Generative engine optimization (GEO) is the practice of structuring content so that large language models cite it in AI-generated answers. Unlike traditional SEO, which targets ranked links in Google’s blue-link results, GEO targets citation and inclusion in responses from ChatGPT, Perplexity, Google AI Overviews, Claude, and similar systems.
The mechanics of GEO differ from traditional SEO in important ways. LLMs do not crawl the web in real time. They are trained on large datasets and, in some cases, retrieve information from the web at query time using retrieval-augmented generation. Getting cited requires that your content is indexed, clearly attributed to a named entity, structured around direct answerable statements, and corroborated across multiple sources.
The three highest-leverage GEO tactics for B2B consultants are entity establishment (making your brand clearly recognizable across schema, Wikidata, and third-party citations), direct answer structure (writing content where the first sentence of each section answers the question the heading poses), and source corroboration (ensuring your key claims appear on your site, your LinkedIn, your Google Business Profile, and in third-party articles). GEO is not a replacement for SEO. It is an additional layer applied to content that is already well-optimized for traditional search.
