Scrape Reddit for Competitor Market Analysis

okay so i guess just for some context um what i find doing some of the user research work is there's a lot of cool conversations happening out in the wilds on reddit twitter slack communities uh and also with uh talking with stefan there's like a lot of interesting background you can get from just seeing like you know what are the conversations happening just out there in the world related to m810 to competitors uh to you know the general space of workflows and automation so our solution was quite simple we kind of scoped it down a little bit just to have like a v1 0. 1 that we can ship today so we have a list of 23 competitors here that we've just added uh these then feed into a workflow here where we're just checking reddit uh to see what people are saying about those competitors uh filtering for the recent posts and then adding them back into the air table right over here so we've got about 35 uh responses annoyingly a lot of them are just uh just bots these are from the past seven days and what we're taking from reddit is obviously who's posted what's the title uh what's the text of the post mostly for searching uh and a few things like you know when was it made where's where is it located uh et cetera um and then going on so i guess the interesting insights one is just seeing okay what are the kind of issues people are having with nodes on other competitors uh this view uh gives us that and two is just you know actually going back to this so here we're just filtering based on uh any title or text of the post containing node integration api connector or module um and that actually then feeds in to a just to show some of the cool stuff that editable does so we have a weekly digest email that goes out just you know recording the kind of mentions of competitor nodes in the past week um and a similar thing happens with any mentions of partner and embed there as well so we have this potential uh partner we found maybe relevant may not be uh i guess one of the things we the challenges we had was there was a lot of data out there and we decided to kind of be a bit more aggressive on the filtering rather than having to uh the automated manually sift through like thousands of potential hits um and yeah that's the main thing any questions