How to measure your brand in AI search

Discovery has moved to AI. Your measurement hasn't. Buyers now research, compare and decide inside AI answers, and most companies have no way to see how their brand shows up there. This is how to fix that.

Has discovery moved to AI?

900 million people use ChatGPT every week. That is more than the combined populations of the United States, the European Union, Australia and New Zealand. Google's AI Mode has passed 1 billion monthly users. And this year, for the first time in internet history, machines generated more web traffic than people.

This is the biggest change in how people find, compare and choose that we have seen in a long time. A buyer asks an AI which option to trust, what to compare, whether you are worth it, and often decides before they ever land on your site. If your most important visitor is now an AI answer you never see, the first job is to make that path visible.

Why doesn't the old SEO playbook work in AI search?

Early on, this looked easy to game. Ask a model for the "top 10 best agencies in New Zealand" and it would happily build the list, so people rushed to write that page. The newer models already rewrite the query to route around the trick. The shortcuts are dying fast.

Anyone who has done SEO for 15 years has seen this film. Every hack works until the system gets better. These systems are rewarded for serving the best answer, so if you are gaming your way up without being that answer, the next model update wipes you out. There is a human at the end of the screen spending real money. Be the best answer. That is the only thing that keeps working.

What should I measure? Build a prompt library around the customer journey

You cannot get a "search console" for ChatGPT. Google did add generative AI performance reports to Search Console in June 2026, so you get some visibility into how you show up in its own AI answers, but that stops at Google. There is no equivalent for ChatGPT, Perplexity and the rest, and no single report spans them all. There is no report of how many people prompted for you or how you performed. Responses change by person and context, and models change often. So the foundation of measurement is a prompt library you build yourself, structured by where the buyer is in their journey rather than by keyword volume.

We build the library around the customer journey, in three stages.

The first is category entry, the moment someone first enters the market, like "things to do with a toddler in Queenstown." Broad, early, high in the funnel. The second is consideration, where they compare options: who is on the list, in what order, and why those brands keep appearing. The third is conversion, the exact questions buyers type before they commit, like "is [brand] worth it?" That tells you what AI says about you when the buyer is closest to spending. Start there and work backwards.

Run those prompts through ChatGPT and Gemini and read the answers for citation, accuracy, sentiment and share of voice. We go deeper on what those metrics mean, and which one to chase. Every person gets a slightly different response, but the responses cluster into recognisable sequences. The same brands keep recurring, because the models mimic the same strategic sources: reviews, reputation, consistent signals. That clustering is what makes the measurement reliable enough to act on.

What is entity diagnostics, and why does it come first?

An AI model builds a picture of who you are from your whole digital footprint: who you serve, what you promise, how you are different. Entity diagnostics tests that picture. Ask the models what your brand is good for, who they would compare you to, and how you differ. You find out how they read your positioning, which is often not how you think they do.

If you don't get your entity diagnosis right, all the other optimisation doesn't work, because AI doesn't know who you are. This is the crossover of PR, brand and technical work: consistent language about what you do, schema markup, and a clean organisation and Wikidata presence. Land this first, or the rest is wasted effort.

How do I connect AI visibility to revenue?

Never look at a number without context. "Share of voice: 12%" means nothing on its own. The value comes when you place AI metrics next to the rest of the picture. Filter Search Console and GA4 by your category terms, layer in bot traffic so you can see how often AI systems are reading your content, and set a benchmark.

Now the picture sharpens. Impressions may be softening while your AI citation is climbing, which tells you the journey is shifting instead of failing. You go from a blur of numbers to something you can act on: where you are cited, where you are invisible, and which stage of the journey moves revenue. That is where budget decisions should be made, not in a monthly argument over a single vanity metric.

What kind of content wins now?

Google's own guidance is blunt. It calls generic "7 tips for first home buyers" pieces commodity content: "often based on common knowledge, which could originate from anyone, and typically has little unique insight for readers." The machine already knows the basics. It does not need your version of them.

The value now sits in your brand's specific point of view and in real proof. Prompts have changed too. The average Google search is a few words. In ChatGPT people give the whole context: "I have a one-year-old and a three-year-old, I want this, not that." That rewards depth and specificity, content built for the real scenario instead of the generic category.

Proof matters more than polish. No one cares what the machine summarises. They care what other people think. So put real social content, video and first-hand experience into your strongest pages. Plan one shoot that feeds organic social, a practical guide and your AI-facing content at once. One capture, many places.

Where do I start this week?

Open ChatGPT and run the exact prompts your buyers run. "Is [your brand] worth it?" and "best [your category] in [your city]." Read how you are described, or whether you appear at all. That is your baseline, and the reason to build the rest.

When someone asks AI about your category, are you in the answer?

Most brands have never checked. They have not run the prompts, so they cannot see how AI describes them, or which competitor it recommends first. That is the gap we close.

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