# App Store Keyword Rank Tracker — ASO Rankings | $2/1K (`bovi/aso-keyword-tracker`) Actor Track App Store search rankings for keywords (ASO). For each keyword, get ranked list of apps with position, name, developer, rating, and review count. Uses Apple's open iTunes Search API — no API key needed. Pay per keyword result. - **URL**: https://apify.com/bovi/aso-keyword-tracker.md - **Developed by:** [Vitalii Bondarev](https://apify.com/bovi) (community) - **Categories:** SEO tools, MCP servers - **Stats:** 5 total users, 4 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.94 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## 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 ```json { "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 ```json { "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](https://docs.apify.com/platform/integrations/n8n), [Make](https://docs.apify.com/platform/integrations/make), [Zapier](https://docs.apify.com/platform/integrations/zapier). - **Webhooks** — fire your own endpoint the moment a run finishes, to push results straight into your pipeline ([docs](https://docs.apify.com/platform/integrations/webhooks)). - **MCP server** — expose this actor as a tool to Claude, Cursor, or any [MCP client](https://mcp.apify.com) so an AI agent can pull this data mid-conversation ([guide](https://blog.apify.com/how-to-use-mcp/)). - **API & SDKs** — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs. See all [Apify integrations](https://apify.com/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](https://apify.com/bovi/google-play-scraper) - [Google Search (SERP) Scraper](https://apify.com/bovi/google-serp-structural) - [Similarweb Traffic Scraper](https://apify.com/bovi/similarweb-scraper) - [App Store Scraper](https://apify.com/bovi/app-store-scraper) - [App Update Tracker](https://apify.com/bovi/app-update-tracker) - [Appstore Charts](https://apify.com/bovi/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. ### Use it from your existing tools #### Use with Claude Desktop / Cursor / Cline (MCP) Load this actor as a tool in your AI assistant. Call it directly from your AI assistant via the Apify MCP server — no Store browsing needed. Paste this into your MCP client config (e.g. `claude_desktop_config.json`) and restart the client: ```json { "mcpServers": { "apify-aso-keyword-tracker": { "command": "npx", "args": [ "-y", "@apify/actors-mcp-server", "--tools", "bovi/aso-keyword-tracker" ], "env": { "APIFY_TOKEN": "YOUR_APIFY_TOKEN" } } } } ``` Replace `YOUR_APIFY_TOKEN` with your own Apify API token (free at apify.com → Settings → Integrations). Curated to a handful of tools so the agent selects reliably. #### Works with Clay Run this actor as an HTTP enrichment step inside a Clay table: - **Method:** `POST` - **URL:** `https://api.apify.com/v2/acts/bovi~aso-keyword-tracker/run-sync-get-dataset-items?token={{apify_token}}` - **Body (JSON):** map your Clay columns to the actor input (see the Input section above), e.g. `{"keywords": "{{clay_column}}"}` The run finishes synchronously and returns the dataset rows straight into your Clay table. It runs on Apify's cloud under your own token and usage. Synchronous runs must complete within 300 seconds. # Actor input Schema ## `keywords` (type: `array`): List of search keywords to track rankings for. Each keyword produces a ranked list of apps. Example: \["photo editor", "fitness tracker", "meditation app"]. ## `country` (type: `string`): Two-letter ISO country code for the App Store storefront (e.g. us, gb, de, jp). Default: us. ## `limit` (type: `integer`): How many app results to return per keyword (max 200 per Apple API). Default: 50. ## Actor input object example ```json { "keywords": [ "photo editor", "fitness tracker" ], "country": "us", "limit": 50 } ``` # Actor output Schema ## `results` (type: `string`): Dataset containing keyword ranking records (keyword, position, app\_id, bundle\_id, name, developer, rating, rating\_count, price, currency, url, icon\_url, genre, country, etc.) # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "photo editor", "fitness tracker" ], "country": "us", "limit": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("bovi/aso-keyword-tracker").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "photo editor", "fitness tracker", ], "country": "us", "limit": 50, } # Run the Actor and wait for it to finish run = client.actor("bovi/aso-keyword-tracker").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "photo editor", "fitness tracker" ], "country": "us", "limit": 50 }' | apify call bovi/aso-keyword-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=bovi/aso-keyword-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "App Store Keyword Rank Tracker — ASO Rankings | $2/1K", "description": "Track App Store search rankings for keywords (ASO). For each keyword, get ranked list of apps with position, name, developer, rating, and review count. Uses Apple's open iTunes Search API — no API key needed. Pay per keyword result.", "version": "0.1", "x-build-id": "bA65gayLcBNNchqg1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/bovi~aso-keyword-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-bovi-aso-keyword-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/bovi~aso-keyword-tracker/runs": { "post": { "operationId": "runs-sync-bovi-aso-keyword-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/bovi~aso-keyword-tracker/run-sync": { "post": { "operationId": "run-sync-bovi-aso-keyword-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "keywords" ], "properties": { "keywords": { "title": "Keywords to track", "type": "array", "description": "List of search keywords to track rankings for. Each keyword produces a ranked list of apps. Example: [\"photo editor\", \"fitness tracker\", \"meditation app\"].", "items": { "type": "string" } }, "country": { "title": "Country code", "type": "string", "description": "Two-letter ISO country code for the App Store storefront (e.g. us, gb, de, jp). Default: us." }, "limit": { "title": "Results per keyword", "minimum": 1, "maximum": 200, "type": "integer", "description": "How many app results to return per keyword (max 200 per Apple API). Default: 50." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```