Which languages to add first, and how to tell
Not a ranked list of the world's biggest languages. A method for reading your own analytics, because the right first language depends on your audience.
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Every article answering this gives you the same table: speakers worldwide, internet users by language, GDP per market. That table is identical for everyone reading it, which is the clue that it can't be the answer to a question about your audience.
The right first language is already visible in data you have. Here's how to read it, and what to do when it says something inconvenient.
Start with who is already watching
Your analytics know where people are and, on YouTube, what language they've set their interface to. Both matter, and they answer different questions.
Geography tells you where viewers are physically. Interface language tells you what they prefer to consume in, which is closer to what you need. A viewer in Berlin with an English interface is telling you something different from a viewer in Berlin with a German one.
Pull the last 90 days and rank by watch time rather than by views. Views count arrivals; watch time counts people who stayed. Someone who watched 80% of a 20 minute video despite the audio being in their second language is a much stronger signal than a hundred people who bounced at ten seconds.
What you're looking for is a market that's already showing up in numbers despite the friction of your current audio. That's demand leaking through a barrier, and removing the barrier is the highest-probability bet on the board.
The signal most people miss
Look at your retention curve broken out by country, not just your view counts.
A market with decent views but a retention curve that falls off a cliff in the first minute is often a comprehension problem, and comprehension problems are what dubbing fixes. A market with low views but strong retention has an entirely different problem, which is discovery, and no amount of dubbing solves it.
That distinction decides where your money goes. Dubbing addresses the first case and does nothing for the second.
Ask what already succeeded without your help
Two more things worth checking before you commit.
Where your subtitles get used. If you've published captions, the language breakdown on their usage is a direct measurement of people who wanted your content in another language and took an extra step to get it. That's the closest thing to a pre-order you'll find.
Where comments come from. Non-English comments on an English video are people who pushed through the friction and then engaged anyway. A market that comments in its own language on your content is telling you plainly that it wants a version of its own.
When the data says something inconvenient
It often will, and following it is usually right.
The market your analytics point at may be smaller than the one you'd pick from a global table. That's fine. A market where you already have traction converts far better than a large market where nobody has heard of you, and the whole point of this exercise is to start where the evidence already is rather than where the opportunity theoretically is.
The other awkward case: your data may point at a market whose audience largely speaks your original language comfortably. Some markets have high functional fluency in English, and dubbing there buys less than the raw numbers suggest. Retention is what disambiguates this. Strong retention in a market means your current audio is already working for them, and translating it is solving a problem they don't have.
Cost it exactly before you commit
One advantage of per-language pricing is that the cost of adding a language is knowable to the credit before you spend anything.
One job is one file and one target language, so the arithmetic is your video length rounded up to the whole minute, multiplied by the number of files you'd dub. There's no bulk rate and no per-language discount, which means there's also no penalty for starting with exactly one. Credits don't expire, so a language that turns out to be wrong costs you the test rather than a commitment.
That makes the sensible move obvious: dub your best-performing video into the single language your analytics most strongly support, publish it, and watch that market for a month. One data point about your own content is worth more than every ranked table on the internet, this page included.
Then read the second signal
After a month you'll have something nobody could have told you in advance: whether that market responds to your content in its own language, and by how much.
If it does, the second language is usually easier to pick, because you now know what a responsive market looks like in your own numbers and can go looking for the next one that resembles it. If it doesn't, you've learned that for a few credits rather than for a catalogue.
Where to look up a specific language
We dub into 32 languages, and that list is what the upload endpoint actually accepts rather than a marketing figure. Each one has its own guide covering the practical side, organised by content type: the YouTube dubbing hub, the e-learning hub, the marketing hub, the corporate hub and the SaaS hub. The use case index covers all of them.
Once you have a shortlist from your own data, those pages are where to check the specifics for the pairing you're considering.
FAQ
How do I choose which language to localize first?
From your own analytics rather than from a global table. Rank the last 90 days by watch time, look for markets already showing up despite your audio being in another language, and check retention curves by country to separate comprehension problems from discovery problems. Dubbing fixes the first.
Should I pick the language with the most speakers?
Not by default. A large global market where nobody knows you converts worse than a smaller one where you already have traction. Global speaker counts are identical for every business reading them, which is why they can't tell you anything specific about yours.
How many languages should I start with?
One. Pricing is per file per language with no bulk rate, so there's no discount for committing to several, and credits don't expire. Test one language on your best-performing video, wait a month, and let the result choose the second.
What if my analytics don't show a clear winner?
Then look at subtitle usage by language and at which languages appear in your comments. Both measure people who wanted your content in another language enough to work around the barrier, which is the strongest demand signal available before you spend anything.