Evaluating LLMs/AI for Media Planning in R

Havas Media's exploration of LLMs for media planning in R highlights the potential for these models to generate convincing media recommendations in mere seconds. The article delves into the importance of verifying the accuracy of these recommendations, ensuring that reach calculations are correct and assumptions are transparent. For website owners, this development means that media planning strategies may soon be influenced by LLMs, potentially altering the way ads are targeted and delivered to their sites. As a result, website owners may see changes in ad traffic and revenue, and it is crucial for them to understand how LLM-driven media planning works and how it may impact their online presence. To prepare for this shift, website owners can take several steps: first, monitor their website's traffic and ad performance closely to identify any changes that may be attributed to LLM-driven media planning; second, review and update their llms.txt files to ensure that they are accurately tracking and managing AI bot traffic; and third, consider implementing additional analytics tools to gain a deeper understanding of how LLMs are influencing their website's ad ecosystem.