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A Guide to SEO, AEO, GEO, LLM-O... WTF-O?

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The Alphabet Soup of Modern Search Optimisation

If you’re feeling confused by all the acronyms being thrown around in marketing right now, you’re not alone. We’ve gone from SEO (Search Engine Optimisation) to AEO (Answer Engine Optimisation) to GEO (Generative Engine Optimisation) and now people are talking about LLM-O (Large Language Model Optimisation).

What’s actually happening? Search is fundamentally transforming from ranked lists to synthesised answers. As Kevin Indig puts it, search is moving from abundance to synthesis - with AI delivering single definitive responses rather than multiple options for users to evaluate.

There’s a lot of noise and hype in this space. Let’s cut through it and focus on the tactics that are actually backed by data and cited by multiple experts.

What Is Answer Engine Optimisation (AEO)?

Answer Engine Optimisation is the practice of structuring your content so that AI-powered search tools - ChatGPT, Perplexity, Google AI Overviews, Claude - can accurately surface it in their responses.

Unlike traditional SEO where you’re optimising for blue links and click-through rates, AEO is about becoming the source that AI systems reference and cite when providing answers to user queries.

The key difference: with SEO, you’re fighting for a click. With AEO, you’re fighting for a citation.

What Is Generative Engine Optimisation (GEO)?

GEO is closely related to AEO but focuses specifically on ensuring your brand and content appear prominently when large language models generate responses.

In practice, AEO and GEO are used interchangeably. Both address the same fundamental challenge: how do you maintain visibility when users increasingly get answers directly from AI rather than clicking through to your website?

The Numbers That Matter

Before diving into tactics, here are the statistics that should inform your strategy (sourced from Kevin Indig’s State of AI Search Optimization 2026):

The implication is clear: traditional SEO still matters (ranking in the top 10 helps AI citations), but third-party mentions and technical performance are now equally critical.

Proven Tactics: What Actually Works

After reviewing the research from Kevin Indig, Ethan Smith (Graphite), Omniscient Digital, PostHog, Joost de Valk, and others, these are the tactics consistently cited as effective:

1. Technical Performance (High Confidence)

Multiple sources confirm that fast sites get more AI crawler attention:

This isn’t new advice, but it’s more important than ever. AI crawlers are time-constrained and favour fast-loading, well-structured pages.

2. Content Freshness (High Confidence)

Content updated within the last 3 months performs significantly better for AI citations. This aligns with what both Indig and Omniscient Digital have observed.

The implication: a content refresh strategy is no longer optional. Prioritise updating your highest-value pages regularly.

3. Third-Party Validation (High Confidence)

This is perhaps the most important shift: 85% of brand mentions in AI search come from third-party sources, not your own website.

What this means in practice:

You cannot control AI citations through your own content alone. You need to build presence across the web.

4. Structured Content Formatting (Moderate Confidence)

Multiple sources agree that structured data improves excerpt probability:

5. Conversational Query Coverage (Moderate Confidence)

Ranking for head terms is less important than covering the conversational queries people actually ask AI systems. Think about how someone would phrase a question to ChatGPT, not just traditional keyword targeting.

6. Author Credentials (Emerging Evidence)

Author credentials, certifications, and expertise signals are increasingly important. This aligns with Google’s existing E-E-A-T framework but is now being picked up by AI systems too.

7. Bottom-Funnel SEO First (High Confidence)

The good news? AEO is really just smart bottom-funnel SEO on your website before anything else. Control the narrative with your owned content, then worry about other channels.

Sam Dunning recommends prioritising what your dream clients search when they need your solution now and are comparing options. Create best-in-class pages to hit this intent:

Nail these landing pages, articles and listicles before anything else. Not only are these pages crucial for prospects evaluating your solution, but many have solid chances to rank in classic organic search, AI Overviews, and LLMs.

PostHog also recommends starting with defensive SEO - competitor comparisons, integration guides, and “best tools” roundups. Another good option is low volume keywords. These are easier to rank for and can create a solid base of traffic. Writing dozens of these adds up - don’t underestimate them.

Do this first. Then worry about link building, brand mentions, and moving onto Reddit and other communities when you have the resource or budget ready.

8. Quality Over Gaming (High Confidence)

Google is dumber than you think. It doesn’t understand your content - it understands user behaviour. Users clicking and spending a lot of time reading shows content is good.

If your content doesn’t rank well, it’s probably because it just isn’t very good. Ask yourself:

If not, improve the content first before worrying about technical optimisation.

9. The Three Channels That Work for AEO (High Confidence)

Ethan Smith, CEO of Graphite, identifies three primary tactics that consistently drive AI citations:

  1. Landing pages - Comprehensive, original content addressing specific questions
  2. YouTube videos - AI models cite video content; descriptions are particularly important
  3. Reddit comments - Authentic participation (not spam) in relevant communities where your expertise applies

Smith also highlights an often-overlooked opportunity: help centre optimisation. Your documentation suddenly becomes your highest-converting content channel because AI systems heavily reference support content when answering product-related queries.

10. Authenticity Over Optimisation (High Confidence)

This insight comes from multiple sources but Ethan Smith states it clearly: avoid hyper-SEOed content. AI models detect and penalise content optimised primarily for algorithms rather than genuine helpfulness.

AI-generated content fails because models trained recursively on AI derivatives collapse in quality. Human expertise and firsthand experience matter. Original content is required - there’s no shortcut here.

The AI Platform Shift (Hard Data)

The numbers speak for themselves:

AI platforms like ChatGPT seem to be more influential than Google already for certain audiences.

