SEO & AI Search Strategy
For two decades, the SEO playbook was straightforward: rank on page one, get the click. That playbook is becoming obsolete. ChatGPT now has 800 million weekly active users—double what it had in February 2025—and 87.4% of all AI referral traffic to websites comes from that single platform.
optimising Your Content for AI Search: The Complete AEO Guide
AI Answer Engine Optimisation (AEO) is the practice of structuring content so it gets cited by ChatGPT, Google AI Overviews, Perplexity and Claude. Research from Princeton University demonstrates that AEO strategies can boost your visibility in AI-generated responses by up to 40%—and with Gartner predicting organic search traffic will decline by 50% by 2028, getting this right isn't optional.
Why Traditional SEO Isn't Enough Anymore
The fundamental shift? AI engines don't show ten blue links and let users choose. They make the choice for the user—synthesising information from multiple sources to provide a single, authoritative answer. Your brand either gets recommended within that response, or it doesn't exist in the conversation.
The Numbers That Matter
- 50%+ of B2B buyers now use AI to research purchasing decisions before visiting vendor websites
- AI-referred visitors convert at 3-15x higher rates than traditional organic traffic
- Session duration from AI referrals averages 7:35 versus 4:41 for Google organic
- By 2028, Gartner predicts organic search traffic will decrease by 50% or more
Here's what makes this particularly valuable: visitors who discover your brand through AI recommendations arrive with higher intent and more context. They've been pre-sold by the AI's endorsement. According to HubSpot research, these visitors convert at 3x the rate of traditional search visitors. This is why integrating AEO into your content marketing strategy is now essential.
How AI Answer Engines Actually Work
Understanding the mechanics behind AI search is essential before you can optimise for it. As we've explored in our guide to SEO in the age of AI, three concepts define how these systems process and surface content.
Query Fan-Out: AI Breaks Questions Apart
When someone asks an AI a question, it doesn't search for that exact query. Instead, it breaks the question into multiple sub-questions—a process called query fan-out.
Someone asking "What's the best CRM for a manufacturing company?" triggers the AI to simultaneously consider: What features do manufacturers specifically need? What's the typical budget range? Which systems integrate with common manufacturing software? What do existing manufacturing users say?
The AI finds answers to all these sub-questions and synthesises them into one response. If your content only answers the main question but doesn't address these sub-questions, you won't get recommended. This is why creating comprehensive pillar pages and topic clusters has become even more critical.
Personalisation: Every Answer Is Unique
Unlike Google, which shows largely the same results to everyone searching the same term, answer engines create highly personalised responses. A marketing director in London asking about marketing automation may receive a completely different answer than one in Manchester—even with identical queries.
This is why generic, broad content performs poorly. Content that speaks to specific personas, specific industries, and specific use cases wins. "Marketing Automation Guide" loses to "How Manufacturing Companies with 50-200 Employees Can Implement Marketing Automation." Our approach to contextual marketing becomes even more powerful in the AI search era.
From Clicks to Recommendations
Traditional SEO success meant getting the click. AEO success means getting the recommendation. The user journey has fundamentally changed:
| Traditional SEO | Answer Engine Optimisation |
|---|---|
| Get website to rank on page 1 | Get brand mentioned within AI response |
| Success = The click | Success = The recommendation |
| Search → Click → Visit → Convert | Ask AI → Get recommendation → Research brand → Convert days later |
Platform-Specific Considerations
Each major AI platform has distinct characteristics that influence how they discover and cite content. Understanding these differences helps you prioritise your optimisation efforts—much like how we tailor SEO strategies for different search engines.
ChatGPT
Favours established domains (45.8% of citations from sites 15+ years old) and Wikipedia (47.9% of top-10 citations). Relies heavily on Bing's index for real-time retrieval. Produces the longest responses (1,686 characters average) with the most links per response (10.42 average).
