Your customers are starting to use large language models (LLMs) to find solutions to problems, but how do you get the timing right?

We'll share with you at least five approaches (at varying levels of complexity) that we are using to understand the timing and depth of this disruption for our clients. Approaches include tracking content that performs in LLMs, comparing visibility in Google against visibility in LLMs, and using existing data to get a feel for when your customer is shifting.

We'll help you answer the question: How can the work you are doing today cater to both conventional search engines and emerging LLM platforms, while winning the hearts and minds of the people consuming these answers?

There is a problem though; today's LLMs are giving "average answers." How do you stand out? The tools to determine LLM visibility are pretty far behind. So, in this session, we'll show you how to build your own tools using AI, mostly.

Note: This course is a recording of a session from the Marketing Artificial Intelligence Conference (MAICON), which was held in September 2024.