Read your own users against the world's speakers.
Speaker counts size the market. Your own DAU or MAU shows how much of it you already serve. Load per-market usage from your analytics stack as CSV or JSON, and nothing leaves the browser. Every market then gets a second axis: penetration of the online audience you could reach, the headroom you have not reached yet, engagement stickiness, and an estimated split of your users by language.
Penetration & headroom
Every market gets a second axis: how much of the online audience you already reach, and how much is left.
Users per language
Your MAU apportioned across each market's language mix: a ranking signal for the next translation target.
Blended everywhere
The active product shows up in the explorer, the coverage map, the launch planner, and every country page.
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Drop your export here, or browse files
CSV or JSON · country + MAU required · DAU, revenue (monthly USD) optional · up to 400 markets
or paste CSV / JSON
Everything parses in your browser. Nothing goes to a server.
How the tool computes the derived metrics
Penetration is MAU ÷ addressable online population (World Bank internet users × CLDR population). It can exceed 100% when a product counts accounts instead of people. Headroom is the remainder: online users you have not reached. Stickiness is DAU ÷ MAU.
The language rollup apportions each market's MAU across its languages by normalized CLDR L1+L2 share. It assumes your users mirror the territory's language mix. It is a prioritization model, not a measurement. Use it to rank translation targets. Do not report the split as audience sizes.
Your data stays in this browser (localStorage). There is no server-side storage. Pipelines can call POST /api/atlas/usage for the same join as JSON or CSV.