Google AI Overviews
Content freshness is particularly important—recently updated pages are 2.5x more likely to appear. Heavily cites Reddit (21%), YouTube (29.5%), and LinkedIn. 46% of citations come from the top 10 organic results, so traditional SEO still matters.
Perplexity
Prioritises educational content and AI-specific domains. Provides exactly 5 links in 99% of responses. 82% semantic similarity with ChatGPT in citation preferences. G2 captures 75% of B2B software review citations.
Claude
Favours longer, coherent passages with clear explanations. Prefers peer-reviewed content and comprehensive sources. Capterra dominates for B2B software citations. Fewer direct links but higher-quality source selection.
Critical technical note: None of these AI crawlers execute JavaScript. If your content relies on client-side rendering, it's invisible to AI systems. Server-side rendering is mandatory for AI visibility—something we address in our technical SEO services.
The 7-Point Content Structure for AI Citation
These structural tactics help content get cited by answer engines. You can implement them to existing content in hours, not weeks. Each point is backed by research from the Princeton GEO study and SE Ranking's analysis of 129,000 domains. These principles align closely with the white hat SEO techniques we've always advocated.
1. Put the Answer First
Answer engines need to know within the first sentence that your content contains the answer they're looking for. If they have to scan three paragraphs of context, they'll move on.
The rule: Your opening sentence must completely answer the primary question. No burying the lead.
Bad: "In today's competitive B2B landscape, companies are looking for better ways to manage their sales pipeline..."
Good: "The most effective way to prioritise sales leads is by using a lead scoring system that ranks contacts based on their fit and engagement level."
2. Go a Click Deeper
After your direct answer, provide 2-3 short paragraphs (150-200 words total) that expand with context, definitions, and methodology. This signals to answer engines that your content is credible and complete—not just a shallow, one-sentence answer.
Pattern: Answer → Explanation. First sentence = direct answer. Next 2-3 paragraphs = why this answer is correct and how to act on it. This is exactly the approach we use in our content marketing strategies.
3. Reference Original Data Throughout
Answer engines actively seek net new information to cite. The Princeton GEO study found statistics addition produced a 41% visibility improvement in AI-generated responses.
You don't need expensive surveys. Mine existing data: CRM reports, client results, sales call insights, customer success patterns. "Analysis of 50 UK manufacturing clients showed average deal cycles of 4.2 months" is original data that answer engines can't find anywhere else. If you're using HubSpot, you have a goldmine of data to draw from.
4. Include a Comprehensive FAQ Section
This is where you capitalise on query fan-out. Every piece of content should include a FAQ section with at least 3-5 related questions, structured as:
- H3 or H4 heading: The question exactly as someone would ask it
- First sentence: Direct, one-sentence answer
- 2-3 sentences: Brief explanation or context
Technical specification: FAQ answers should be 30-50 words per response for optimal extraction.
5. Add Structure Extensively
Answer engines are "lazy readers"—they scan for bullet points, headers, tables—anything that lets them quickly extract information. 78% of AI Overviews include lists.
Optimal specifications:
- Lists work best with 5-8 bullet points of 10-50 characters each
- Tables should not exceed 5 rows by 3 columns
- Section lengths of 120-180 words between headings correlate with higher citations
- Paragraphs under 4 sentences
6. Make Each Section Standalone
Answer engines don't read content top to bottom. They use "chunking" where they extract individual passages and evaluate them independently. Every section must make sense even if AI hasn't read what came before or after.
Test this: Can someone understand this paragraph without any surrounding context? If not, add context. Restate key terms in each section. Use "HubSpot" instead of "it," use "manufacturing companies" instead of "they."
7. Tie Every Point Back to Your Solution (Most Critical)
If you only implement one point from this list, make it this one. This is the difference between educating AI and getting recommended by AI.
Without product connection, you're making answer engines smarter without getting credit. You become free education for ChatGPT, but when someone asks for a recommendation, AI suggests your competitor because they better connected their content to their solution.
