The evolution of online search

Access to online information is undergoing a radical transformation. Users are increasingly relying on large language models (LLMs) to get direct answers, rather than navigating through a myriad of links.

Tools like ChatGPT and Perplexity synthesize information from various sources, providing immediate answers within the interface. This shift poses new challenges for brands and publishers: how to ensure visibility when the traditional click-based model is in decline?

Beyond the click: new visibility strategies

For years, search engine optimization (SEO) has been based on a consolidated cycle: content publication, ranking in search results, click acquisition, and performance measurement. Traffic, impressions, and engagement were the key metrics.

The advent of LLMs requires a rethinking of this approach. Brands need to explore new strategies to influence the visibility of their content within AI-generated responses. This may include a greater focus on the quality and accuracy of information, as well as the ability to provide concise and relevant answers to user questions.

For those considering on-premise deployments, there are trade-offs to consider. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these aspects.