YouTube Fake Subscriber Check

How the YouTube estimate works

Enter a @handle: we fetch the channel and recent uploads, then score views-per-subscriber (median views over subscriber count) and view dispersion. YouTube no longer exposes public like or comment counts, so those signals are marked unavailable instead of guessed.

How to read the result

The primary signal is median views per subscriber: a bought-subscriber channel shows a rising subscriber count with flat views. The verdict is capped at “medium” because fewer signals are measurable — that honesty is deliberate.

FAQ

Why is there no likes-to-views signal for YouTube?

YouTube no longer returns public like or comment counts through either data source we use, so those signals are structurally unavailable. The estimate relies on views-per-subscriber and view dispersion, and the page says exactly that.

How do I read views-per-subscriber?

Median recent views divided by subscriber count. Healthy channels commonly sit between a few percent and tens of percent; a channel whose subscribers keep climbing while median views stay near zero is the classic bought-subscriber shape.

Where does the data come from?

Public platform data and third-party public profile databases. We don't scrape behind logins or buy private lists.

Is this an audit?

No. It's a heuristic estimate from public metrics to help you decide whether to reach out — not a verdict on a creator.

Does it cost anything?

Some tools work without signing up. Data lookups use a small number of credits per successful query; failures are refunded automatically.

Can I export the results?

Yes. Unlocked results export to CSV, and in the workspace you can process them in batches.