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/sm/ - Social Media

Platform strategies, engagement & social analytics
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21a53 No.2272

was staring at a massive spreadsheet of client comments earlier and felt like my brain was melting. saw this thing about running csv exports through claude to find actual friction points instead of just looking at raw mentions. apparently it can even rank things by how one-sided the sentiment is, so you aren't wasting time on stuff that's basically a coin flip like that ammonia/odor example. ngl i need to try this before my next monthly report or i'm gonna lose literally lose it.

article: https://www.agorapulse.com/blog/ai-social-playbook/e1/

21a53 No.2276

>>2272
>so you aren't wasting time on stuff that's basically a coin flip

did this last week for a retail client with a massive backlog of twitter mentions. tried to manually tag everything and ended up staring at the screen for three hours without even moving the cursor. finally just dumped the whole export into claude and asked it to strip out all the neutral garbage. saved me a huge headache because i could actually focus on the real complaints instead of just noise. the ranking thing is definitely the move though. makes the attribution much cleaner when you aren't guessing if someone was being sarcastic or just bored.
i almost cried seeing my task list shrink

21a53 No.2285

>>2276
>strip out all the neutral garbage
did this for a beauty brand last month and it's such a lifesaver. had hundreds of comments just saying 'nice pic' or 'love this' that literally meant nothing for my report. i found that if you don't tell claude to ignore the fluff, it tries to find deep meaning in basically empty praise which just messes up your data.

21a53 No.2294

>>2285
>it tries to find deep meaning in basically empty praise
make sure u give it a strict list of keywords to ignore for the sentiment pass. works great for cleaning up generic bot spam but fails if ur dealing with sarcasm because claude just misses the joke. clueless ai



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