GEO, the New Age of Search
- May 7
- 2 min read
Updated: May 8
Jason Cober, Senior Consultant Regulatory Affairs Ad Promo & Digital
Consumer search is rapidly evolving in response to emerging AI capabilities and marketers are adapting content design to ensure products not only appear in search results but are presented accurately in AI summaries and LLM responses. From Google search to email to Adobe Acrobat, AI-generated summaries offer a faster, more efficient channel to connect consumers with search results. Further, recent data suggests there is an ongoing shift in consumers use of LLM chat to search for information about brands and products. But what does this mean for the future of digital marketing? Enter Generative Engine Optimization.
What is Generative Engine Optimization?
Generative Engine Optimization (or GEO) is the optimization of digital assets (websites, social media, etc) for discovery in AI-generated summaries, search results, and LLM chat responses. GEO focuses on presenting information in formats and structures that will enable the content to be discovered by AI Agents and then presented within AI-generated summaries or LLM chat responses.
How is GEO different from SEO?
In some regards, GEO is an evolution of SEO. To be clear, GEO and SEO should be used in combination with one another and GEO is not a replacement for SEO. The two work together. SEO drives search result rankings and visibility within search – a key driver in AI agent data discovery. GEO is focused on ensuring brand content is presented in AI-generated responses or cited as a reliable source of information for AI-summary clickthrough.
How does GEO surface content to AI summaries?
GEO works through several different approaches but is primarily a design principle that informs and guides the structure of web content for easy indexing by AI agents. GEO-centered web design principles include the use of clear, plain language headers, FAQs, and authoritative presentations. Websites designed with GEO-first principles are cleaner and easier for AI agents to parse and extract information from. This in turn allows for efficient and accurate presentation with generated summaries.
Why is Generative Engine Optimization important?
Consumers are increasingly turning to AI-generated summaries and LLM chat for search. Pharma brands must ensure that the information presented to consumers through these channels is discovered through reliable sources and accurately presents facts about their products. Most LLMs are trained on information from the internet during pre-training and then rely on external sources to develop answers to user prompts. Improved AI visibility increases the likelihood that a product website will be presented in an AI-generated response as a trusted, authoritative source.
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