About
Why TubeHunter exists
Most YouTube tools hand you a single "difficulty" score and hide how they got it. That score usually measures how much advertisers compete for a keyword - not whether a channel your size can actually rank. TubeHunter was built to answer the question creators really ask: what should I make next, and will it beat my own channel's median?
We break every channel down the same way - not vanity subscriber counts, but the things that decide a video: the titles that won versus flopped, the words that keep showing up in the winners, the median views, the best time to post, and how consistently the channel hits.
How we measure a channel
Every number on TubeHunter comes from real, public YouTube data - the same information anyone can see on a channel and its videos. There is no private clickstream and no black box. The core metrics:
- Median views - the typical performance of a video, far more honest than an average one viral hit can distort.
- Hit-rate - the share of a channel's uploads that beat 2× its own median. It measures how consistently a channel breaks out, independent of its size.
- Top-video share & multiple - how much of a channel's reach comes from its biggest hits, and how far the best video pulled ahead.
- Winning title words - the words that recur in a channel's over-performing titles versus the ones that flop.
- Cadence & typical length - how often the channel posts and how long its videos usually run.
Why you can trust the numbers
We only publish what the data supports. Estimates (like ad-revenue ranges) are clearly labelled and shown as ranges, because true earnings depend on niche RPM, sponsorships, and factors no outside tool can see. When something is a signal rather than a certainty, we say so - we would rather show a smaller honest number than a confident wrong one.
Who builds TubeHunter
I'm a one-person shop. I've spent years pulling apart what actually makes YouTube videos work - title patterns, retention, the demand behind a topic - and I got tired of tools that dress up an ad-competition score as "difficulty." So I built the thing I wanted: honest, median-based analysis from public data, with the reasoning shown instead of hidden.
I keep my name off the site on purpose. Not to hide - the whole method is laid out above - but because I'd rather the numbers earn your trust than a headshot and a LinkedIn. I run every metric against my own channels first; if it doesn't help me decide what to film, it doesn't ship here.
- built solo, no VC, no growth team, just data and a lot of coffee ☕
Get in touch
Questions, corrections, or a channel you'd like analysed: [email protected]. Corrections to any breakdown are always welcome - accuracy matters more than being first.