Discover top-ranking apps by country, chart type and result limit. Explore popular free and paid apps across different markets.
Choose your market and ranking preferences to view the top apps.
An apps rank tracking tool helps researchers observe where mobile applications appear in a supported public store chart. This tool focuses on chart discovery: choose a country, select a top-free or top-paid list, set the available category scope and choose how many results to display. The returned table provides a time-specific view of the apps currently available through that public chart request.
The word “tracking” can describe several different ASO activities. Some platforms save daily keyword positions, some monitor category charts, and others combine public store data with private developer analytics. This page is a public chart explorer. It does not ask for an app identifier or search keyword, and it does not connect to App Store Connect or Google Play Console. Use it to study chart visibility and market context rather than to claim verified downloads, revenue or conversion performance.
Storefront results can vary by country. Regional availability, audience demand, pricing, language, competition and merchandising can create a different chart in Bahrain, the United States, India or another market. Always record the selected country when documenting a result.
A top-free list and a top-paid list answer different questions. Free apps compete within a low-friction acquisition model, while paid apps ask a user to purchase before installation. Avoid treating the two charts as interchangeable benchmarks.
The maximum-results control changes how much of the available chart is displayed. A top-10 view is useful for immediate leaders; a deeper list can reveal additional publishers, categories and positioning patterns. Result depth does not change the underlying rank calculation.
Returned details may include rank, app name, developer, category, release information and a store destination when supported. These fields help identify the visible listing, but they should not be interpreted as private business-performance metrics.
Top-chart analysis and keyword-position analysis are both useful for App Store Optimization, but they measure different discovery surfaces. Confusing them can lead to incorrect reporting.
| Measurement | Question answered | Required context | What it does not prove |
|---|---|---|---|
| Top chart position | Which apps appear in a selected public chart? | Country, free or paid chart, category and observation time | Exact downloads, retention, revenue or keyword visibility |
| Keyword position | Where does a particular app appear for a particular search phrase? | Store, country, language, keyword, device context and observation time | Conversion rate or total organic acquisition |
| Private product analytics | How do impressions, page views, installs, purchases or retention perform? | Authorized developer-console or analytics access | The full public competitive landscape |
A repeatable process produces more useful evidence than an isolated lookup. Apply the same settings, record the observation context and connect public findings with verified product data before changing a store listing.
Decide whether you are studying free-chart leaders, paid-app competition, a launch market, localization opportunities or category positioning. A clear question determines which storefront and chart type are relevant.
Choose the storefront that matches the audience you want to understand. Do not use one country as a universal proxy. If several markets matter, run equivalent checks and document each result separately.
Compare top-free with top-free and top-paid with top-paid. Use the same result depth when reviewing changes. Consistency reduces the risk of mistaking a settings difference for a market movement.
Study relevant app names, publishers, categories and store listings. Look for recurring value propositions, audience language, pricing models and category patterns without copying protected creative work or unsupported claims.
Save the country, chart type, result limit, date and time. Public charts can change, so a rank without context is difficult to reproduce or cite responsibly.
Compare public observations with authorized impressions, product-page views, installs, conversion, retention, ratings and revenue. Public visibility and business performance are related questions, not identical measurements.
A high position means the app appeared near the top of the selected public chart when the request was made. It is evidence of visibility within that chart context. It can justify a closer review of the app’s listing, publisher, category, pricing model, ratings, release activity and market fit.
It does not independently reveal why the app reached that position. Public charts may respond to signals and editorial systems that this tool cannot observe. A position does not disclose an exact install count, paid acquisition spend, conversion rate, active-user total, retention rate or revenue. Avoid turning correlation into a causal claim.
Geographic App Store Optimization begins with the recognition that users, competitors and storefronts differ by market. Localization is more than translating words. The app name, subtitle, description, screenshots, pricing, support information and cultural framing should accurately reflect the intended audience and the product that users will receive.
Generative Engine Optimization and AI Optimization concern whether an entity can be understood and accurately described by AI-assisted discovery systems. For an app, that means maintaining consistent facts across the official store listing, product website, developer identity, documentation and support pages. Clear descriptions of purpose, platform, audience, features, limitations, availability and pricing give search and answer systems more reliable evidence.
GEO or AIO does not mean adding artificial keyword repetition or promising that an AI assistant will recommend the app. Public chart rank is only one contextual signal. Accurate entity information, strong product experience, credible reviews, accessible documentation and consistent first-party facts are more durable than unsupported optimization claims.
The user selects a country, a supported chart type, the available category scope and a maximum result count. The application sends those parameters to the existing tool processing route. Supported public chart data is requested and normalized into a table that may include rank, app name, store destination, developer, category and release information. The page does not calculate an independent popularity score and does not invent missing values.
Results represent the public response available at request time. Store data, chart composition, app availability and listing fields may change. A later request can therefore return a different order or different records. Anyone citing a finding should record the page URL, selected country, chart type, result depth and retrieval date.
The methodology is descriptive, not predictive. It reports supported public chart evidence but does not forecast future position or guarantee acquisition. Missing apps can result from chart depth, storefront availability, category context, temporary upstream behavior or other factors. Confirm important decisions using the official store listing and authorized analytics.
A useful monitoring log preserves the context behind every observation. Record the app-store country, chart type, category scope, result depth, retrieval date and time. If you are reviewing a particular competitor, also record its visible app name, developer name, category and store URL. These fields make later comparisons easier to reproduce.
Use a regular observation schedule that fits the decision being made. A launch review may require more frequent checks, while broader market research may use weekly snapshots. Avoid changing the country, chart type and result depth midway through a comparison without documenting the change. Otherwise, a difference in settings may look like a ranking movement.
Add a separate notes field for verified events: a new app version, pricing change, localization update, major promotion, store-feature event or important product announcement. These notes provide possible context but do not prove what caused a rank change. Store-ranking systems use signals that a public chart lookup cannot fully observe.
Finally, connect each public snapshot with the appropriate first-party measurement. If the objective is acquisition, review authorized impressions, product-page views, installs and conversion. If the objective is product quality, review retention, engagement, ratings, support feedback and reliability. This prevents a visible chart position from becoming the only measure of success.
It retrieves a public app chart snapshot using the selected country, free or paid chart type, category scope and result limit. It does not access private developer analytics.
No. This tool shows public top-chart positions rather than an app position for a typed keyword. Keyword tracking and top-chart research answer different ASO questions.
Each storefront can reflect different audiences, competition, availability, pricing and regional demand. A position observed in one country should not be assumed to apply globally.
No. A public rank is a visibility signal, not a verified download total. Downloads, conversion rate, retention and revenue require authorized private analytics.
Use a consistent schedule and record the country, chart type, result depth and observation time. Comparing equivalent snapshots is more useful than reacting to one isolated position.
No. It supports public market research, but ranking and conversion outcomes depend on listing relevance, product quality, ratings, localization, competition and other store-specific factors.