Paste a video link to check that one video's views, or a creator name to check the whole account. The free check compares the views with likes, comments, shares, saves and the creator's other videos in seconds; a deep audit then goes further.
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Paste a video link to check that one video's views, or a creator name to check the whole account. The free check compares the views with likes, comments, shares, saves and the creator's other videos in seconds; a deep audit then goes further.
One number tells you nothing on TikTok. A view is counted the moment the video starts playing, with no minimum watch time, so the count says how often the video was served, not how many people watched it. What tells you something is the relationship between that number and everything else the account does.
A creator whose videos usually get 20,000 views and one who usually gets 2 million are both ordinary. The question is never how big the number is, it is whether this video's number belongs to this account. Three times their typical views with barely more likes is the pattern worth asking about.
Bought views arrive without people attached. The like rate on the video · likes divided by views · collapses while the view count runs ahead. A video that genuinely travelled brings likes with it: ten times the views with half the usual like rate is still five times the likes.
Views can be bought for a few dollars per thousand. Comments cost far more and are far harder to fake convincingly, so a large view count with almost nothing under it is one of the plainest signals there is.
TikTok shows shares and saves on every video. People who like something pass it on or keep it now and then; a bought package of views and likes does not. Hundreds of likes with not one share or save is worth a question, though a joke is saved far less than a recipe, so it is never proof on its own.
A snapshot cannot show how the views arrived. Real viewing is fast at first and then slows, rising and falling through the day. A drip feed delivers the same number every hour, and a dump lands in one block · both look identical to a big number until you have two readings.
TikTok counts a view as soon as the video begins to play, with no minimum watch time. In TikTok's own definition, each time the video is shown counts once: a loop that keeps playing adds no view, but swiping away and coming back does. The For You feed autoplays, so a view on TikTok means something closer to "this was served to someone" than "someone chose to watch this".
The practical consequence for anyone checking an account is that TikTok view counts are not comparable with YouTube's or Instagram's, and a big number on its own proves nothing at all. Every useful reading on TikTok is a ratio: views against the creator's own median, likes against views, comments against views.
It also means a real video can look extreme. A creator whose videos usually reach 20,000 people can wake up to 2 million because the feed picked it up, and nothing about that is bought. That is why this check asks whether the engagement came with the views, rather than treating a spike as an accusation.
TikTok's community guidelines ban trading services that artificially boost engagement or trick the recommendation system, and automation tools built to get around its systems. When TikTok detects inauthentic metrics it removes fake likes, followers and other inflated signals, and it can restrict or ban the accounts involved. That is why a bought count often climbs and then falls back.
Both creators have about 200,000 followers and usually get 150,000 views a video with a 12% like rate. Each posted one video that did far better than usual.
Video B is not proof of anything on its own: a paid promotion produces exactly the same shape, and so does a video that got pushed to an audience with no interest in the creator. That is why the result says what was measured and asks whether the video was promoted, rather than calling it fraud.
What settles it is the account behind the video. If its followers are real, its other videos hold their like rate and its comments read like people, one strange video is one strange video. If they do not, the video was the smallest part of the problem.
| Video A | Video B | |
|---|---|---|
| Views | 1,500,000 | 1,500,000 |
| The creator's typical video | 150,000 | 150,000 |
| Likes | 96,000 | 20,400 |
| Like rate | 6.4%, about half their usual | 1.4%, a ninth of their usual |
| Comments | 3,200 | 41 |
| Reading | 10 times the views and 5 times the likes: it travelled | 10 times the views and 1.1 times the likes: the views arrived without people |
A video that reaches a wider crowd is liked by a smaller share of it · that is normal, and it is why the check asks whether the likes grew at all, not whether the rate stayed identical.
The free check reads one video and the creator's recent videos. Two paid audits go further: the Video Deep Audit for one video, and the AI Deep Check, which reads the account:
The Video Deep Audit opens with a direct answer to whether the video shows signs of fake views. It compares the video with the creator's recent videos at a similar age and weighs its likes, shares and saves against its views. Its PDF records the public numbers with the time they were read: supporting evidence in a payment dispute, never proof of who bought the views.
