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.
Not an audio engineer, but something bugs me about video calls without headphones: when AEC struggles, the system just ducks the volume. You lose the conversation exactly when it gets most dynamic. There has to be a better fallback.
Limitations: two-party only, both endpoints need to implement it, voice sounds band-limited. Though I wonder if a neural net could reconstruct the missing bands at the receiver side, like bandwidth extension in telephony.
Si una máquina con una pantalla necesita seis carteles explicativos, es que la máquina está mal diseñada.
Cuando el manual de usuario es mayor que la inferfaz de usuario, es que tu diseño es malo. Punto.
Mala tecnología que tenemos que utilizar a diario.
Recomiendo tanto la web "Cómo hacer presentaciones" de Giles Turnbull que se me dio por traducir todos sus artículos, así la puedo seguir recomendando.
Ley Orihuela o Ley de la Unicidad Múltiple: En la administración pública, toda vez que algo se denomina ‘Único’, existen al menos cinco versiones diferentes de ello.
What happens when a team turns a failure into a dramatic success? Sometimes, their hard work and courage earn them a GAO nastygram. That's because the Government Accountability Office holds them accountable to the operating model that caused the problem in the first place. 👇
There were other scripts on GitHub to do the same thing, but what I liked about this specific one was the clarity of the Readme file, which explains step by step how to implement it, for people with no technical background.
I have multiple clients and I have a Google account with each. I want to be able to block my calendar on each account when I have an event with my other client, or if I have a personal appointment, so that my colleagues don't see that space as free.