Search Engine Optimisation (SEO) is a digital marketing strategy that you've almost certainly heard before. It aims to increase a website's visibility on search engine results pages (SERPs) and, in the instance of Google Maps, ensure that a physical premises is shown to someone searching for a location on maps. It involves optimising various elements of a website and business profile, including its content, architecture, and backlinks, to align with the algorithms used by search engines like Google. The goal is to rank higher on SERPs for relevant keywords, thereby attracting more organic traffic and potential customers. The beauty of SEO, is that once you are ranking, traffic is "free" so you're not having to pay every time someone clicks your link.

However, the landscape of information retrieval is rapidly evolving. With the rise of Large Language Models (LLMs) like OpenAI's GPT-3 and GPT-4, the way we search for and consume information is changing. Instead of scrolling through pages of search results, users are increasingly turning to AI models that provide direct, conversational responses to queries.

This shift has given rise to a new concept: Large Language Model Optimization (LLMO). Similar to SEO, LLMO aims to ensure that a business or entity is accurately represented in the responses generated by LLMs. Techniques for LLMO can range from directly providing information to the creators of the LLM, fine-tuning the LLM with specific data, or using in-context learning to guide the model's responses.

As we move forward from 2023, the importance of LLMO is expected to grow. Traditional SEO strategies may not be as effective in a world where LLMs dominate the information retrieval landscape. Businesses and individuals will need to adapt their strategies, focusing not just on SERPs, but also on how they are represented in the vast knowledge base of LLMs.