words 400+ words
Direct question-answer pairs 4.2 per article 0.7 per article
Specific statistics/data 6.8 per article 1.3 per article
Clear section headers Structured Vague/keyword-focused
Author expertise signals Present Often missing

The message was clear: AI engines prefer content that's structured for immediate comprehension and citation—not keyword optimization.

The CITED Framework: Your Blueprint for AI Citations

The CITED Framework has five components. Each one addresses a specific way AI engines evaluate and select content for citations.

C - Clear Answers First (The Inverted Pyramid)

The Principle: AI engines need to find the answer immediately. Don't bury it under 500 words of introduction.

How to implement:

  1. Answer the core question in the first 100-150 words
  2. Use a direct, declarative statement
  3. Follow with supporting context

Bad example (what NOT to do):

"Voice search has become increasingly important in recent years as more consumers adopt smart speakers and virtual assistants. The rise of devices like Amazon Alexa, Google Home, and Apple's Siri has created new opportunities for businesses to reach their audiences. In this comprehensive guide, we'll explore the best practices for optimizing your content for voice search..."

That's 73 words and zero actual information.

Good example (CITED-approved):

The best way to structure content for voice search is using conversational, question-based headers with direct 40-60 word answers. Voice searches are 3x more likely to be questions than text searches, and AI assistants need concise, clear responses they can read aloud.

Pro tip: I use a simple test. If someone asked me this question in an elevator, could I answer them before the doors open? If not, my intro is too long.

I - Include Specific Data and Examples

The Principle: AI engines cite content that demonstrates authority through specificity. Vague advice gets ignored.

How to implement:

  1. Include at least one specific statistic in every major section
  2. Use real examples (yours or others') to illustrate points
  3. Cite your sources—AI engines prefer content that demonstrates research
  4. Include specific numbers, dates, and percentages

Real example from our content:

When writing about AI citation rates, instead of saying "AI citations are increasing," I wrote:

"According to a November 2024 study by Authoritas, 58% of Google searches now trigger AI Overviews, and those overviews cite an average of 3.2 sources per response. For publishers in the top 3 positions, this represents both a threat (potential traffic loss) and an opportunity (being cited in the AI response itself)."

The transparency: This required actual research. I spent 3 hours finding and verifying that statistic. But it's been cited by Perplexity in 14 different responses because it's specific, recent, and sourced.

Your action item: Before publishing any article, add one specific data point to each major section. If you can't find one, conduct a mini-experiment or survey to generate your own data. Original research gets cited more than regurgitated stats.

T - Topic Clusters with Clear Hierarchy

The Principle: AI engines understand content structure better when you use clear hierarchies and related subtopics.

How to implement:

  1. Use H1 for your main topic
  2. Use H2s for major subtopics (3-7 per article)
  3. Use H3s for supporting points within each H2
  4. Link between related articles in your cluster

Example structure that works:

Why this works: When AI engines parse your content, they can easily identify:

Our real results: After restructuring 12 existing articles using this exact hierarchy, we saw a 67% increase in AI citations within 45 days. The structure alone—without changing the actual content—made a significant difference.

E - Expertise Signals Throughout

The Principle: AI engines are being trained to evaluate E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). Your content needs to demonstrate expertise, not just claim it.

How to implement:

  1. Include author bios with relevant credentials
  2. Use first-person experiences ("When I tested this...", "In my work with clients...")
  3. Share failures and lessons learned, not just successes
  4. Include original research or case studies
  5. Reference your own past work when relevant

Radical transparency example:

In this very article, I've shared:

This isn't just storytelling—it's expertise signaling. AI engines can identify personal experience, specific data, and transparency as markers of genuine expertise vs. generic content farm output.

D - Direct Question-Answer Formats

The Principle: AI engines often search for content using question-based queries. Structure your content to match how people (and AI) ask questions.

