SEO vs GEO vs AEO vs LLMO: the 2026 alphabet of search, explained

Search broke, then it rebuilt itself four times in 18 months. Here's what the acronyms actually mean, which ones matter, and what to do differently if you want to be found in 2026.

The one-line version

• SEO — get ranked in Google's list of blue links. Still works.
• GEO — get your content surfaced inside AI-generated answers. New.
• AEO — get cited in dedicated answer engines (Perplexity, You.com, Brave Search). New.
• LLMO — get referenced when users ask ChatGPT, Claude or Gemini a question. Newest.
• AIO / GAIO — the umbrella term covering all of the above.

The tactics overlap heavily. The measurement doesn't.

Why this happened

For 20 years, "search" meant "Google." A user typed a query, Google returned ten blue links, the user clicked one, the destination site measured the visit. That loop drove a trillion dollars of commerce.

In late 2024, three things happened at once:

1. Google started replacing results with generated answers. First SGE (Search Generative Experience), then productionised as AI Overviews, now standard above the fold for most informational queries.
2. Perplexity crossed the threshold from curiosity to habit. A whole category of users — researchers, analysts, curious professionals — now starts their research inside Perplexity, not Google.
3. ChatGPT added search. OpenAI wired ChatGPT directly to Bing's index, giving it the ability to answer "what's Amora Digital's pricing?" with real, current information and cite sources.

The implication: if your strategy was "rank on Google," you were now competing for a small fraction of the attention that used to flow through that channel. The remaining attention is fragmented across answer engines, each with its own crawlers, citation behaviour, and optimisation playbook.

The acronyms, defined

SEO — Search Engine Optimisation

The original. Everything you've done for the last 20 years to rank on Google and Bing — keyword research, on-page optimisation, technical SEO, backlinks, content clustering — is still SEO. It still works. Google still drives the majority of informational traffic for most businesses.

What's changed: Google's own SERPs now include AI Overviews at the top for ~40% of informational queries. Your page might be ranked #1 and still not get the click, because the user read the answer in the Overview and didn't need to.

GEO — Generative Engine Optimisation

Optimising your content to appear inside AI-generated answers, rather than as a destination users click to afterwards. This is specifically about:

• Google AI Overviews / SGE
• Bing's generative answers
• Any SERP feature that synthesises multiple sources into a single response

GEO tactics skew toward citation-worthiness: clear claims, unambiguous sourcing, structured data that makes your page parseable, timestamped statements. If your page is the one Google's model "quotes" in the generated answer, you get the citation, the brand visibility, and often a click-through from users who want the fuller context.

AEO — Answer Engine Optimisation

Optimising for dedicated answer engines — services whose primary interface is a direct answer with citations, not a list of links. The big ones in 2026:

• Perplexity — the market leader for serious research queries.
• You.com — enterprise-focused with custom knowledge bases.
• Brave Search (Summarizer) — privacy-focused with AI summary.
• Kagi — paid, serving a smaller but high-value audience.
• Duck.ai — DuckDuckGo's answer layer.

AEO overlaps significantly with GEO, but the sources these engines trust differ. Perplexity leans on recent, reputable sources; You.com allows users to pin their own sources; Brave has a more utilitarian summary style.

LLMO — Large Language Model Optimisation

The newest of the acronyms, and the one people confuse most. LLMO is optimising to be cited or recommended when users ask LLM-based conversational interfaces a question. The distinction from AEO is subtle but real:

• AEO targets products whose core feature is "search with AI answers."
• LLMO targets the frontier LLMs themselves — ChatGPT, Claude, Gemini, Mistral's Le Chat, DeepSeek — whether or not they're doing real-time retrieval.

For models that retrieve in real-time (ChatGPT Search, Claude browsing, Gemini grounding), LLMO overlaps heavily with AEO and GEO.

For models that answer from training data (plain ChatGPT without browsing, plain Claude), LLMO is about getting your content into the training corpus in the first place — which means being findable by crawlers like GPTBot, ClaudeBot, and CCBot (Common Crawl).

AIO / GAIO — AI Optimisation umbrella

Catch-all terms. "AIO" for AI Optimisation, "GAIO" for Generative AI Optimisation. Useful if you're writing a blog post about all of the above at once. Less useful as a technical distinction, because the tactics under the umbrella vary more than they share.

SGE and AI Overviews

SGE — Search Generative Experience — was Google's internal name for the generative-answer experiment. In 2024–2025 it graduated out of experimental status and became AI Overviews, the brand name for what you now see at the top of most Google SERPs. When people say "SGE" in 2026 they almost always mean AI Overviews.

Copilot Search

Microsoft's integrated answer experience across Bing, Edge, and Windows. Powered by Bing's index + GPT-class models. If you optimise for Bing (which you should), you're largely optimising for Copilot Search as a side effect.

