Log file analysis is an underutilized tool in SEO, especially important now due to the rise of AI bots. These logs, particularly access logs, provide raw data about every request made to a website, including details like IP addresses, timestamps, requested URLs, and the user agent strings that identify the bot or browser. While tools like Google Analytics filter out much of this data, log files capture everything, making them valuable for understanding how users and bots interact with a site. The Screaming Frog Log File Analyser simplifies the process of importing and analyzing these logs. Users can easily drag and drop their log files into the tool, select user agents for analysis, and verify bot authenticity against known IP lists. The tool can distinguish between various AI bots, such as those from OpenAI and Perplexity, allowing for detailed insights into their behavior. Users can explore data through several tabs, focusing on metrics like request frequency, response codes, and geographic distribution of bot traffic. Key areas to monitor include response codes and errors. High levels of 4XX or 5XX errors can indicate issues blocking AI bots from accessing content. For citation bots, these errors can mean missed opportunities for visibility. Analyzing which URLs receive the most requests helps identify valuable content for AI training and citation. If important pages aren’t getting crawled, it may signal issues with internal linking or robots.txt configurations. This analysis is critical for optimizing how content is presented to AI systems, ultimately influencing visibility and engagement.