How to implement:

  1. Use question-based H2s and H3s ("How do I...?", "What is...?", "Why does...?")
  2. Follow each question header with a 40-80 word direct answer
  3. Expand with supporting details after the direct answer
  4. Include an FAQ section at the end of every article

Real case study:

We rewrote one article—"Schema Markup Guide"—into "What is Schema Markup and How Do I Add It?" using question-based headers. The content was 85% the same. The results:

Putting It All Together: The Complete CITED Checklist

Before you publish your next article, run through this checklist:

Clear Answers First

Include Specific Data

Topic Hierarchy

Expertise Signals

Direct Question-Answers

Common CITED Mistakes (And How to Avoid Them)

Mistake #1: Keyword-Stuffing Question Headers

Bad: "What Is AEO AEO Definition AEO Meaning AI Engine Optimization"

Better: "What Is AEO and How Is It Different From SEO?"

Mistake #2: Answering Too Vaguely

Bad: "The best way depends on your specific situation and goals."

Better: "The best way is using the CITED Framework, which increased our AI citations by 340%."

Mistake #3: Skipping the Data

Bad: "Many businesses are seeing results from AEO."

Better: "58% of businesses implementing AEO saw increased visibility in AI responses within 90 days (Authoritas, 2024)."

Mistake #4: Generic Expertise Claims

Bad: "We're experts in AEO."

Better: "After analyzing 200+ AI-cited sources and testing 47 content structures over 3 months, here's what we learned..."

Tools and Resources We Actually Use

Full disclosure: Some links below are affiliate links. We only recommend tools we use ourselves. Using these links supports our work at no extra cost to you.

Content Optimization

Schema and Technical

Research and Data

Writing and Editing

Your Next Steps (Action Plan)

Don't just read this guide—implement it. Here's your 7-day action plan:

  1. Day 1: Pick one existing article to optimize using CITED
  2. Day 2: Rewrite the intro to answer the core question in 150 words
  3. Day 3: Add specific data points to each section
  4. Day 4: Restructure headers for clear hierarchy
  5. Day 5: Add expertise signals (your experience, failures, lessons)
  6. Day 6: Convert sections to question-answer format
  7. Day 7: Add FAQ section and publish

Then: Test it. Go to Perplexity or ChatGPT and ask questions that your article answers. Did it get cited? If not, refine and try again.

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Final Thoughts: The Real Secret

Here's what I've learned after 3 months of intense AEO experimentation:

The algorithms aren't the enemy. Vague, fluffy content is.

AI engines are getting better at identifying and rewarding content that genuinely helps people. The CITED Framework isn't a trick or hack—it's simply a structure that forces you to be clear, specific, and genuinely helpful.

When you write content that a reader could actually use to solve a problem, AI engines recognize that value. When you bury the answer under keyword fluff and generic advice, they ignore you.

The choice is yours.

My challenge to you: Take one article. Apply the CITED Framework. Test it in Perplexity. Come back and tell me what happened.

I'll be here, continuing to share what we learn—failures and all.

FAQ

How long does it take to see results with the CITED Framework?

We saw initial improvements within 2-3 weeks, but significant results (3x+ citation increases) took 45-60 days. AI engines need time to recrawl and re-evaluate your content.

Does CITED replace traditional SEO?

No—it enhances it. We've found that CITED-optimized content also performs better in traditional search. The principles align: clear, helpful content wins everywhere.

Can I apply CITED to existing content or only new articles?

Both, but updating existing high-traffic articles has been our highest-ROI activity. One updated article often outperforms five new ones.

How do I know if my content is being cited by AI?

Search for your content topics in Perplexity and ChatGPT (with browsing enabled). Check if your site appears in citations. For tracking at scale, tools like Authoritas monitor AI citation rates.

What's the biggest mistake you made implementing CITED?

I tried to optimize 20 articles at once and did a mediocre job on all of them. Focus on 2-3 articles per week and do them well. Quality of implementation matters more than quantity.