App Store Keyword Rankings & ASO Scraper

App Store keyword rankings, made exact: this Actor returns the precise App Store search rank of every app for any keyword and country storefront you give it, plus the app's full store metadata — developer, price, rating, rating count, genre, screenshots, description and update date. Rankings are measured per storefront, so the same app can sit at #3 in the US and #40 in Germany, and no API key, Apple account or login is needed. Run it to answer the three questions ASO turns on: where do I rank, who is beating me, and is the keyword worth fighting for?

What you get

• rank — the exact position (1, 2, 3 …) Apple returns for each app, per keyword, per storefront. Real rank, not a reconstructed or vendor-invented score.
• appName, developerName, primaryGenre, averageUserRating, userRatingCount — the full competitive snapshot on every row.
• price, formattedPrice, currency, isFree — monetisation per storefront, so you see where a niche is paid and where it is free-only.
• keywordMatchInTitle and keywordMatchInDescription — whether the ranked app uses your keyword in its own name, Apple's strongest ranking signal.
• screenshotUrls, descriptionChars, supportedLanguages, minimumOsVersion and version — listing metadata for a visual and textual teardown.
• recordHash — deterministic over app, keyword and storefront, so two scheduled runs diff into a rank-change report.

Quick start

1. Add one or more keywords to Keywords to rank for — phrase them the way a real user types them (habit tracker, budget app). The field comes prefilled, so you can also just run it as-is.
2. Add Country storefronts as two-letter codes (us, gb, de, jp). Every storefront is measured separately.
3. Run it with this minimal input:

{
  "keywords": ["habit tracker", "budget app"],
  "countries": ["us"],
  "resultsPerKeyword": 50
}

4. Click Start, then open the Rankings, Competitive landscape and App metadata dataset tabs.

Example output

One representative dataset row (US storefront, keyword habit tracker):

{
  "recordType": "ranking",
  "ok": true,
  "errorCode": null,
  "keyword": "habit tracker",
  "storefront": "us",
  "rank": 4,
  "appId": "1091189122",
  "bundleId": "com.example.habits",
  "appName": "Habit Tracker - Daily Goals",
  "developerName": "Example Labs",
  "developerId": "1234567890",
  "developerUrl": "https://example.com",
  "appStoreUrl": "https://apps.apple.com/us/app/habit-tracker/id1091189122",
  "price": 0,
  "formattedPrice": "Free",
  "currency": "USD",
  "isFree": true,
  "primaryGenre": "Health & Fitness",
  "genres": ["Health & Fitness", "Productivity"],
  "averageUserRating": 4.82,
  "userRatingCount": 128411,
  "version": "4.12.0",
  "currentVersionReleaseDate": "2026-09-24T10:00:00Z",
  "releaseDate": "2016-05-02T07:00:00Z",
  "minimumOsVersion": "16.0",
  "contentAdvisoryRating": "4+",
  "fileSizeBytes": 189663232,
  "artworkUrl": "https://is1-ssl.mzstatic.com/image/thumb/.../512x512bb.jpg",
  "screenshotCount": 8,
  "supportedLanguages": ["EN", "DE", "FR"],
  "descriptionChars": 2410,
  "keywordMatchInTitle": true,
  "keywordMatchInDescription": true,
  "recordHash": "5f2b8c1d94e03a76",
  "scrapedAt": "2026-10-02T12:00:00.000Z"
}

What this ASO keyword scraper returns

• 🏆 Real ranks, per storefront — one row per app per keyword per country, with rank starting at 1. Rankings are per storefront, so the same app can sit at 3 in the US and 40 in Germany. Add countries and the Actor tells you that in its run summary.
• 🧠 Difficulty you can audit — keywordMatchInTitle records whether each ranked app uses the keyword in its own name, the strongest signal Apple uses. The run summary reports how many of the top 5 titles contain the keyword. A top 5 where nobody uses the keyword is an opening; a top 5 where everybody does is a wall.
• 💪 Incumbent strength in one glance — userRatingCount next to rank. A high rank with a low rating count is a weak incumbent, and that is the most actionable pattern in ASO.
• 💰 Price and business model — price, formattedPrice, currency and isFree per storefront, so you can see where a niche is monetised and where it is free-only.
• 🖼️ Creative and listing data — up to 10 screenshot URLs, icon, description and its length, supported languages, minimum iOS, age rating and file size. Everything you need to benchmark a listing visually and textually.
• 🔍 Direct app lookup — skip the keyword search and resolve any app by numeric ID, bundle ID, App Store URL, or name:Search Term for the top match by name. Those rows carry rank: null.
• 📈 Rank-change tracking — recordHash is deterministic over app, keyword and storefront. Schedule the Actor and diff two runs to get a rank-movement report for free.
• 🎯 Filters that cut your bill — minimum average rating, free-only and paid-only all run before rows are written, so filtered apps are never charged.

Running on Apify adds scheduling, webhooks, monitoring, API and SDK access, and one-click export to JSON, CSV, Excel, Google Sheets and 20+ integrations.

How to use it

1. Add search terms to Keywords to rank for, phrased the way a real user types them.
2. Add Country storefronts — two-letter codes such as us, gb, de, fr, jp.
3. Set Results per keyword. Top 10 is the usual ASO target; 50 exposes the long tail.
4. Optionally add apps to the Apps to look up directly list for pure metadata pulls.
5. Click Start, then use the Rankings, Competitive landscape and App metadata dataset tabs.