Frequency: Reference your product, service, or approach in every paragraph or every other paragraph. This might feel like too much, but you're training AI to understand why your brand is relevant to this topic.
Building Authority Through Mentions (Not Just Backlinks)
For 20 years, SEO professionals obsessed over backlinks. That playbook is becoming obsolete for AI search. Answer engines don't care about backlinks. They care about mentions.
Ahrefs' 2025 analysis of 75,000 brands found web mentions correlate at 0.664 with AI visibility versus only 0.218 for backlinks. This represents a fundamental shift: LLMs don't use PageRank but interpret human language and infer context from mentions.
A "mention" is any time your brand, product, or service is positively referenced in online content—whether Reddit threads, LinkedIn posts, YouTube videos, review sites, blog articles, or podcasts. The mention doesn't need to be hyperlinked. What matters is the context and frequency. This is where a strong social media strategy becomes essential for AEO.
Where to Build Mentions
Platform-specific statistics reveal where to focus:
- Reddit: Presence in AI Overviews increased 450% from March to June 2025. Accounts for approximately 7.15% of all AI Overview citations. OpenAI has a $60M data licensing deal with Reddit.
- YouTube: Receives 29.5% of AI Overview citations—more than Wikipedia. Video types most cited: instructional how-tos (47%), product demos (38%), visual demonstrations (41%).
- G2 and Capterra: 100% of ChatGPT-recommended software tools have Capterra reviews. 99% have G2 reviews. A 10% increase in reviews correlates with 2% increase in AI citations.
When you secure a mention, provide messaging about HOW to describe your solution. Answer engines learn your positioning from these descriptions. "Whitehat is a HubSpot Diamond Partner specialising in ethical SEO and inbound marketing for UK B2B companies" beats "Whitehat is a marketing agency." Learn more about our positioning on our about us page.
Technical Requirements for AI Visibility
Pages containing robust schema markup are 3.7x more likely to appear in AI summaries. Google explicitly recommends JSON-LD format. At minimum, implement:
- FAQPage schema for FAQ sections (critical priority)
- Article schema with author E-E-A-T information (critical priority)
- Organisation schema on homepage (critical priority)
- HowTo schema for step-by-step content (medium priority)
- Speakable schema for voice assistants and AI extraction (medium priority)
Robots.txt Configuration
Each major AI platform operates distinct crawlers. For maximum AI visibility while protecting training data:
- Allow: OAI-SearchBot, ChatGPT-User, Claude-SearchBot, Claude-Web, PerplexityBot
- Optional block (training only): GPTBot, ClaudeBot, Google-Extended
- Always allow: Googlebot, Bingbot (ChatGPT Search relies heavily on Bing's index)
Important: Submit your sitemap to both Google Search Console AND Bing Webmaster Tools. This is critical for ChatGPT visibility specifically. If you need help with technical SEO implementation, our SEO audit services can identify and fix these issues.
The 4 Metrics That Actually Matter for AEO
Traditional SEO metrics (keyword rankings, organic traffic, backlinks) provide incomplete visibility into AEO performance. Track these four instead—and if you're using HubSpot, you can configure custom dashboards to monitor these. Our HubSpot consultants can help set this up.
1. AI Visibility
For each query you care about, is your brand being recommended? Benchmark: 40%+ visibility on priority queries = Excellent. Under 20% = Significant opportunity.
2. AI Share of Voice
Of all AI responses mentioning solutions in your category, how often is your brand named versus competitors? Track monthly to see if you're gaining or losing share.
3. AI Citations
How often do answer engines use YOUR website content (not just mention your brand)? When AI cites your content, the description will be more favourable than third-party mentions.
4. AI Referral Demand
Visits, conversions, and revenue from people who first encountered your brand through AI recommendations. Add "How did you first hear about us?" with AI options to conversion forms.
