The Ultimate Large Language Model Optimization Guide for Online Retailers

Aside from the Internet itself, it’s safe to say no technology has had a greater impact on how people shop over the last two decades than the Search Engine. Today 89% of shoppers consult a search engine results page (SERP) when making a purchase. 

Now another results page threatens to test the SERP’s primacy: The CHERP. With their vast knowledge bases and lightning-fast response times, LLM-powered chatbots like OpenAI’s ChatGPT, Google’s Bard and Microsoft’s Bing are poised to become another indispensable tool in shoppers’ hunt for just the right product.  

In a move that speaks volumes to the importance of this new technology in the buying journey, Amazon is working on its own chatbot that will “reimagine Amazon Search with an interactive conversational experience” to help customers make better buying decisions. 

Some call it Large Language Model Optimization (LLMO). Others are calling it Generative AI Optimization (GAIO). Still others are labeling it Answer Engine Optimization (AEO). The name will likely change as the practice matures, but one thing is for sure: it’s here to stay. 

Key Takeaways

This guide is intended to help online retailers optimize their product content to ensure their products appear prominently in results as shoppers turn to LLM-powered chatbots like ChatGPT, Bard and Bing to research. It will cover: 

1. 1. How shoppers are using Bard, Bing and ChatGPT on their path to purchase, 
   2. How LLMs use product information to help shoppers find the right products, and 
   3. How retailers should structure their content to ensure their products appear prominently in LLM chat results.