Report 002 · Data limits
Apple has no global chart, so we did not invent one
A clean average across 51 local rankings would look convincing. It would still ignore differences in storefront size, availability, and the complete absence of public download data.
Apple's Marketing Tools feed is organized by storefront. The United States, Japan, and Taiwan each have separate charts. They are not translations of one ranking.
What we actually count
- Select 51 Apple storefronts.
- Collect each local paid top 100.
- Merge the same product by Apple App ID.
- Add one for each storefront where the product appears.
- Keep the local positions and calculate an average only for those appearances.
The July 16 snapshot contains 5,100 chart positions and 2,190 unique App IDs. Every storefront counts as one. There is no weighting for population, iPhone usage, store revenue, or purchasing power.
Why this is not a global ranking
Suppose one app ranks first in the United States but nowhere else, while another ranks number 90 in 30 markets. The winner changes depending on whether the question is sales, reach, revenue, or cultural fit. The public feed does not provide enough data to settle that question.
Cross-market presence tells us how many local charts contained a product. It does not tell us which app sold the most worldwide.
Why begin with paid apps
Free charts are dominated by large platforms such as ChatGPT, Gemini, Threads, Google Maps, Claude, CapCut, and Telegram. The paid chart contains more buy-once professional tools, which makes small products easier to discover. It still does not equal an indie chart, so maker identity must be checked separately.
What this method misses
- Free, subscription, and in-app-purchase products
- Apps that perform well only in category charts
- Android, Steam, and web products
- Stable products outside the top 100
- Downloads and revenue
- Small timing differences within one collection run
Read it as radar, not a financial statement
The count is useful for finding small products that appear in several regions, comparing the shape of one app's local footprint, and tracking later snapshots without deleting the earlier one. It cannot prove that a product is a global hit or estimate a developer's monthly income.