90-Day Implementation Roadmap
This roadmap integrates with your existing HubSpot content strategy to deliver measurable results within a quarter.
Days 1-30: Foundation
- Test 10-15 key questions across ChatGPT, Perplexity, and Google AI Overviews
- Verify robots.txt allows AI search bots
- Submit sitemap to Google Search Console AND Bing Webmaster Tools
- Add answer-first formatting to top 5 pages
- Implement Organisation schema on homepage
Days 31-60: Content Enhancement
- Apply 7-point checklist to next 10 high-value pages
- Create FAQ sections with schema on top content
- Add original data and statistics to pillar content
- Launch systematic review request campaign (target 10+ new reviews)
- Begin guest post outreach to 5 high-citation publications
Days 61-90: Scale
- Optimise content for each platform's specific preferences
- Create comprehensive comparison content
- Implement HowTo and Speakable schema where relevant
- Full measurement review: visibility, citations, referral traffic, branded search
- Plan next quarter priorities based on data
Expected Results Timeline
- 2-4 weeks: Initial visibility signals, first citations possible
- 2-3 months: Measurable visibility improvements for low-competition queries
- 3-6 months: Compounding effects—more citations, branded search increases
- 6-12 months: Significant business impact—conversion improvements, market share gains
Frequently Asked Questions
What is AI Answer Engine Optimisation (AEO)?
AI Answer Engine Optimisation (AEO), also called Generative Engine Optimisation (GEO), is the practice of structuring and formatting content so it gets cited by AI platforms like ChatGPT, Google AI Overviews, Perplexity and Claude. Unlike traditional SEO which aims for page-one rankings, AEO focuses on getting your brand recommended within AI-generated responses.
How long does AEO take to show results?
Initial visibility signals can appear within 2-4 weeks. Measurable improvements for low-competition queries typically emerge in 2-3 months. Significant business impact—including conversion improvements and market share gains—generally requires 6-12 months of sustained effort.
Does AEO replace traditional SEO?
No, AEO builds upon traditional SEO. Your existing SEO foundation—technical health, content quality, domain authority—still influences which pages AI systems discover. AEO adds a layer of optimisation specifically for how AI engines extract and cite information from your content. Our SEO services now incorporate both traditional and AI optimisation.
Which AI platforms should UK businesses prioritise for AEO?
UK businesses should prioritise ChatGPT (87.4% of AI referral traffic), Google AI Overviews (integrated into standard Google searches), and Perplexity (growing rapidly among B2B researchers). Claude is increasingly used by professionals, particularly in regulated industries requiring careful, nuanced responses.
What is the most effective AEO strategy according to research?
According to the Princeton GEO study, adding statistics to your content produces a 41% visibility improvement in AI-generated responses. Other high-impact strategies include citing credible sources, adding expert quotes, and structuring content with clear FAQ sections that directly answer specific questions.
Ready to Future-Proof Your Search Visibility?
Our team can audit your current AI visibility and build a strategy that gets your brand recommended when it matters most.
Book Your SEO AuditRelated Resources
- SEO in the Age of AI – How AI is reshaping search engine optimisation
- Mastering SEO with a HubSpot Content Strategy – Best practices for HubSpot users
- Local SEO Guide – Optimising for local search and AI visibility
- HubSpot Onboarding Services – Get the most from your HubSpot investment
- Leveraging AI in Social Media Strategy – Strategic planning with AI tools
- About Whitehat – London's largest HubSpot User Group leaders
References & Citations
- Aggarwal, P., et al. (2024). GEO: Generative Engine Optimization. ACM SIGKDD Conference. arxiv.org
- Gartner (2024). Search Engine Volume Will Drop 25% by 2026. gartner.com
- Search Engine Land (2024). Generative Engine Optimization framework. searchengineland.com
- Princeton University (2025). GEO Research. princeton.edu
- ACM Digital Library (2024). GEO Proceedings. dl.acm.org