This is your real addressable audience — not total population. A country with 1B people where only 5% use gives 50M potential users. Same as a 130M country at 38%.

💡 Combine with GDP per capita to judge quality vs quantity. A smaller audience in a rich country can be worth more than a huge one in a price-sensitive market.

Formula: GDP per capita → price tier

💡 Sets the economic ceiling — what people can generally afford. If Sub mkt. is also shown, use both together: this sets the ceiling, Sub mkt. confirms what already works.

Formula: Median paid app price from the top chart

More reliable than the GDP estimate — it shows confirmed willingness to pay in this specific niche. If the median is $4.99 in a mid-income country, that's real purchase behavior, not a theoretical ceiling.

💡 If market median is lower than the GDP estimate suggests, price-sensitivity is higher than average. If it's higher — users in this category are willing to pay premium. Follow the market, not the model.

On Mac, or on any Top Free chart: there are no paid apps to read a price from, so this is instead the median monthly subscription price sampled from in-app purchases (% of them offer a free trial).

The 0.4% base coefficient is calibrated on iPhone against known data: US App Store spending ~$33B/year with ~184M iOS users at GDP/cap $65K gives ~0.27%. We use 0.4% as a conservative upper estimate that accounts for higher engagement in developed markets.

💡 Use it to compare countries and size the prize. A $50B market and a $200M market take the same effort to enter but have very different upside. Don't treat this as an exact figure — treat it as an order of magnitude.

Formula: Money capacity ÷ apps in chart ÷ 12

On Mac: the chart is the ~100-app Top Free list — Mac has no Paid/Grossing chart to divide by instead.

Reality check: App revenue follows a power law — the top 10 apps earn most of the money, the rest of the chart earns very little. This number is a market-size reference, not a personal revenue forecast.

💡 Best used for cross-country comparison. If Avg MRR/app in Germany is 5× Ukraine, that's a signal about the prize pool size. Whether you capture it depends on your product and positioning.

Source: Wikipedia / IMF. Shown in trillions USD.

GDP is a proxy for total spending power. Larger GDP = more money flowing through the economy = bigger absolute app market.

💡 Don't use GDP alone — a huge but poor country (high GDP, low GDP/cap) has less app-buying power per person than a small rich one. Always pair with GDP/cap to get the full picture.

Source: Wikipedia / IMF. Shown in thousands USD (e.g. 12,34 = $12,340/year).

GDP/cap directly drives subscription pricing — what people can realistically pay per month. It's the foundation for the Sub price estimate shown earlier in this row.

💡 Higher GDP/cap = users more likely to convert on IAP or subscriptions. A market with 20M users at $50K GDP/cap is usually more valuable than 80M users at $8K.

Source: Wikipedia / IMF

Context for . A populous country where few people use can still be a large market in absolute numbers. Compare with to understand penetration.

💡 Small countries can still be premium markets. Switzerland (8M people) and Germany (83M) have very different populations but both have high GDP/cap — making them both excellent targets.

Source: World Bank

Urban users have faster internet, more devices per person, and more app spending habits. Rural populations in lower-income countries often have limited data plans or shared devices.

💡 70%+ urban is a good signal. Below 50% — even with large total population — the actual addressable audience is smaller than the numbers suggest.

Source: World Bank / ITU

No internet = no downloads. Directly limits your real addressable market. In most developed markets it's 90%+, but in some emerging markets it can be 40–60%, which cuts your audience significantly.

💡 Look for markets with 80%+ internet penetration unless you're building offline-first apps. Below 60% — only target if you have a specific reason (language niche, diaspora audience, etc.).

Formula: Sum of the % share of the 3 largest categories

💡 Low concentration = more places to land. High concentration doesn't mean avoid — it means either compete inside the big 3 with a sharp angle, or find a niche in the long tail.

Formula: Gap between the #1 category share and the median of the top 5

💡 High risk doesn't mean "avoid" — it means be deliberate. Outside the dominant category you face less pressure. Inside it, you need a sharper product, not just a newer one.

Formula: Based on Top 3 concentration + gap between #1 and median category

💡 Accessible or Open is the sweet spot for indie developers. Locked isn't impossible — it means you need a niche play or a product that's clearly better than what's already there.