What tactics actually matter

Here's the uncomfortable honest truth: 80% of the tactics for SEO, GEO, AEO and LLMO overlap. The 20% that differs is in measurement and specific formats. The foundations are the same:

Foundations (cover all four at once)

1. Technical baseline that renders for AI crawlers. Your content must load without requiring JavaScript to hydrate, because many AI crawlers don't execute JS. Server-side rendering or static generation. Fast response times. Clean HTML.
2. Entity modelling via schema.org. Every page should declare what it's about in structured data — Organization, Service, FAQPage, Article, Product. AI engines parse this into a knowledge graph.
3. Clean URL structure and internal linking. Makes it easy for crawlers to build a mental map of your site.
4. Citation-worthy content structure. Clear claims, supported by specific evidence, with timestamps. AI engines preferentially quote content that has a clean "claim → evidence → source" structure.
5. Authority signals. Real company information (ABN, address, phone), named authors, bylines, about pages, long-form case studies. AI engines trust sites with verifiable provenance.

Specifics per surface

For SEO (Google / Bing classical):

• Keyword research and on-page targeting still works.
• Core Web Vitals matter.
• Backlinks matter, but less than they used to.
• Freshness signals matter a lot for YMYL queries.

For GEO (AI Overviews, Bing generative):

• Pages that answer the question directly in the first paragraph get cited.
• Lists, tables and bullet formats are quoted more often than prose.
• Pages with FAQPage schema get higher inclusion rates.
• Brand mentions on other high-authority sites matter — AI engines cross-reference.

For AEO (Perplexity, You.com, Brave):

• Source authority matters a lot. Perplexity has a visible "quality" weighting.
• Recency matters — content that's been updated recently gets more citations.
• Unique data or primary research is disproportionately cited.

For LLMO (ChatGPT, Claude, Gemini):

• For real-time search-enabled answers: same tactics as AEO and GEO.
• For training-data inclusion: be crawlable by GPTBot, ClaudeBot, and CCBot. An llms.txt file at your site root helps LLMs understand your site.
• Brand-specific knowledge is captured most reliably when your own site is the canonical source. If Wikipedia, Crunchbase, and your site agree on a fact, LLMs learn it.

How to actually measure it

This is where people get stuck. Classical SEO had clear metrics: rank position, impressions, clicks, conversions. AI search is harder.

Here's what works in 2026:

1. AI Overviews impressions in Google Search Console. Google added this. Check it weekly.
2. Direct referral traffic from Perplexity, ChatGPT, Claude. Shows up in analytics as referrers like perplexity.ai and chatgpt.com. Low volume per visit but very high intent.
3. Prompt-testing frameworks. A set of questions your buyers might ask the AI engines, run monthly against each engine, logging whether your brand or content is cited. We run ~50 questions across ChatGPT Search, Claude, Perplexity and Google AI Overviews per month for each client.
4. Branded query volume in Google Search Console. Rising "amoradigital" style searches mean AI engines are surfacing you and users are verifying. One of the earliest leading indicators.
5. Conversation-attributable closed deals. Harder to measure, but the "I found you via ChatGPT" lines show up in sales calls once this works.

What doesn't work

• Stuffing your page with every acronym you can find. LLMs down-rank low-information content. The page you're reading should be useful whether or not you know what any of these words mean.
• AI-generated content at scale without editing. Easy to detect, low citation rate, erodes your authority over time.
• Fake author bios and E-E-A-T gaming. Real people, real credentials, real track record. Or nothing.
• Paid-link schemes. They've never worked well for SEO. They work worse for AEO / LLMO.
• "AI-optimised" vendors promising guaranteed citations. Nobody can guarantee a citation. Run from anyone who says they can.

What we actually do for clients

Our SEO + AI-search engagement covers all four surfaces as one service, not four. Baseline includes:

• Technical audit (including AI-crawler render testing)
• Entity modelling with full schema.org coverage
• Citation-worthy content clustering
• llms.txt and llms-full.txt site summaries
• Digital PR to build source authority
• Monthly prompt-testing report across all major AI engines
• Standard Google Search Console + Bing Webmaster + IndexNow push

From $2,400/month retainer. Typical clients see branded AI-search citations within 3–4 months and meaningful referral traffic within 6–9.

Summary

• If your SEO is already good, your GEO, AEO and LLMO start from a solid base.
• If you're starting from scratch, don't build four separate strategies. Build one strong content and technical foundation, then add the specific measurement and formatting work per surface.
• Don't trust anyone selling "GEO-guaranteed rankings" or "LLMO for $300/month." The real work is the same work SEO always was, applied across a wider surface.
• Measure with a mix of Google Search Console, referral analytics, and monthly prompt testing. Branded-query growth is your earliest leading indicator.

Questions? Email <hello@amoradigital.com.au>. Or check our SEO + AI search service page for scope and pricing.