Every comment is read: whether the same accounts appear again and again, whether the text is generic, whether they arrived in batches within minutes of posting.
A sample of recent followers, by the counts on their own accounts · following thousands with no posts of their own is what a bought follower looks like.
Followers and views over time, so a purchase that landed in one night is visible as a step rather than a curve.
What a post is worth on the engagement that is actually real, with the promoted videos left out of the calculation.
| Signal | What counts as normal | What gets flagged |
|---|---|---|
| Views against the creator's own median | A video within a few times the creator's typical view count, in either direction | Many times the typical views while the likes barely move |
| Like rate on the video | Close to what that same account gets on its other videos | A quarter of the account's own rate or less, on one video |
| Comments against views | Comments arrive in proportion to views, as they do elsewhere on the account | A large view count with almost no comments under it |
| Shares and saves against likes | A few shares and saves for every hundred likes | 500 likes or more and not one share or save, or fewer than 1 per 500 likes (videos past 10,000 views) |
| How the views arrive (second check) | Fast at first, then slower, rising and falling through the day | The same number every hour, or one block landing at once |
| Likes while views climb (second check) | Likes climb with the views, at the account's usual rate | Views climb, likes do not move at all |
The free check reads the video, its shares and saves, and the creator's recent videos. The paid audits go further: the Video Deep Audit for one video, the AI Deep Check for the account behind it (who comments, whether the followers are real, how the numbers moved over time).
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Compare it with the creator's other videos. Bought views arrive without the likes, comments and shares real viewers leave, so the like rate on that one video collapses while the view count runs ahead. A video with many times the usual views and barely more likes is the pattern; a video that travelled organically brings its likes with it.
TikTok counts a view when a video starts to play, with no minimum watch time. In TikTok's own definition, each time the video is shown counts once: a loop while it keeps playing adds no view, but swiping away and coming back does. A view means the video was served and started, which is why the like rate, not the raw number, tells you anything.
Yes, when it detects them. TikTok's community guidelines ban trading services that artificially boost engagement, and TikTok says that when it detects inauthentic metrics it removes fake likes, followers and other inflated signals. A count that climbs and then drops back is often that correction, not a glitch.
They are sold openly, usually in blocks or as a drip feed of a fixed number per hour. Both look like one big number in a single check. Check the same video twice and the shape shows: real viewing rises and falls, a delivery does not.
Yes. Paste the link to the video. Nothing is installed, no TikTok account is connected, and the first check needs no signup. What is read is what TikTok shows publicly on that video and on the creator's recent videos.
Sometimes it travelled: TikTok counts a view the moment a video starts to play, so a video pushed hard on the For You feed collects views from people who scrolled past in a second. Sometimes the views were bought. The difference shows in the creator's OTHER videos: if their normal like rate is 8% and this one is 0.3%, the audience that watched it did not behave like their audience.
Often. TikTok's community guidelines ban trading services that artificially boost engagement, and TikTok says it removes fake likes, followers and other inflated signals when it detects inauthentic metrics. That is why a count sometimes climbs and then falls back · the correction is not a bug.
It can happen. TikTok's guidelines say deceptive account behaviour can get an account banned, along with new accounts made to get around the ban, or restricted: limited posting, and kept out of top search results and the For You feed. Automation tools and scripts can lead to content removal or bans. Even without a ban, TikTok removes the inflated numbers it detects.
They help, and TikTok shows both on every video. Views and likes can be bought as a package; shares and saves come from people who wanted to pass a video on or keep it. On a video past 10,000 views, 500 likes or more with not one share or save is flagged. A joke is saved far less than a recipe, so this is one signal among several, never proof on its own.
Not while it loops. In TikTok's own definition a view is counted when a video starts to play, once each time it is shown: a loop that keeps playing adds watch time, not views, but swiping away and coming back counts again. TikTok publishes no other rule for the public count, so read a view as "the video started", not "someone watched it".
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