Apple App Store Keyword Rank Tracker
Pricing
from $10.00 / 1,000 keyword checks
Apple App Store Keyword Rank Tracker
Track where your iOS app ranks in Apple App Store search for any keyword, with the top competing apps for every term. Run on a schedule for daily rank history.
Pricing
from $10.00 / 1,000 keyword checks
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App Store Keyword Rank Tracker
Track where your iOS app ranks in Apple App Store search for any keyword — and see the top competing apps for every term. Built to run on a schedule for a daily ranking history.
What you get
For every keyword you track, one row containing:
- Your rank — the position your app holds in App Store search results for that keyword (or "not found" if it ranks beyond your chosen search depth)
- Your app's full listing as it appears for that keyword — title, developer, rating, rating count, price, and icon
- Top competitors — the highest-ranking apps for the keyword, each with rank, App Store ID, title, developer, rating, rating count, price, store URL, and icon
- A timestamp on every row, so scheduled runs build a clean rank-over-time history
- Total results found and the search depth used
Export to JSON, CSV, Excel, or Google Sheets — or run on a schedule and append to the same dataset for a time series.
Use cases
- App Store Optimization (ASO) — measure how keyword changes move your ranking over time
- Keyword strategy — find which terms you already rank for and which you don't
- Competitor monitoring — see exactly which apps outrank you for your most valuable keywords
- Release impact tracking — schedule daily runs and watch how each update shifts your positions
- Agency reporting — pull client ranking snapshots for any country on demand
How to use
- Add your Keywords — one search term per line
- Enter the App to track — your app's Apple App Store numeric ID (e.g.
571800810) or bundle ID (e.g.com.calm.app) - Set the Country storefront (two-letter code, default
us) - Choose the App type — iPhone, iPad, or Mac apps
- Set Search depth (how deep to look, max 200) and Top competitors to capture
- Run the actor — one row per keyword in the Dataset tab
Build a ranking history
Set this actor on an Apify Schedule (e.g. once a day) and let it append to the same dataset. Each run stamps every row with checkedAt, so you get a daily time series of your rankings and your competitors' — the foundation of any ASO dashboard.
Finding your App Store ID
Open your app's App Store page; the number after id in the URL is your App Store ID — e.g. https://apps.apple.com/us/app/calm/id571800810 → 571800810. You can also use your bundle ID.
Output format
One row per keyword:
{"keyword": "meditation","platform": "ios","country": "us","entity": "software","trackedAppId": "571800810","rank": 4,"found": true,"totalResults": 100,"searchDepth": 100,"checkedAt": "2026-05-29T18:00:00.000Z","trackedApp": {"rank": 4,"appId": 571800810,"bundleId": "com.calm.app","title": "Calm","developer": "Calm.com, Inc.","rating": 4.8,"ratingCount": 1700000,"price": 0,"formattedPrice": "Free","url": "https://apps.apple.com/us/app/calm/id571800810","iconUrl": "https://.../512x512bb.jpg"},"topResults": [{ "rank": 1, "appId": 123, "title": "...", "developer": "...", "rating": 4.7, "ratingCount": 90000 }]}
Input options
| Field | Type | Description |
|---|---|---|
| Keywords | array | Search terms to check — required |
| App to track | string | App Store numeric ID or bundle ID — required |
| Country | string | Two-letter storefront code — default us |
| App type | enum | iPhone (software), iPad, or Mac apps — default iPhone |
| Search depth | integer | How many results to scan, 1–200 — default 100 |
| Top competitors to capture | integer | Competitors to include per keyword — default 10 |
Notes
- Rankings reflect Apple's App Store search relevance order for each keyword and storefront. They closely track what users see in the App Store and are ideal for monitoring movement over time.
- If your app ranks beyond the Search depth,
rankis reported asnullandfoundasfalse— raise the depth (up to 200) to look deeper. - One result row is produced per keyword, so a run checking 50 keyword × storefront combinations is fast and inexpensive.