Generative Engine Optimization (GEO)

Generative Engine Optimization, abbreviated GEO, is the discipline of structuring a website's content, entity relationships, and authority signals so that large-language-model-powered engines such as ChatGPT, Claude, Perplexity, and Gemini cite the business by name when generating answers. Unlike traditional SEO, which optimizes for ranked links on a search results page, GEO focuses on making content machine-readable and authoritative enough to be selected as a source during the model's retrieval and generation process. This involves building comprehensive entity profiles, publishing citable original research, configuring llms.txt and ai.txt files, and deepening schema markup to provide clear, structured evidence of expertise. For example, a fintech client saw a 3x increase in ChatGPT citations within 90 days of implementing a GEO strategy. The practical takeaway is that businesses investing in GEO today position themselves to capture the growing share of queries answered directly by AI engines.

SEO and GEO both aim to increase a business's visibility, but they operate on fundamentally different surfaces and require distinct optimization strategies. SEO targets search engine results pages, where the goal is to rank a webpage link as high as possible so users click through to the site. GEO targets the text generated by AI models, where the goal is to be named, quoted, or recommended inside the AI-generated answer itself. SEO success is measured in rankings, click-through rates, and organic traffic. GEO success is measured in citation frequency, brand mentions, and recommendation positioning across AI engines. For example, a brand might rank first on Google for a keyword yet never appear in ChatGPT's answer for the same query, because ChatGPT draws on different authority signals. The practical takeaway is that modern visibility strategies need both SEO and GEO running in parallel to cover the full spectrum of how people discover information today.

Wishfy tracks brand citations across four major AI engines: ChatGPT by OpenAI, Claude by Anthropic, Perplexity, and Gemini by Google. Each engine uses different retrieval mechanisms, training data, and ranking heuristics, which means a brand can appear prominently in one engine while being completely absent from another. Wishfy's monthly citation reports break down performance per engine, showing the exact queries where the brand is cited, the position within the answer, and the sentiment of the mention. For example, a SaaS company might find it is cited in 60 percent of relevant Perplexity queries but only 10 percent of equivalent ChatGPT queries, revealing a clear optimization gap. The practical takeaway is that tracking all four engines individually allows Wishfy to prioritize optimization efforts where the largest citation gaps exist, ensuring no major AI surface is neglected.