I was wondering if there is a way to tell if the post was boosted and for how much on Instagram when you don’t have an access to their stats? It is from the potential future client of mine and their marketing team is kind of “know it all”, but the company director is on my side although not very skilled in the art of social media
They already lost content production side to us so I suspect that they may not be as co-operative as I need them to be.
I have seen this particular post on my feed as “sponsored”, but once they used all their advert budget, the post sits on their feed with a tone of likes without a trace of being boosted before (or I don’t know how to find it).
Is there any report website or a way within the Instagram to tell that?
If not, no worries, next time I will just screenshot it
Would hypeauditor help here as it analyses likes and comments? I found it useful for analysing influencer and competitor accounts
I used that on their account but from what I can see it gives me only a general stats about all the likes etc, but I’m using a free version.
Can you analyse a single post with hype auditor?
Is it possible to just analyse manually or are the numbers big? I sometimes just scroll through the likes to find non relevant accounts, they are easy to spot as they don’t fit the niche
I know which posts has been boosted even without hype auditor as they usually get 400-600 likes and got some posts on 4000+. I also remember seeing these posts as sponsored on my private account feed.
They also almost never use hashtags. I was just wondering if I can find out somehow how much they put behind every post without asking them or if the post was sponsored in the past. (I should just take screenshots when I seen them)
If you dive into Instagram’s web JS data, you can differentiate organic likes from boosted ones.
How? I mean how do you get the JS data? You need a script or something?
Is the any “how to” guide of how to do that?
Follow this guide: https://edmundmartin.com/scraping-instagram-with-python/
Requires some Python knowledge but pretty straightforward
After you have it working check the JSON output of post you know that were boosted and others that were not.
As for the last time I used it (around 2 months), I could have extracted the organic like count.
Thank you very much! I will dive into it!
Cool thank you. Will try this out - just need to reerve some quite times to fully dive into the python rabbit hole.
A few weeks ago I read somewhere that you can just add some characters to the instagram url and by this get some additional information (like image recognition tag). Have bookmarked that somewhere but haven’t found it after my 5min search yet.
Would you be able to share it once found?
Lmk how it goes
I’m not familiar with the url manipulation, but you will get all this data in JSON format from the script in the guide.
I used to have a chrome extension that showed it all nicely in the browser, will post if i find it.
Great share, thank you! I wonder what’s possible to discover if you’re really good at coding, it, etc
I think that I managed to make it (with a help of one of my guys from dev team)
I am happy to share the zipped files plus a guide of how to use it so will make a separated tread about it just in case the other people who would be interested, but didn’t check this tread can have an access to it.
I will link the tread here once it’s done as well.
Looking forward to seeing that, thanks.
Yes, if you know how to scrape data from Instagram, you can discover a lot of stuff, doing research with it is really good. If you don’t know how to code, you can always hire someone.
@ido finally have found the chars that you just need to add to an IG url to get all post data (also image tags). It is: ?__a=1
So for instance you have this IG post: https://www.instagram.com/p/Bf3i30GjdCb/
You add the chars and it becomes: https://www.instagram.com/p/Bf3i30GjdCb/?__a=1
For this picture information you have to search a bit. Since I have a German browser profile I search for “Bild” which meand picture and then I see the text information that two persons are preparing food and are both high as f*ck