Excited to launch our FREE Chrome extension that uses Chrome's built in gemini model to do semantic semantic analysis of websites. Extract keywords, score content, find the most relevant "chunk" and more! https://t.co/g7hEYAY2sb
In the last 6 months at @Ahrefs, we analyzed over 1 billion data points across 14 studies. Here's what we learned about AI search optimization:
1) "Best X" blog listicles are the single most prominent content format cited by AI chatbots. They make up 43.8% of all page types cited by ChatGPT specifically.
2) 67% of ChatGPT's top 1,000 citations come from sources marketers can't influence: Wikipedia (29.7%), homepages (23.8%), app stores (6.6%). Only 32.3% are influenceable content like educational pages, reviews, news, and blog posts.
3) 28.3% of ChatGPT's most-cited pages have zero Google organic visibility. These pages get cited repeatedly by ChatGPT despite not ranking in Google at all. A completely separate discovery layer.
4) ChatGPT only cites about 50% of the URLs it retrieves. It fetches dozens of pages per query but uses half as background context without attribution. This means that being retrieved and being cited are very different things.
5) Adding schema markup had zero meaningful impact on AI citations. AI Overviews actually dipped −4.6%, while AI Mode (+2.4%) and ChatGPT (+2.2%) showed changes indistinguishable from zero.
6) YouTube mentions have the highest correlation (0.737) with AI brand visibility out of all the factors we studied (including all the conventional SEO metrics like backlinks, page count, DR, etc). This held true for both Google-owned and OpenAI products.
7) AI Overviews reduce clicks to the #1 result by 58%. That’s up from 34.5% just 10 months earlier. The trend is accelerating.
8) 99.9% of AI Overviews appear on informational intent queries. Transactional, navigational, and local searches are almost entirely AIO-free. Shopping triggers AIOs just 3.2% of the time.
9) For a given search query, Google’s AI Mode and AI Overviews reach the same conclusions 86% of the time — but cite almost entirely different sources (only 13.7% citation overlap).
10) AI Overviews change every 2.15 days on average, with 70% of content differing between consecutive observations. But semantic similarity stays at 0.95. The words, sources, and entities constantly shuffle, but the actual meaning barely moves.
Just did a presentation about GEO for the C-level of a fortune 50 company. 40 people live in the room, but 100+ on the webex. Nobody told me that where I stood next to the screen in the room was right in front of the camera so those on webex saw an hour straight of just my ass instead of the other attendees.
The AI ponzi scheme goes like this:
Everyone is generating all these long ass docs and then passing them off for others to read
Then the person receiving is like, wtf this is way too long, and hands that into an AI to read and summarize
Then they are generating a long ass response back
and this cycle goes like that forever. and we call this work now 😅
The token lords watch this from their towers nodding and grinning.
@IdleMusings101@PadraigOraghail@DavidGQuaid@rustybrick It’s only confusing if you think of them both as ranking signals. If you have content that’s written by an expert it’s going to be better than content written by a non-expert. You just gotta forget about the ranking signals.
lots of SEOs critizicing others because they don't rank for SEO agency style terms. Here's a secret:
Once you get past the small clients, big clients don't search for SEO agencies. They have procurement teams and issue RFPs. They find agencies through word of mouth, press mentions, conferences & events, and recommendations from trusted advisors.
The truly successful SEOs don't need to rank for SEO terms.