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Instagram profile data extractor

Takes a list of Instagram usernames or profile links and returns one row per account with the follower count, following count, post count, bio, external link, verification and account type. Switch on recent posts and every row also carries a real engagement rate.

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About this workflow

Version 1 · Updated Aug 10, 2026 · Published by Incredible

What this workflow does

Checking one Instagram profile takes ten seconds. Checking six hundred takes a week, and by the time you reach the end the numbers from day one are stale. This workflow takes the list instead: hand it usernames or profile links and it returns one row per account with the follower count, following count, post count, bio text, the external link in the bio, the verified badge, the account type and the profile picture link.

Switch on recent posts and each row also carries the likes and comments on that account's latest posts, which is what turns a list of follower counts into something you can make a decision from. The finished file arrives with two computed columns already in it: engagement rate, and the follower-to-following ratio. Ten seconds of sorting then does more filtering than an afternoon of clicking through profiles.

Run the same list again a month later and you get growth trajectory, which is a better signal than any single snapshot. An account that gained 40 per cent followers in a month while engagement stayed flat is telling you something specific, and it is not visible from one look.

How it works, step by step

Every run follows the same four steps in the same order. You supply the list, choose whether you want recent posts, and the workflow does the rest:

  1. 1Read the username list. Takes the usernames or profile links you supply, from a pasted list or a spreadsheet column.
  2. 2Open each profile. Visits every account in turn and reads the follower count, following count, post count, bio, bio link, verification and account type.
  3. 3Read the recent posts. When recent posts are switched on, opens the last posts on each profile and reads the like and comment counts.
  4. 4Save and check the CSV. Writes one row per profile into a CSV in Downloads, adds the engagement rate and follower ratio columns, and opens it to check the row count.

Every run follows these steps in order. If a step cannot be completed, the run stops and tells you what happened instead of guessing.

What you need to run it

A computer with Google Chrome or Microsoft Edge and the Incredible extension installed, plus a normal browser you already use for Instagram. You do not need a Facebook developer account or app review, because the workflow reads the same public profile pages any visitor sees. A Google account is needed only if you want the finished file checked in Google Sheets. There is nothing to code and no APIs to connect.

Why teams run this with Incredible

Incredible works inside Instagram the way a person would, so the same public profile fields you could read yourself come back as a table instead of a week of tabs. Runs are predictable because the workflow always follows the steps it was taught, which is what makes a monthly re-run comparable to the last one. Accounts that are private or no longer exist come back marked rather than silently dropped, so the file always lines up with the list you supplied. Incredible is GDPR compliant and none of your data is stored or used for training.

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Run it on your own computer

Incredible works in your own browser, doing the steps the way a person would. Getting there takes three steps.

1Create your account
2Download the app for Mac or Windows
3Run this workflow

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Compliance

GDPR compliant

GDPR compliant. None of your data is stored or used for training.

Frequently asked questions

How do I check hundreds of Instagram profiles at once?

By handing over the whole list instead of opening profiles one at a time. This workflow takes usernames or profile links, opens each account in turn, and returns one row per profile with follower count, following count, post count, bio, bio link, verification and account type. Runs of several thousand handles are routine; the limit is elapsed time rather than list length.

Does it return email addresses?

Only where an account has published a public contact button, which most have not. The link in the bio is generally the more reliable route to a contact path, and it is returned as its own column so you can work through those separately.

Can it see private accounts?

It returns the public shell of a private account: username, bio, follower count, following count and post count. Posts and comments stay hidden, as they should, so those rows come back partially empty and are marked private in the file.

Are Instagram follower counts exact?

Below roughly 10,000 they are exact. Above that Instagram rounds what it displays, so large accounts return Instagram's rounded figure. That is a platform display choice rather than a limit of the collection, and no tool can return a precise number Instagram does not publish.

Can I calculate engagement rate automatically?

Yes. Switch on recent posts and the run reads the likes and comments on each account's latest posts alongside the follower count, then writes the engagement rate straight into the file as its own column, worked out as average likes plus average comments divided by followers. Accounts with no readable posts are left empty rather than scored zero.

Why is follower count a weak signal for influencer vetting?

Because engagement rate falls as audience size grows, and steeply. Creators in the 1,000 to 10,000 band commonly sit at 3.5 to 6 per cent on static posts against a platform average nearer 1.2 per cent, so a 90,000-follower account at 0.4 per cent reaches fewer engaged people than a 12,000-follower account at 5 per cent, and costs several times more. Engagement rate against follower count is also the cheapest check on inflated audiences there is.

How is this different from the Instagram data extractor?

Account level rather than content level. This one takes usernames and returns profile records for vetting and list building. The Instagram data extractor takes hashtags, locations and post links and returns posts, Reels and comments for research and trend work. Vetting workflows normally run this one first, then that one on the shortlist.