TikTok engagement rate calculator

On TikTok the follower count is even less of a guide than elsewhere, because the platform serves videos to people who do not follow the account at all. A creator with 40K followers can reach millions on a good week and a few hundred on a bad one. The report is built to show which.

• Engagement rate from the last dozen videos, against the TikTok range for that size.
• Average views, likes, comments and shares per video.
• Views against followers, the single most telling ratio on this platform.
• Audience quality, a risk score with every reason listed.
• The recent videos themselves, with their numbers, so one viral hit is visible as one hit.

Why one viral video misleads

An average that includes a video with twenty times the usual views is not a typical week. The report measures how evenly reactions are spread and says so when one post is carrying the number, which matters when a client is paying for the typical post, not the lucky one.

Engagement rate falls as an account grows. That is not a failing, it is arithmetic: a million people do not all react to one post the way a thousand close followers do. So a rate only means something next to the account’s size, and this is the range the tool compares against.

Rate is average likes, comments and shares per recent post, as a percentage of followers. These are working ranges drawn from what is reported across the industry for each tier, rounded so nobody mistakes them for precision. As the checker builds up its own data, they will be replaced with measured medians and this page will say where they came from.

There are two ways to look for fake followers. The expensive one samples the follower list itself, thousands of accounts per profile, and grades each on whether it looks like a person. That is what the paid platforms do, and it is why they cost what they cost. The other is to read what a bought audience leaves behind in the public numbers, which is what this tool does. Bought followers do not react, do not comment, and do not watch, and those absences show.

The signals

• Engagement against size. The heaviest signal. An account with 200K followers whose posts get the reactions of a 5K account has followers who are not there.
• Comments against likes. Likes are cheap to buy in bulk; comments are not. Under one comment per two hundred likes, on an account big enough that the ratio means something, is a tell.
• Following against followers. An account that follows more people than follow it, past a few thousand, usually grew by following everyone back rather than by being worth following.
• Audience against output. Fifty thousand followers on twenty posts happens, but rarely.
• Consistency. Real audiences are uneven. A run of posts that all land within a few percent of each other looks purchased; one post carrying the whole average means the typical post does far worse than the number suggests.
• Views against followers. On video platforms, followers who never watch are the clearest sign of all.

What the score is, and is not

Each signal adds to a score out of 100, and every point is shown with its reason, so you can disagree with any of them. A quiet week on a small account trips the first signal honestly, which is why one signal on its own never gets past “a few signals” and the score only says high risk when several agree. It is a risk indicator built from public behaviour, not a count of fake accounts, and the page never quotes a percentage it cannot stand behind.

Checking one creator is a minute. Shortlisting thirty, tracking their deliverables and putting the results in front of a client is the job. Wiro is built for that job, with a creator database refreshed in batches, campaign deliverables and client reporting in one place, and this checker is the front door to it.