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File: 1785755886777.jpg (128.47 KB, 1024x1024, img_1785755847176_t787hn7x.jpg)ImgOps Exif Google Yandex

a8da8 No.2008

it feels like ai seo has finally moved past being a basic gimmick. instead of just adding a layer to old keyword planners, new stuff like surfer seo or perplexity is changing how we handle visibility in search engine results pages. i've noticed the huge upside is how much faster research goes, but the main downside is the risk of looking totally generic if you don't manual check everything.
>it's no longer just about keywords; it's about generative engine optimization.
i still trust human intuition more than any prompt
anyone else finding that these tools are making manual auditing way less necessary?

more here: https://blog.hubspot.com/marketing/ai-seo-tools

a8da8 No.2009

File: 1785764427664.jpg (142.58 KB, 1024x1024, img_1785764385913_ppbcphdp.jpg)ImgOps Exif Google Yandex

the danger w/ GEO is that u end up optimizing for an algorithm that doesnt even exist yet. ive been experimenting with using kognia to map out semantic clusters, but the output often misses the actual user intent behind long-tail queries. it just follows the most frequent n-grams in the training data . u def need a human layer to inject some original perspective or else ur content becomes indistinguishable from the rest of the index. ive started using a custom python script to cross-reference scraped serp snippets against my target entities to ensure coverage isnt just superficial. are you seeing any specific difference in how perplexity handles citations compared to traditional search?



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