How do I find out if a keyword is worth targeting?

Run the keyword, then look at two things in the Competitive landscape view: userRatingCount across the top 5, and keywordMatchInTitle across the top 5. Low rating counts with few title matches means a weak, beatable set. High rating counts with the keyword in every name means you would be fighting established apps on their own strongest signal.

How do I track my own rank over time?

Schedule the Actor daily, keep keyword and storefront fixed, and compare rank between runs using recordHash or the app ID. You get a rank-tracking pipeline without paying a per-seat ASO subscription.

How much does it cost to scrape App Store rankings?

Pricing is pay per event with one event:

Event	What triggers it	Billed
App ranking	One app's rank and metadata written to the dataset	per row
Actor start	Once per run, platform fee	per run

A 50-result keyword in one storefront is 50 rows. Five keywords across three storefronts at 50 results each is 750 rows — that is the whole calculation. Compute, bandwidth and storage are included; there is no separate platform-usage charge on top.

Rows removed by your filters are not billed. Keywords and apps that return nothing are not billed.

Set Max cost per run in the run options for a hard ceiling. Higher Apify plans get progressively lower per-row pricing through Apify Store tier discounts.

Zero-cost sizing: set Results per keyword to 10 with one keyword and one country, and you can see the entire output shape for the price of ten rows.

Example input

A full input with keywords, storefronts, direct lookups and filters:

{
  "keywords": ["habit tracker", "budget app", "learn spanish"],
  "countries": ["us", "gb", "de"],
  "resultsPerKeyword": 50,
  "apps": ["310633997", "com.spotify.client", "name:Duolingo"],
  "includeAppDetails": true,
  "minRating": 0,
  "freeOnly": false,
  "maxTotal": 3000
}

More example output

A keyword that returns nothing:

{
  "recordType": "ranking",
  "ok": false,
  "errorCode": "EMPTY_RESULT",
  "error": {
    "code": "EMPTY_RESULT",
    "message": "No apps matched \"a very long phrase nobody searches\" in the US storefront. Very long-tail phrases can genuinely return nothing.",
    "hint": "The source responded correctly but returned nothing for this query."
  }
}

Use cases

• ASO keyword research — build the ranked competitive set for every keyword in your niche, with real difficulty evidence.
• Rank tracking — schedule daily and diff rank per keyword and storefront.
• Competitor teardown — screenshots, description length, update cadence, language support and pricing for the apps outranking you.
• Niche discovery — userRatingCount across a category reveals which sub-niches have weak incumbents.
• Market entry research — compare the same keyword across storefronts to decide which country to launch in first.
• Listing optimisation — flag every top-5 competitor that uses the keyword in its app name and pull their descriptions to study metadata structure.

Related Actors by Axiora Solutions

Actor	Use it for
App Store Review Scraper	Pull the reviews of every competitor you find here and see what their users complain about
Domain Contact Enricher	Contact details for the developers and companies behind the apps
News & RSS Feed Scraper	Press and release coverage about the apps in your tracked set

Frequently asked questions

Is the rank Apple's real position or a computed score?

It is Apple's own relevance order, fetched from Apple's public search endpoint in the order Apple returns it, and numbered from 1. Nothing is recomputed server-side, which is why the number is trustworthy and why it is comparable between runs.

Do rankings differ by country?

Yes, substantially. Rankings, ratings, prices, screenshots and even the descriptions are per storefront. That is why countries is an array and why every row carries storefront. A one-country view of a global app is a partial view.

How can I tell if a keyword is hard?

Two auditable signals, both on your rows. userRatingCount of the top 5 — hundreds of thousands means established incumbents; under a few thousand means you can compete. keywordMatchInTitle across the top 5 — if most of them use the keyword in their own name, that position is reinforced by Apple's strongest ranking signal.

Can I get search volume for a keyword?

Not from Apple — Apple publishes no keyword search volume data at all, and any tool that shows you a precise volume number is modelling it, not measuring it. This Actor deliberately does not invent one. It gives you the ranked competitive set and incumbent strength, which is the evidence you can actually defend. Pair it with your own impression data from App Store Connect if you have it.

Does it work for any storefront?

Any two-letter App Store country code. Ratings, prices and screenshots are returned in that storefront's own currency and language.

What is descriptionChars for?

Apple does not use the description for ranking, but it drives conversion. Comparing descriptionChars across a ranked set tells you how much copy the incumbents are investing — and if the whole top 10 is under 1,000 characters, that is an easy place to out-work them.

Do I need an Apple account or API key?

No. Apple's public search and lookup endpoints are open, and nothing in the input is a credential, so an autonomous agent can call this Actor without a human.

Is scraping the App Store legal?

The Actor calls the same public JSON endpoints a browser hits when you search the App Store, and it identifies itself. Store listing data is public. You remain responsible for how you use it, including Apple's terms and any applicable marketing law.

Something looks wrong — how do I report it?

Open the Issues tab on this Actor page with the keyword, the storefront and what you expected to see.

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Runnable examples and how-to guides for these Actors: github.com/batow133/axiora-apify-actors