In an AI search world, the key metric is no longer a human clicking a link but an AI's user agent visiting a page to gather information. Marketers can track these bot visits via CDN integrations to understand which content is influencing AI responses, treating it as the new "click."

Traditional metrics like click-through rates don't apply to AEO. Brands should instead measure its ROI by tracking increases in branded search, direct site traffic, and direct referral traffic. These metrics indicate that AI-driven recommendations are successfully influencing consumer demand, even without a direct click.

Instead of guessing how to make your site more compatible with new AI browsers, directly ask the AI itself. Prompt ChatGPT with your URL and ask what changes are needed on your site to ensure the right answers appear when users search with the Atlas browser.

Despite the rise of AI, Google still handles over 94% of searches. However, marketers must focus on LLM visibility, as customers sourced from AI search engines convert at a 4.4 times higher rate. This makes it a critical, complementary channel, not a replacement for traditional SEO.

Tracking success in LLMs isn't about UTMs, as it's top-of-funnel discovery. Instead, use three key metrics: Share of Voice (% of time you appear vs. competitors), Mention Rate (% of time your brand is mentioned), and Citation Rate (% of time your site is linked in an answer).

Marketers must now measure their brand's presence in AI-powered search results (e.g., ChatGPT, Google AI Overviews). This "AI visibility" metric is crucial for demonstrating relevance and can be tracked without expensive tools, making it an essential addition to any marketing dashboard.

The first step in a modern visibility audit is to check if your brand, products, or services are cited in Google's AI-generated answers. This is a critical new battleground for visibility that precedes traditional search results and requires dedicated attention.

In AI interfaces, a brand's content can influence millions of purchase decisions without a single user clicking a link or seeing the source material. Key metrics must shift from traffic to influence, recommendation rates, sentiment, and share of voice within AI-generated answers.

AI tailors recommendations to individual user history and inferred intent, such as being budget-minded versus quality-focused. This means there is no single, universal ranking; visibility depends on aligning with specific user profiles, not a monolithic algorithm.