Quick comparison
SEO. Goal: click from search results | Measurable via: Search Console, rankings | Timeline: 4–9 months | Tools: keyword research, backlinks, meta tags, internal links | Strongest for: direct website visits, transactional queries.
GEO (Generative Engine Optimisation). Goal: mention in AI answers (ChatGPT, AI Overviews, Perplexity) | Measurable via: manual check in AI tools, Bing Webmaster | Timeline: 3–8 weeks per optimisation | Tools: schema, llms.txt, answer-first content, brand mentions | Strongest for: informational queries, pre-deal trust.
Overlap: 70% of the techniques work for both. E-E-A-T, structured data, fast load time, quality content. The foundation is the same.
The core difference
SEO targets a click from search results. GEO targets a mention inside AI answers (ChatGPT, AI Overviews, Perplexity). Both revolve around authority + structure, but the endpoint differs.
A practical distinction: if someone searches 'best SEO agency London' in Google, you want to be the #1 blue link (SEO goal). If that same person types it into ChatGPT or Perplexity, you want to be the cited source in the AI answer (GEO goal). For informational searches ('how does SEO work') click flow is shifting increasingly toward AI Overviews, that's GEO territory. For transactional searches ('hire SEO agency') traditional search results remain dominant. SEO territory.
What overlaps?
Schema.org structured data. Clear heading structure. E-E-A-T signals (expertise, authority, trust). Fast load time. Mobile-first. Content that answers instead of introduces.
The overlapping techniques are good news: those already seriously focused on SEO have 60–70% of the GEO foundation in place. Schema.org is already required for SEO (FAQ schema, Review schema, LocalBusiness schema) and works directly for GEO citations. E-E-A-T. Google's framework of Expertise, Authority and Trust, is the lens through which both Google's algorithm and AI models assess your content. Investing in E-E-A-T is the most efficient combined investment for both SEO and GEO.
What's GEO-specific?
llms.txt file for AI crawlers. Explicit entity relations. Citable data (own stats, benchmarks). Brand mentions off-site. Answer-first paragraphs (first 60 words = complete answer).
GEO-specific means: techniques that weren't relevant for classic SEO but are crucial for AI search engines. llms.txt is the most unique: it gives AI crawlers a structured table of contents for your site, what robots.txt does for search engine crawlers. Answer-first paragraphs are 'nice to have' for SEO (featured snippet optimisation) but almost mandatory for GEO: AI models extract the first 60–100 words as an answer candidate. Brand mentions off-site (external mentions without hyperlink) were long ignored by SEO specialists, in GEO they're crucial because AI models read text, not follow links.
What's SEO-specific?
Keyword research for search volume. Backlink strategy to specific URLs. Internal linking for topic clusters. SERP position optimisation (meta tags, rich snippets). Local SEO (GBP, citations).
SEO-specific are the techniques that optimise for Google but influence AI search engines less directly. Backlinks are the most pronounced example here: a strong backlink profile raises your domain authority for Google, but an AI model doesn't directly read your backlink profile, it weighs external mentions of your brand and content as trust signals, but via text co-occurrence, not via link graph. Keyword research remains relevant for GEO (you need to know what people search for) but the implementation mechanism differs.
Why you need BOTH
SEO traffic stays. AI Overview traffic grows. No GEO = invisible in ChatGPT and AI Overviews. No SEO = invisible in classic Google without AI. Ignoring both = invisible everywhere.
Concrete numbers: in 2026 AI Overviews are shown for 40–60% of all searches in most markets. That means 40–60% of your potential search demand is filtered by an AI block before the blue links. Those in that block capture attention. Those not in it wait for the remaining clicks. At the same time: ChatGPT, Perplexity and Microsoft Copilot together have more than 500 million active monthly users. B2B buyers use these tools in the orientation phase for research. GEO is not a futuristic investment, it's a now investment.
By industry: when to pick what
Local services (trades, dentist, physio): SEO + GBP is the core, local queries are still predominantly traditional. Add GEO for informational content ('what does a root canal cost') that appears in AI Overviews.
B2B professional services (accountant, marketing agency, IT company): GEO is more urgent here than for consumers. B2B decision-makers use ChatGPT and Perplexity intensively for pre-deal research. Both are necessary.
E-commerce: SEO dominant for product category pages and transactional queries. GEO for comparative questions and informational content ('best running shoes'). Product pages themselves are less relevant for GEO. AI models cite information, not product listings.
Publisher, blog or knowledge platform: GEO is critical, informational content is exactly what AI Overviews cite. Those who don't invest in GEO here lose disproportionately more traffic through AI impression absorption.
Our recommendation: how to decide
Order for those starting from zero: 1) Lay the SEO foundation (technical, on-page, local). 3–6 months. 2) Add the GEO layer (llms.txt, answer-first, FAQ schema), incrementally on top of SEO, not as a separate project. 3) Build brand mentions off-site, content marketing, guest publications, PR.
The most efficient approach: don't treat GEO as a separate channel but as a writing style and technical configuration on top of your existing SEO. Every page you write, you write answer-first. Every FAQ you add, you implement with schema. Every new blog post ends with your llms.txt update. That costs 20% extra time per page but gives you simultaneous SEO and GEO results.
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