This is where AI search gets interesting for marketing teams.
Most teams are still trying to measure it the way they did in old SEO. Clicks, referral traffic, fixed rankings. The problem is that AI answers do not behave like search result pages. A buyer may see your brand in an AI answer, never click the source, and still search for you later or bring your name into a sales conversation.
So traffic alone will underreport influence.
The better question is what is changing around the brand.
Are branded searches going up?
Are AI systems describing the brand correctly?
Which third-party sources are shaping the answer?
Are competitors being mentioned more often?
Is the brand showing up for the right category prompts?
This is the angle I find most relevant for FTA Global. A lot of our work sits at the intersection of visibility and business outcome. It is not enough to say a brand appeared in ChatGPT or Perplexity. We need to understand whether that visibility is improving recall, credibility, qualified demand, and sales conversations.
AI visibility measurement will not be clean for a while, but it can still be useful if we stop treating traffic as the only proof.
The branded search cycle is the piece most small operators miss entirely. I work with independent hotels and destination marketers who are still measuring success by direct traffic from AI platforms. Meanwhile their property name is showing up unlinked in ChatGPT answers and they have no idea it's happening. The real signal is whether more people Google you after the AI conversation, not whether the AI sent a click. That reframe alone would change how most of my audience thinks about visibility.
The branded search cycle point is spot on. We ran audits across 150 B2B SaaS brands recently and found that 67% are completely invisible to at least one major LLM. The scary part: most of them had no idea because they were still measuring success with traditional SEO metrics.
The metrics gap is real. You can't just transplant keyword rankings and organic traffic into the AI visibility world. Citation rate, share of voice across models, sentiment accuracy -- these are fundamentally different signals that require different tooling.
Curious what you think about model-specific strategies. We're seeing brands that rank well in ChatGPT but get completely ignored by Claude or Gemini. Each model has different training data and retrieval preferences.
This is where AI search gets interesting for marketing teams.
Most teams are still trying to measure it the way they did in old SEO. Clicks, referral traffic, fixed rankings. The problem is that AI answers do not behave like search result pages. A buyer may see your brand in an AI answer, never click the source, and still search for you later or bring your name into a sales conversation.
So traffic alone will underreport influence.
The better question is what is changing around the brand.
Are branded searches going up?
Are AI systems describing the brand correctly?
Which third-party sources are shaping the answer?
Are competitors being mentioned more often?
Is the brand showing up for the right category prompts?
This is the angle I find most relevant for FTA Global. A lot of our work sits at the intersection of visibility and business outcome. It is not enough to say a brand appeared in ChatGPT or Perplexity. We need to understand whether that visibility is improving recall, credibility, qualified demand, and sales conversations.
AI visibility measurement will not be clean for a while, but it can still be useful if we stop treating traffic as the only proof.
The branded search cycle is the piece most small operators miss entirely. I work with independent hotels and destination marketers who are still measuring success by direct traffic from AI platforms. Meanwhile their property name is showing up unlinked in ChatGPT answers and they have no idea it's happening. The real signal is whether more people Google you after the AI conversation, not whether the AI sent a click. That reframe alone would change how most of my audience thinks about visibility.
Yes! At least until LLMs learn to link brand mentions! (or let people perform actions without ever leaving)
The branded search cycle point is spot on. We ran audits across 150 B2B SaaS brands recently and found that 67% are completely invisible to at least one major LLM. The scary part: most of them had no idea because they were still measuring success with traditional SEO metrics.
The metrics gap is real. You can't just transplant keyword rankings and organic traffic into the AI visibility world. Citation rate, share of voice across models, sentiment accuracy -- these are fundamentally different signals that require different tooling.
Curious what you think about model-specific strategies. We're seeing brands that rank well in ChatGPT but get completely ignored by Claude or Gemini. Each model has different training data and retrieval preferences.