GEO: Generative Engine Optimization
Pranjal Aggarwal Vishvak Murahari Tanmay Rajpurohit Ashwin Kalyan Karthik R Narasimhan Ameet Deshpande
The advent of large language models (LLMs) has ushered in a new paradigm of
search engines that use generative models to gather and summarize information
to answer user queries. This emerging technology, which we formalize under the
unified framework of Generative Engines (GEs), has the potential to generate
accurate and personalized responses, and is rapidly replacing traditional
search engines like Google and Bing. Generative Engines typically satisfy
queries by synthesizing information from multiple sources and summarizing them
with the help of LLMs. While this shift significantly improves \textit{user}
utility and \textit{generative search engine} traffic, it results in a huge
challenge for the third stakeholder -- website and content creators. Given the
black-box and fast-moving nature of Generative Engines, content creators have
little to no control over when and how their content is displayed. With
generative engines here to stay, the right tools should be provided to ensure
that creator economy is not severely disadvantaged. To address this, we
introduce Generative Engine Optimization (GEO), a novel paradigm to aid content
creators in improving the visibility of their content in Generative Engine
responses through a black-box optimization framework for optimizing and
defining visibility metrics. We facilitate systematic evaluation in this new
paradigm by introducing GEO-bench, a benchmark of diverse user queries across
multiple domains, coupled with sources required to answer these queries.
Through rigorous evaluation, we show that GEO can boost visibility by up to
40\% in generative engine responses. Moreover, we show the efficacy of these
strategies varies across domains, underscoring the need for domain-specific
methods. Our work opens a new frontier in the field of information discovery
systems, with profound implications for generative engines and content
creators.