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SEO & AI: How to Measure AI Web Traffic - Firebrand

Originally published on 01/29/2025
Updated on 03/24/2025 to include details on AI Search Intent

As online user behavior continues to evolve, digital marketers must constantly adapt to new technologies and methods of measuring marketing data. The rise of AI tools such as ChatGPT, Gemini, Perplexity, and Copilot have disrupted traditional search behaviors, and in doing so, have created a multitude of challenges and opportunities for digital marketers, particularly SEO specialists. With AI-driven search results and chatbots now influencing how users access information, measuring AI web traffic has become a critical component of SEO strategies.

Just within the last few months we’ve seen an exponential lift in web traffic to our clients’ websites from AI chatbots, and we don’t expect the trend to subside in the near future. This blog post provides insights into today’s biggest questions regarding AI web traffic including how to measure AI web traffic, why it is important, and how to adapt your SEO strategy to maximize your chances for appearing in AI-powered platforms. Let’s dive in!

What is AI Web Traffic?

Broadly, AI web traffic is considered to be visits to a website derived from interacting with AI-powered platforms such as chatbots and AI search engines. Online searchers are increasingly utilizing these new Large Language Model (LLM) based AI tools for a more conversational and interactive way to find information. These platforms can provide searchers with quick answers to questions in a natural language format, often with the ability to ask follow-up questions and clarify details within the same conversation, enhancing the search experience.

Increasingly users are finding the information they need in the Google Search AI Overview, or in traditional featured snippets, without clicking to a website. These are termed “zero-click searches.” The AI-generated search results can include links to the source information, creating a new strategic channel for SEO specialists to incorporate into their marketing mix. As organic search metrics become increasingly impacted by AI-driven searches, we can measure the website traffic these new platforms are generating, and how to maximize brand visibility within the results.

As AI-driven search evolves, understanding the three main types of AI search systems—Training-First, Search-First, and Hybrid—is crucial for SEO teams looking to adapt their strategies and secure citations across these new discovery channels. Each system processes and surfaces information differently and by aligning SEO and content strategies with these models, brands can maximize visibility, secure citations, and remain competitive in the AIO landscape.

Will Seer and Jason Stinnett at Seer Interactive recently broke down the three types of AI search systems:

  • Training-first systems such as Claude and Llama “generate responses based solely on their training data — snapshots frozen in time until the next model update.”
  • Search-first systems such as Google AI Overviews and Perplexity “rely heavily on real-time indexing of web pages … It’s like SEO on steroids, with a dash of content curation.”
  • Hybrid systems such as Gemini and ChatGPT “blur the lines by deciding, often in real time, whether to answer based on their training data or fetch updated information from the web.”

    • Most Commonly Used AI Chatbots

    Some of the most widely used AI chatbots today are ChatGPT, Copilot, Perplexity, and Gemini, with many more rapidly increasing in popularity including Claude.

    © 2025 Firebrand Communications LLC

    Original source: https://www.firebrand.marketing/2025/01/how-to-measure-web-traffic-from-ai

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