SEO vs AEO vs GEO.
The Definitive 2026 Guide.

No, but they are tightly related. AEO is the umbrella term covering every system that returns an answer instead of a list — featured snippets, knowledge panels, voice results, AI Overviews. GEO is the LLM-specific subset of AEO. AEO predates LLMs by a decade; GEO is the layer that emerged after generative AI became the dominant retrieval surface. Most agencies use the terms interchangeably; we keep them separate because the tactics that win a featured snippet are not always the tactics that get cited inside ChatGPT.

No. The signals overlap heavily — entity authority, schema graph, editorial mentions, content quality, link equity. What changes is the measurement framework and the prioritisation of off-site work. A serious 2026 programme runs SEO, AEO and GEO as one integrated retainer with a single content roadmap and three measurement layers (rankings, AI Overview presence, LLM citation share).

No. Click-through rates on informational queries are compressing because the AI Overview answers them in the SERP, but the signals that decide which sources Google's Gemini, ChatGPT and Perplexity cite are largely the same signals that earned a top-10 organic ranking — authority, content depth, schema clarity, editorial corroboration. SEO is being reshaped, not killed. The brands winning AI search are almost always brands that already rank well organically.

Depends on your buyer. B2B SaaS and enterprise buyers use ChatGPT and Perplexity heavily for shortlisting — GEO is now non-negotiable. D2C and ecommerce see growing AI-Overview share on category and comparison queries — AEO matters most. Local services still see most of their pipeline from classic SERP and Maps — SEO is still the centre of gravity. The right answer for almost every brand is to invest in all three but weight the budget against where your buyers actually research.

Through controlled prompt audits. We run a fixed prompt set across ChatGPT, Gemini, Claude and Perplexity each month, recording when the brand is cited, the position of the citation, and the sentence in which it appears. That gives a defensible share-of-voice metric across LLMs. We also monitor referrer traffic from the LLMs that do pass it (Perplexity, Gemini search) inside GA4, segmented by source. The combination of prompt-audit data plus referrer attribution gives a complete GEO measurement framework.

Almost all of them. Schema markup, internal linking, page speed, content depth, Core Web Vitals, crawlability, freshness and editorial backlinks all directly affect how LLMs retrieve and rank a brand at runtime. The GEO-specific layer that does not exist in classic SEO is distributed citation footprint — Reddit, Wikidata, podcast transcripts, niche directories — because LLMs were trained on a much wider source set than Google ever indexed.

Faster than people expect on retrieval-driven engines (Perplexity, Bing Copilot, Gemini search) — measurable citations within 60 to 90 days because they retrieve live from the web at query time. Slower on training-driven engines (ChatGPT, Claude default mode) — typically 6 to 9 months for meaningful citation share because the model has to retrain on text that mentions the brand. Most clients see early Perplexity wins inside the first quarter and ChatGPT share-of-voice gains compounding from month four onward.