YouTube Channel Analyzer — Reach, Audience Language & Sponsorship Fit

Give it a list of YouTube channels. Get back what you actually need before you offer anyone a sponsorship.

Subscriber counts do not tell you what a video will get, and they do not tell you who watches. This Actor reads a channel's recent uploads, a sample of its real comments, and its recent video descriptions, and returns the numbers a brand needs — each one with the evidence behind it.

What you get, per channel

Field	What it means
Expected views	The median of recent uploads — not the average, and not subscribers
Days since last upload	So a big number from a dormant channel cannot mislead you
Audience language	Inferred from a sample of real comments, with the sample size and confidence
Takes sponsorships	Whether recent videos carry brand deals — and separately, affiliate links, memberships and their own products
Sponsors named	Who has sponsored them recently, where the description says so
Competitors seen	Any brand you named, with the sentence it appeared in — read across the last ten videos, not just the last three
Estimated price range	Expected views × your CPM. Arithmetic on measured data
Upload cadence and engagement	How often they post, and their like rate

Why the median, not the average

One viral upload drags a channel's average 20–75% above what a normal video gets. We measured it: @RaidOwl averages 28,933 views and the median is 16,500. Price a sponsorship off the average and you overpay by that much.

Why comments, not titles

YouTube translates video titles into whichever language you ask for. Request English and a Mexican Spanish-language creator's titles come back in English — the titles describe your request, not their audience. Comments are not translated, so that is what we read.

Two windows, on purpose

Audience language comes from comments, and three videos is plenty — the language a sample points to is stable from about ten comments, so sampling stops as soon as it has enough.

Sponsor history and competitor mentions come from descriptions, and that window is wider by default, because "has this creator promoted my competitor recently" is not a question three videos can answer. On one real channel, reading three descriptions found no competitors and reading twelve found three of them.

Both are adjustable. Raising the description window makes runs slower, since each extra video is one more page fetched.

What it will not do

• It will not tell you who to pick. It returns facts and one piece of arithmetic. The weighting, the shortlist and the budget are yours — you know your market and we do not.
• It will not guess a CPM. Rates vary enormously by niche. Supply your own, or leave them blank and get every other field.
• It will not claim a language it cannot support. When a comment sample is too small or too mixed, the language is left blank with the reason stated, and the full distribution is still there for you to read. Audiences that write their own language in Latin script — romanized Hindi, for example — reliably defeat language detection, and we would rather say nothing than say "English".
• It does not read transcripts. A sponsor mentioned aloud and never linked in the description is invisible to it.
• It does not report audience age or gender. Those exist only in a creator's own YouTube Analytics or in paid panel data. Anyone selling them from the outside is modelling, not measuring.

Input

Paste channel handles (@name), full channel URLs, or channel IDs (UC...). Repeats in your list are charged once. Optionally add your CPM range and the competitors you want flagged.

Leave the input empty and it runs a small sample so you can see the output shape.

Output

Two dataset views: Shortlist (the decision columns) and Evidence (sample sizes, sponsor names, and the reason any answer was withheld). Export the Shortlist view for a clean CSV — exporting the unfiltered dataset sorts all columns alphabetically.

Every row carries the same columns, including rows for channels that could not be read, so a spreadsheet built on the output never changes shape halfway down.

Pricing

Pay per channel analyzed. Channels that could not be read are not charged — our failure is not your bill.