ASO Keyword Rank Tracker — App Store Rankings | $3/1K | No Key | 10× Cheaper

App developers, ASO managers, and mobile growth agencies use this actor to track how their app ranks for target keywords — without a Sensor Tower subscription. Schedule weekly runs to spot ranking trends.

$3.00 per 1,000 ranked results. Track 50 keywords × 50 results = $0.75 per sweep. Weekly tracking = ~$3/month. No subscription. No API key.

Worked example:

• 10 keywords × 50 results each = 500 results → $1.50
• 50 keywords × 50 results weekly = 2,500/week → $7.50/month
• 5 keywords × 200 results (deep sweep) = 1,000 results → $3.00

10–100× cheaper than ASO platforms. Sensor Tower and AppTweak charge $99–$500/month for keyword ranking data. This actor gives you the same raw rankings for under $5 per week.

Track how apps rank in Apple App Store search results for specific keywords (ASO — App Store Optimization). Uses Apple's open iTunes Search API — no API key required. Pay per result.

Sample output

{
  "keyword": "photo editor",
  "position": 1,
  "app_id": "1225106839",
  "name": "Facetune - AI Photo Editor",
  "developer": "Lightricks Ltd.",
  "rating": 4.6,
  "rating_count": 413000,
  "genre": "Photo & Video",
  "country": "us",
  "parse_confidence": 1.0
}

---

What you get

For each keyword → a ranked list of apps showing who appears at each position:

Field	Description
keyword	The search keyword
position	Search rank position (1 = top result)
app_id	Numeric Apple app ID
bundle_id	App bundle ID (com.company.app)
name	App name
developer	Developer name
rating	Average user rating
rating_count	Total number of ratings
price	Price (0.0 = free)
currency	Currency code
url	App Store URL
icon_url	App icon URL (512px)
genre	Primary category
all_genres	All categories
version	Current version
release_date	Original release date
update_date	Last update date
parse_confidence	Data quality score 0.0–1.0

Use cases

• ASO monitoring: track where your app ranks for target keywords
• Competitor research: see which apps dominate a keyword
• Market analysis: find what categories / developers own a search space
• Keyword discovery: see what shows up for related terms

Usage

{
  "keywords": ["photo editor", "fitness tracker", "meditation app"],
  "country": "us",
  "limit": 50
}

FAQ

Do I need an API key or ASO platform subscription? No. This actor uses Apple's public iTunes Search API — free, no auth, no proxy.

What formats can I export? JSON, CSV, Excel, or JSONL — from the Apify dataset UI or REST API.

How do I track rank changes over time? Schedule weekly runs via Apify Scheduler. Compare datasets across runs — the position and keyword fields are stable identifiers for diff queries.

What if a keyword returns 0 results? Some ultra-niche keywords return no apps. The actor logs a warning for that keyword and continues to the next — no crash, no charge for empty keywords.

Limits

• Apple's Search API returns up to 200 results per keyword
• Supports all App Store country storefronts
• Results reflect real-time App Store search rankings

vs. ASO platforms

Feature	This actor	Sensor Tower	AppTweak	AppFollow
Keyword rank positions	✅	✅	✅	✅
No subscription	✅	❌	❌	❌
Pay per keyword sweep	✅	❌	❌	❌
parse_confidence drift detection	✅	N/A	N/A	N/A
Monthly cost (50 kw × weekly)	~$3	$99–500	$99–249	$99+

parse_confidence — every record carries a 0.0–1.0 data quality score. Score < 0.5 → check the warnings field.

Best practice: Schedule this actor weekly. Keyword rankings shift constantly. Use Apify Scheduler + webhook to get alerts when your app drops or rises in position.

Monitoring workflow: Run weekly, store results in Apify Dataset, compare datasets across runs to detect ranking changes. Pipe to Slack or email via Apify webhook — full change-detection pipeline with zero server-side code.

Use with AI agents (MCP)

All actors in this suite are available via the Apify MCP server. Connect to Claude, GPT-4o, or n8n to let AI agents pull live App Store data on demand — market research, competitor monitoring, and ASO tracking automated end-to-end.

MCP config: https://mcp.apify.com/?tools=bovi/aso-keyword-tracker

Also in this suite

• Apple App Store Scraper — full metadata + reviews
• Google Play Store Scraper — Android ecosystem
• App Store Charts Scraper — market surveillance, chart positions
• iOS App Update Tracker — version monitoring, change detection
• App Store Reviews Scraper — reviews-only, bulk NLP use case
• F-Droid Scraper — FOSS/privacy research

Integrations

Built for app developers and ASO agencies tracking keyword search rankings without a Sensor Tower subscription — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Google Play Scraper
• Google Search (SERP) Scraper
• Similarweb Traffic Scraper
• App Store Scraper
• App Update Tracker
• Appstore Charts

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.