Free tools · Fake follower check
Do the numbers add up?
Type what a public profile shows: followers, following, posts, and the average likes and comments of the last ten. Five checks say whether the numbers make the shape bought audiences make, and which one to look at. No sign-up. The thresholds are printed.
Worth a look.
One or two numbers sit where they usually don’t. Open ten posts and read who comments, then look at where the audience lives. Half the time it is a bad month. The other half it isn’t.
- Reactions per follower0.59%Sits with the mid-tier range (1–2.5%) for Instagram.
- Comments per hundred likes0.57Quiet for the number of likes. Not proof of anything; worth opening ten posts and reading who comments.
- Following against followers0.32Follows more accounts than a creator this size usually does. Sometimes a community account, sometimes growth tactics.
- Posts behind the following571 per postThe following grew with the work. Nothing odd here.
- Growth in the last 30 days—Optional. Type the followers gained in the last month if you know it, and this check switches on.
Reads the arithmetic, not the followers. A profile can pass here and still be full of bots, and a real account can trip a check on a bad month. The audience report is the audit; this is where you decide to ask for it.
What just happened
Bought audiences have a shape.
Nobody buys engagement to match. They buy followers, and bought followers do what bought followers do: nothing. So the first tell is reactions per follower far below what accounts that size get. The second is likes without comments, because likes are cheaper to buy than sentences. The third is the follow count: audiences grown by following back leave the following number high. And a jump of a hundred thousand in a month with no post to explain it is a receipt.
None of these convicts on its own. A creator can have a quiet month, a niche can be all lurkers, a community account follows everyone. Two or three together is when you ask for the audience report.
What this page cannot see is the followers themselves: where they live, what language they speak, how many follow thousands of accounts and engage with none. That is follower-level data, and it is what the audience view in Discovery shows for creators in Beatly’s index.
The rules, shown
Disagree with them here.
Every threshold the checks use, printed from the same file that runs them. Pass counts one, worth a look counts a half, fail counts nothing; the score is the average over the checks that could run.
| Check | Pass | Worth a look | Fail |
|---|---|---|---|
| Reactions per follower | inside or near the working range for the account size | more than 3× the top of the range | under 50% of the bottom of the range |
| Comments per hundred likes | 0.8 to 15 | under 0.8, or over 15 | under 0.3 |
| Following ÷ followers | under 0.2 (under 1 below 10,000 followers) | 0.2 to 0.5 (1 to 2 below 10,000) | 0.5 or more (2 or more below 10,000) |
| Posts behind the following | anything else | more than 15,000 followers per post | fewer than 20 posts with 50,000+ followers |
| Growth in the last 30 days | under +30% | +30% to +100% | +100% or more |
Adds up: score of 85% or more. Worth a look: 50% to 85%. Doesn’t add up: under 50%. The working ranges behind the first check are on the Rate Check.
Before you sign
Questions people ask us.
- Can this tell me whether a creator has fake followers?
- It can tell you whether the numbers make the shape bought audiences make. It cannot see the followers. A pass means the arithmetic is consistent; a fail means look closer. The audience report is the audit: where followers live, what language they speak, how many are mass-followers or inactive. Discovery shows that for creators in Beatly’s index.
- What is a mass-follower?
- An account that follows thousands of others and engages with almost none. Some are bots, some are people who followed back for a decade. Either way they inflate the follower count and never see a post. An audience with a large share of them reaches far fewer people than the number suggests.
- Why does a viral post trip the check?
- Because a viral post does the same thing to the numbers a purchase does: followers arrive in a wave, and reactions on the next posts don’t keep up. The difference is that you can find the post. If the wave has no post behind it, that is your answer.
- The creator failed a check but I know they are real.
- Then you know more than the arithmetic does, which is the point: this page sends you to look, it does not decide. Keep the creator, and write into the brief which number you will report on, because the platform will judge the post by the same arithmetic.
- Where do the thresholds come from?
- From vetting creators, and they are printed on this page so you can disagree with them. They are deliberately generous: the tool is built to send you to look, not to convict. They will move as Beatly measures them against its own creator index.
Ask for the audience before the invoice.
Every Beatly shortlist comes with the audience behind the numbers: where they live, what language they speak, how many are real. Bring the creators you are considering.
Talk to a strategist → Try the Rate Check