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.
@jwuphysics Great point on summarization being a form of outsourcing one’s thinking.. looking back, ideas do tend to stick longer by reading rather than AI summaries
F.lux was sherlocked almost a decade ago when Apple introduced Night Shift for MacOS. Today however, I found myself installing it. Night shift seemed buggy on my external display, while F.lux worked flawlessly @JustGetFlux
@sidi_jeddou_dev Zoho’s docs leave something to be desired tho, at least for Zoho Desk. There are times where we stumbled towards questions with no answers found in the docs. As well as undocumented quirky behaviors that left us no choice but to contact CS and wait.
@rauchg@emilkowalski@reactjs Didn't know it supports snap points last time I checked! Was looking for this specific feature for my map directory, just like how gmaps does it. The current way seems a bit janky. Will definitely check this out.
honestly, the most helpful feature in @cursor_ai is getting to apply code suggestion automatically, without having to manually copy and paste snippets around commented out code from ChatGPT/Claude
@ibamarief@Wahjoeni rasanya ini juga terjadi dalam skala global, contohnya "corporate memphis" yang trending dulu. Pas developing https://t.co/QKFtq0nPEU, saya mulai specifically dari sudut pandang functionality (sorry self plug), not the best UI/UX but at least not boring imo 😁
Supabase's image transformation is only available on their pro> plan, and even then gives few monthly invocations
This led me to pre-transform images and upload to my bucket. This way, visitors get optimized images without hitting API limits!
#buildingpublic#supabase