YouTube engagement rate calculator
Enter any channel handle. See subscribers, average views, likes and comments, engagement against channels of the same size, and whether the subscribers are watching. Free, no sign-up.
What a subscriber count does not tell you
Subscribers accumulate. A channel that was big in 2019 keeps the number long after the audience has moved on, and a channel on its way up looks small. Views on recent uploads are the number that says what the channel is now, and the report puts them next to the subscriber count rather than behind it.
- Engagement rate from the last dozen uploads, against the YouTube range for that size.
- Average views, likes and comments per video.
- Views against subscribers, which on YouTube is the number that matters.
- Audience quality, a risk score with every reason listed.
- The recent uploads, so you can see the spread and not only the average.
A word on comments
Comments carry more weight on YouTube than anywhere else. A video is long, and a comment means somebody watched enough of it to have something to say. A channel with healthy views and almost no comments is not necessarily fake, but it is worth knowing before you brief it.
What a good YouTube engagement rate looks like
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.
| Tier | subscribers | Low | Typical | High |
|---|---|---|---|---|
| Nano | under 10K | under 2% | around 4% | over 8% |
| Micro | 10K to 100K | under 1.2% | around 2.5% | over 5% |
| Mid | 100K to 1M | under 0.7% | around 1.5% | over 3% |
| Macro | over 1M | under 0.3% | around 0.8% | over 2% |
Rate is average likes and comments per recent post, as a percentage of subscribers. 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.
How the audience score works
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.
Beyond one channel
Wiro keeps a creator database for each agency across Instagram, TikTok and YouTube, refreshes the numbers in batches, and carries them through to campaign deliverables and the report a client reads. This page is one channel; the product is the whole roster.
Common questions
How is YouTube engagement rate calculated?
Average likes plus comments per recent video, divided by subscribers, as a percentage. Views are shown separately and used in the audience score, because on YouTube a view is a real commitment of minutes and says more about the audience than a like does.
What is a good engagement rate on YouTube?
Lower than Instagram or TikTok at every size, and that is normal. Under 10K subscribers, 4% is typical. At 100K, around 1.5%. Past a million, under 1% is ordinary. A YouTube channel judged by a TikTok benchmark will always look dead, which is why each platform on this site has its own table.
What do I enter?
The channel's handle, with or without the @, or the channel URL. Channel IDs, the long strings starting with UC, are not supported; every channel has a handle now and it is in the URL bar on the channel page.
Does it check for fake subscribers?
It scores the risk from public signals. On YouTube the decisive one is views against subscribers: a channel whose videos are watched by under 2% of its subscribers has subscribers who are not there. The score comes with its reasons, not as a percentage, and the method is explained below.
Are Shorts included?
No. The report reads the channel's regular uploads. Shorts have a different audience and different numbers, and mixing them in would make the rate mean less, not more.
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