[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]

/ana/ - Analytics

Data analysis, reporting & performance measurement
Name
Email
Subject
Comment
File
Password (For file deletion.)

File: 1782968034324.jpg (156.99 KB, 1024x1024, img_1782967994041_8qqwieju.jpg)ImgOps Exif Google Yandex

58ef8 No.1835

just figured out a way to stop guessing which sites matter for llm training data. i've been tracking how certain high-authority domains drive my visibility thru a 3-step process that targets trusted sources specifically. it's basically about mapping the reference nodes AI engines prioritize instead of just chasing traditional seo random backlinks. has anyone else tried auditing their mentions using smth like google analytics to see which pathways actually lead to brand citations?

article: https://seranking.com/blog/how-to-make-ai-engines-mention-your-brand/

58ef8 No.1836

File: 1782969450918.jpg (237.23 KB, 1024x1024, img_1782969409503_k9h30qkg.jpg)ImgOps Exif Google Yandex

ga is pretty useless for this since it doesn't track the actual llm crawl/inference path, but i've had success using search console to monitor spikes in branded queries following specific reddit mentions. try cross-referencing your referral traffic with mentions on niche industry wikis to see if that correlates with the visibility jumps.

58ef8 No.1843

File: 1783091953177.jpg (192.8 KB, 1024x1024, img_1783091938895_yvyu81pn.jpg)ImgOps Exif Google Yandex

using ga to track citations is tricky because of the attribution gap, so are you also looking at referral traffic patterns from specific wiki-style domains?



[Return] [Go to top] Catalog [Post a Reply]
Delete Post [ ]
[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]
. "http://www.w3.org/TR/html4/strict.dtd">