# Amazon FBA Competitor Keyword Tracker API (`intelscrape/amazon-fba-competitor-keyword-tracker`) Actor Headless programmatic extraction of Amazon's A9 ranking algorithm. Delivers real-time JSON payloads tracking competitor ASIN ranks, hidden keywords, and PPC momentum. Optimized for direct integration via webhooks and AI e-commerce workflows. Institutional grade, zero UI bloat. - **URL**: https://apify.com/intelscrape/amazon-fba-competitor-keyword-tracker.md - **Developed by:** [IntelScrape](https://apify.com/intelscrape) (community) - **Categories:** E-commerce, AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 asin / keyword payloads This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Amazon FBA Competitor Keyword Tracker Track Amazon competitor keyword rankings and search position changes in real-time. Monitors ASIN positions for target keywords, detects BSR shifts, and maps which competitors are gaining or losing organic visibility. ### What you get - Keyword search rank position per ASIN (daily tracking) - BSR and rank position change (up/down delta) - Sponsored vs. organic position differentiation - Competitor ASIN set for any target keyword - Top-of-search ad spend estimation - Search volume trend for tracked keywords - Output in deterministic JSON for FBA intelligence pipelines ### Use cases - **PPC optimization** - identify keywords where competitors are spending heavily vs. organically ranked - **Listing optimization** - detect keywords where your rank is slipping before sales drop - **Competitive intelligence** - monitor when new competitors enter your keyword space - **Launch strategy** - find keywords with high volume and weak current competitors - **Wholesale and arbitrage** - identify underranked products with strong keyword demand ### Sample output ```json { "keyword": "wireless headphones noise cancelling", "searchVolume": 245000, "results": [ { "asin": "B07ZPKN6YR", "title": "Sony WH-1000XM5", "organicRank": 1, "sponsoredRank": null, "bsr": 5, "bsrCategory": "Electronics", "rankChange": "+2", "trackedAt": "2026-04-05T21:00:00Z" } ], "scrapedAt": "2026-04-05T21:00:00Z" } ```` ### Keywords Amazon keyword tracker, Amazon rank tracker, Amazon ASIN tracker, competitor keyword monitor, Amazon BSR tracker, Amazon search rank, FBA keyword ranking, Amazon PPC tracker, Amazon listing optimizer, ASIN position tracker, Amazon keyword scraper, FBA competitive intelligence ### Integrations Outputs clean JSON for LangChain, n8n, Make.com, and FBA analytics dashboards. Schedule daily runs to build a keyword rank history database for every tracked ASIN. *** ### More Actors by This Developer | Actor | What it does | |-------|-------------| | **Amazon Product Scraper** | Scrape Amazon product data, BSR, and reviews at scale | | **Amazon FBA Research Tool** | Find winning FBA products with BSR opportunity scoring | | **TikTok Shop Scraper** | Extract trending product data from TikTok Shop | | **Zillow Foreclosure Scraper** | Find undervalued real estate investment opportunities | > Power combo: Run Amazon FBA Research Tool to find high-opportunity keywords, then use Competitor Keyword Tracker to monitor your rank position after optimizing your listing. # Actor input Schema ## `maxItems` (type: `integer`): Hard limit configuration constraint on extracted entities to prevent memory leaks. ## Actor input object example ```json { "maxItems": 100 } ``` # Actor output Schema ## `timestamp` (type: `string`): Time of extraction ## `target_url` (type: `string`): Source URL ## `data_payload` (type: `string`): Extracted JSON data ## `confidence` (type: `string`): AI confidence score ## `trigger_event` (type: `string`): What initiated this run # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("intelscrape/amazon-fba-competitor-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 = {} # Run the Actor and wait for it to finish run = client.actor("intelscrape/amazon-fba-competitor-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 '{}' | apify call intelscrape/amazon-fba-competitor-keyword-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=intelscrape/amazon-fba-competitor-keyword-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon FBA Competitor Keyword Tracker API", "description": "Headless programmatic extraction of Amazon's A9 ranking algorithm. Delivers real-time JSON payloads tracking competitor ASIN ranks, hidden keywords, and PPC momentum. Optimized for direct integration via webhooks and AI e-commerce workflows. Institutional grade, zero UI bloat.", "version": "1.0", "x-build-id": "IfkIAjfkThiroo0YT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/intelscrape~amazon-fba-competitor-keyword-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-intelscrape-amazon-fba-competitor-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/intelscrape~amazon-fba-competitor-keyword-tracker/runs": { "post": { "operationId": "runs-sync-intelscrape-amazon-fba-competitor-keyword-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/intelscrape~amazon-fba-competitor-keyword-tracker/run-sync": { "post": { "operationId": "run-sync-intelscrape-amazon-fba-competitor-keyword-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "maxItems": { "title": "Maximum Execution Result Extraction", "type": "integer", "description": "Hard limit configuration constraint on extracted entities to prevent memory leaks.", "default": 100 } } }, "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 } } } } } } } } } } ```