What to Ignore (For Now)

There’s a lot of speculation in the AEO space. These tactics are frequently discussed but lack strong evidence:

Stick to the fundamentals until better evidence emerges.

The Unintended Consequences of SEO

It’s worth understanding how we got here. Joost de Valk, founder of Yoast SEO, wrote a thoughtful piece on the unintended consequences of SEO.

He acknowledges that while the foundational practices remain sound - readability, content structure, internal linking - the industry developed a checklist mentality. Writers optimised for green lights rather than value. The result was a flood of content that hit the right technical notes but didn’t add real value.

The current industry consensus is shifting toward:

This is good news if you’ve been creating genuinely helpful content all along.

Measuring AI Visibility with Microsoft Clarity

Here’s where things get practical. Microsoft Clarity introduced reporting that shows AI bot traffic and activity across websites, offering transparency into how automated agents crawl and interact with content.

The new “Bot Activity” report is a dashboard that tracks server-side signals to show exactly how AI agents access your site.

Unlike standard analytics that track human visits, this requires a CDN or server integration to capture the “upstream” activity - the scraping and crawling that happens before a user ever sees an answer.

The report breaks down traffic by “Bot Operator” (e.g., OpenAI, Anthropic, Google) and, crucially, “Bot Activity” type, distinguishing between an “AI Crawler” (scraping for training data) and an “AI Assistant” (fetching a live answer for a user).

Why This Matters

AI bots don’t behave like search bots - they don’t just index content, they consume it. What was once hidden in complex server logs is now visible, letting you easily track whether an AI is reading your site 10,000 times a day or ignoring it completely.

This dashboard democratises the “AI Request Share” metric, allowing you to quantify how much of your infrastructure is serving non-human agents versus actual customers without needing a data science team. It effectively separates “Training” (extractive) from “Inference” (potential visibility).

The New Reality: It’s OK Not to Get Traffic

It’s okay not to get traffic. That’s the new reality we have to accept. The real breakthrough here is that now it’s much easier to know whether an AI actually used your content as the basis for those answers.

Previously, “Zero Click” was a black box - you had to guess if your content was fuelling the AI’s response or if you were just being ignored. Now, you have proof. If you see high AI consumption of your content, you know you are winning mindshare and influencing the answer, even if you aren’t getting the click.

This metric finally validates the strategy of “feeding the bot” to maintain brand relevance in a world where the user might never leave the chat interface.

How to Set Up Microsoft Clarity Bot Tracking

  1. Enable Server-Side Integration - You cannot get this data with just the JavaScript snippet. Connect your CDN (Cloudflare, etc.) to Clarity to see the server logs.

  2. Audit “Path Requests” - Identify what AI systems are reading. Are they scraping your high-value proprietary data (pricing, JSON endpoints) or your brand-building content (blog, about page)?

  3. Calculate Your “AI Conversion Rate” - Compare your AI Request Volume (from Clarity) to your AI Referral Traffic (from GA4). If the ratio is massively skewed, you need to rethink your content strategy for agents.

The Three-Stage Pipeline: Retrieved, Cited, Trusted

Kevin Indig outlines a useful framework for thinking about AI search optimisation as a sequential process:

  1. Retrieval Stage - Your content must first enter the candidate pool. This requires proper crawling, indexing, and fast server response times. Without this, nothing else matters.

  2. Citation Stage - Models then select which sources to reference in their answers. This is where content quality, structure, and authority come into play.

  3. Trust Stage - Finally, users validate and act on citations. Your brand reputation and the accuracy of your content determine whether users trust the AI’s reference to you.

Most companies fail at stage one. Fix your technical foundation before worrying about content strategy.

Action Plan: What to Do This Quarter

Week 1: Measure Your Starting Point

  1. Set up Microsoft Clarity with server-side integration
  2. Test your brand in ChatGPT, Perplexity, and Claude for relevant queries
  3. Audit your page load times (aim for under 1 second)
  4. Check your server response times (aim for under 200ms TTFB)

Week 2-4: Fix Technical Issues

  1. Address any page speed issues identified
  2. Ensure semantic HTML structure across key pages
  3. Update content that’s older than 3 months
  4. Add structured data (tables, FAQs) where appropriate

Ongoing: Build Third-Party Presence

  1. Encourage customer reviews on relevant platforms
  2. Participate in industry forums and communities
  3. Seek guest posting and podcast opportunities
  4. Monitor brand mentions across the web

Metrics to Track

People and Companies to Follow

If you want to stay current on AEO and AI search optimisation, these are the voices worth following:

Individuals

Companies and Publications

Tools to Watch

Further Reading

The Bottom Line

The proliferation of acronyms - SEO, AEO, GEO, LLM-O - reflects a genuine shift in how people find information. But the proven tactics remain grounded in fundamentals:

  1. Fast, well-structured websites get more AI attention
  2. Fresh, helpful content gets cited more often
  3. Third-party validation matters more than your own claims
  4. Measurement is finally possible with tools like Microsoft Clarity

Don’t chase every new tactic that emerges. Focus on these fundamentals, measure your progress, and iterate based on data - not hype.

How Growth Method Helps

Growth Method is the only work management platform built for growth marketers. We help you track and optimise your marketing experiments across all channels - including the emerging world of AI search optimisation.

Our platform helps you:

“We are on-track to deliver a 43% increase in inbound leads this year. There is no doubt the adoption of Growth Method is the primary driver behind these results.” — Laura Perrott, Colt Technology Services

We help companies implement a systematic approach to grow leads and revenue. Book a call today.

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