How to compare AI mentions with Google search performance using Search Console

You compare them by measuring each side separately for the same topics and the same dates, then matching the results on two things they share: the topic a searcher is asking about and the page on your site that answers it. Search Console gives you one side. Its Search results report shows the queries people used to find you in Google, the pages that came up, and the clicks, impressions, click-through rate, and average position behind each one. AI mentions are the other side, and most of them happen outside Google entirely.

Search Console now sees part of the AI picture, which is where people get confused. Google counts your appearances in AI Overviews and AI Mode inside the regular web totals of the Search results report, without a filter that separates them. Since June 2026, Search Console has also had a Generative AI report, found under Performance, which counts the impressions your links earn inside AI Overviews and AI Mode. It breaks those impressions down by page, country, device, and date. It doesn't show which queries triggered them, and it doesn't count clicks.

None of that tells you whether ChatGPT, Gemini, Perplexity, or Claude recommend you. To learn that, you have to ask those engines the questions your buyers ask and record whether your brand appears, which competitors appear instead, and which pages the answers cite. Then you line those results up against Search Console.

The lining up is where the job succeeds or fails. Comparing your total Google clicks with a single share-of-voice figure tells you almost nothing, because the two numbers describe different searches. A good comparison works topic by topic. For each question your buyers ask an AI engine, it finds the Search Console queries that mean the same thing and the page that earns them, then answers a plain question: are you winning here in Google, in AI answers, in both, or in neither? Repeated over the same dates, it also shows whether the two are moving together.

Kite does this comparison for you. It reads your Search Console performance, takes its own reading of the AI answers, matches the two by topic and page, and tells you what each gap means and what to change.

Start by asking Kite in Slack to compare the two:

"Compare our AI answer mentions with our Search Console performance over the last three months, and tell me where they don't line up."

Kite is an AI marketer in your Slack. It researches your business, builds a growth strategy, and ships the work that brings you new customers. From that research, it already knows your category, your products, your competitors, and the problems your buyers search for, so it can propose the topics and questions worth measuring without a long brief. If your team already tracks a set of AI-answer questions, Kite uses those exactly as written. Confirm the topics or adjust them, and Kite starts.

You'll need to connect the Google account that has access to your Search Console property, through OAuth. Kite works only on the properties that account can see, at the permission level Google grants it. The AI-answer measurement is built into Kite, so you don't need a separate AI-visibility tool or account for that half of the job.

Kite starts by settling exactly what it is comparing. It lists the verified properties on your connected Google account and reads each one's details, including your permission level, so it works in the property that holds your real traffic. A domain property covers every subdomain and protocol, while a URL-prefix property covers only the address it names, and picking the wrong one quietly leaves pages out.

Next, Kite settles the topics. These are the subjects your buyers ask about, written the way a buyer would type them, such as a problem you solve or the category you sell in. Kite keeps your brand name out of the questions on purpose. A question that already names you will almost always get an answer that mentions you, which measures nothing.

Kite queries your Search Console performance and breaks it down by query and by page, with the date added so it can see the trend. For each row, it reads clicks, impressions, click-through rate, and average position, and it can split the results by country and device when your markets differ. It compares the period you asked about with the one before it, and with the same period a year earlier when seasonality matters. Search Console keeps about sixteen months of data, which gives that comparison room.

Kite also accounts for how Search Console counts AI features. Every link inside an AI Overview takes the position of the Overview itself, so a page cited in an Overview at the top of the results can show an average position near one without ranking there as a regular result. Kite reads average position as a trend to move, not an exact rank. It also leaves out the most recent two or three days, which Google hasn't finished processing.

If you'd like Google's own AI count in the comparison, export the Generative AI report from Search Console and share the file in the Slack thread. Kite reads it and adds those page-level AI impressions next to the Search results data.

Kite runs your buyers' questions through ChatGPT, Gemini, Perplexity, and Claude and records what each engine says. For every answer, it notes whether your brand appears, which competitors appear, and which pages and domains the answer cites. Across all the questions, it measures your rank among the brands that came up and your share of voice against them.

Kite adds search context from its own built-in sources. For the keywords you rank for, it reads your Google rank, the monthly search volume, and whether Google shows an AI Overview for that search. Kite keeps the same questions from one reading to the next, so a change in the numbers reflects a change in the answers rather than a change in what was asked.

Kite matches the two measurements by topic first and by page second. It groups your Search Console queries under the topics it measured, so the queries that mean the same thing as an AI question sit beside that question's answers. Then it checks the pages the AI answers cite against the pages that earn your clicks in Google.

With both sides in place, Kite sorts each topic into one of four groups:

• Strong in both. You earn clicks in Google and the AI engines mention you. Kite records which pages carry the topic so you know what to protect.
• Strong in Google, missing from AI answers. You rank and earn clicks, but the engines recommend competitors. Kite reads the pages the answers cite instead, which are often roundups, comparison pages, documentation, and community threads you don't appear in, and checks whether your ranking page states a clear answer to the question.
• Mentioned in AI answers, weak in Google. The engines name you, often because of what other sites say about you, but your own page doesn't rank. Kite looks at that page's impressions and position to see whether it needs a rewrite or doesn't yet exist.
• Weak in both. Kite weighs these by how much demand the topic has before it recommends spending effort there.

Kite compares the trend on each side over the same dates, because the most useful findings come from the two moving apart. When impressions on a topic hold steady while clicks fall, and Google shows an AI Overview for those searches, the Overview is likely answering the question on the results page. That's a different problem from losing your ranking, and it calls for a different fix. When your share of voice in AI answers rises while Google clicks stay flat, the engines are picking up something Google isn't rewarding yet.

Kite's AI-answer history starts with its first reading, while Search Console reaches back about sixteen months. So the first comparison sets the baseline for AI answers, and each later reading adds a point to the trend.

When the comparison is done, Kite posts a summary in the Slack thread where you asked. It gives your share of voice and rank in AI answers, your Search Console clicks and impressions for the same period and how they changed, and the topics in each of the four groups with the pages behind them. For each gap, it explains the likely cause and recommends a fix, such as a clearer answer on a ranking page, a new comparison page, better structured data, or a pitch to a site the engines already cite.

If the comparison needs more room than a Slack message, Kite publishes it as a report with charts and tables at a shared link. Kite can make the recommended website changes on a site it hosts or through a supported CMS connection, and afterward it runs the same questions again and rereads Search Console once Google has caught up. If you want the comparison regularly, ask Kite to run it every month, and each run posts in the same thread.

When Kite finishes, you have a comparison that shows, topic by topic, where Google and the AI engines agree about your brand and where they don't.