# Amazon Bestsellers Tracker: Top 100 by Category (`dltik/amazon-bestsellers`) Actor Track Amazon's top 100 bestsellers across 8 marketplaces (US, FR, DE, UK, ES, IT, CA, JP). Filter by category and country. Get rank, ASIN, title, price, rating, reviews count, image URL. Daily refresh ready. For Amazon sellers, brands, e-commerce SaaS, product researchers. $2/1K products. - **URL**: https://apify.com/dltik/amazon-bestsellers.md - **Developed by:** [dltik](https://apify.com/dltik) (community) - **Categories:** E-commerce, Business, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $2.00 / 1,000 bestseller scrapeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 Bestsellers Scraper — Top 100 by Category, 8 Marketplaces > Track **Amazon's top 100 bestsellers** by category across 8 marketplaces (US, FR, DE, UK, ES, IT, CA, JP). Filter by category and country, get rank, ASIN, title, price, rating, reviews count, image URL. Daily refresh ready, HTTP-only, no proxy needed. **$0.002 per bestseller** ($2 per 1,000). ⭐ **Bookmark this Amazon Bestsellers Scraper** — Apify ranks actors by bookmarks, so it directly helps the visibility of this scraper on the Apify Store. ### What is the Amazon Bestsellers Scraper? The **Amazon Bestsellers Scraper** pulls Amazon's `/bestsellers` rankings on demand — across all 8 main marketplaces and any of Amazon's product categories. Drop in a category URL or one of the 50+ pre-configured category slugs (electronics, fashion, books, home-garden, toys-games, etc.) and get the live top 100. Multi-country in one run. Built for daily monitoring without paying for a subscription bestseller-tracker SaaS. Pure HTTP, low memory (256MB), works fine without residential proxies on most categories. ### Use cases - **Dropshipping product research** — daily refresh of best-sellers in your niche to spot rising products fast. - **Competitive pricing** — track competitor pricing on top items across 8 markets. - **Trend forecasting** — log bestsellers daily, compute velocity per ASIN, surface the rising stars. - **Affiliate marketing** — auto-publish "Top 10 X this week" posts using fresh bestsellers data. - **Brand monitoring** — track your own products' rank changes vs. competitors over time. ### Input ```json { "country": "US", "categories": ["electronics", "home-garden", "toys-games"], "topN": 100 } ```` ### Output ```json { "rank": 1, "country": "US", "category": "electronics", "asin": "B0EXAMPLE12", "title": "Example Product Name", "price_usd": 49.99, "rating": 4.6, "reviews_count": 14823, "image_url": "https://m.media-amazon.com/images/I/...", "amazon_url": "https://www.amazon.com/dp/B0EXAMPLE12", "scraped_at": "2026-05-01T12:00:00Z" } ``` ### Pricing **PAY\_PER\_EVENT — $0.002 per bestseller scraped** (= $2 per 1,000). Failed runs not charged. ### FAQ — Amazon Bestsellers API **Does this work without an Amazon API key?** Yes — Amazon's `/bestsellers` page is HTML, no API key needed. We parse the rendered HTML. **How often should I run it?** Amazon refreshes the bestseller rank every hour, but daily is enough for most use cases. Schedule daily on Apify and feed the dataset to your DB. **Can I track ASIN over time?** Yes — schedule daily, write to a versioned dataset, then query the time series per ASIN. **Why not the Amazon Product Advertising API?** That API is gated, requires affiliate approval, and excludes a lot of data. This HTML scraper is simpler and covers more. *** ⭐ **Found this useful? Bookmark this Amazon Bestsellers Scraper** — it's the strongest signal for Apify Store ranking. #### Related actors - [Amazon Reviews Scraper — Sentiment + Pros/Cons](https://apify.com/dltik/amazon-reviews-scraper) — review-level sentiment analysis - [Trustpilot Scraper](https://apify.com/dltik/trustpilot-scraper) — brand reputation + sentiment - [Substack Scraper — Sentiment](https://apify.com/dltik/substack-scraper) — content sentiment analysis License: MIT · Author: [dltik](https://apify.com/dltik) # Actor input Schema ## `categories` (type: `array`): Amazon bestseller category slugs (e.g. 'electronics', 'books', 'fashion', 'kitchen', 'beauty', 'sports', 'toys', 'grocery'). See amazon.com/gp/bestsellers for the full list. ## `marketplace` (type: `string`): Amazon country: com (US), fr (France), de (Germany), co.uk (UK), es (Spain), it (Italy), ca (Canada), co.jp (Japan). ## `maxProductsPerCategory` (type: `integer`): Top N bestsellers per category. Amazon shows 50 per page (2 pages = top 100). ## `proxyConfig` (type: `object`): Optional Residential proxy. Bestsellers pages work without proxy in most cases. Add proxy if you hit rate limits. ## Actor input object example ```json { "categories": [ "electronics" ], "marketplace": "com", "maxProductsPerCategory": 100, "proxyConfig": { "useApifyProxy": false } } ``` # Actor output Schema ## `results` (type: `string`): Bestseller products with rank, ASIN, title, price, rating. # 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 = { "categories": [ "electronics" ] }; // Run the Actor and wait for it to finish const run = await client.actor("dltik/amazon-bestsellers").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 = { "categories": ["electronics"] } # Run the Actor and wait for it to finish run = client.actor("dltik/amazon-bestsellers").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 '{ "categories": [ "electronics" ] }' | apify call dltik/amazon-bestsellers --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dltik/amazon-bestsellers", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Bestsellers Tracker: Top 100 by Category", "description": "Track Amazon's top 100 bestsellers across 8 marketplaces (US, FR, DE, UK, ES, IT, CA, JP). Filter by category and country. Get rank, ASIN, title, price, rating, reviews count, image URL. Daily refresh ready. For Amazon sellers, brands, e-commerce SaaS, product researchers. $2/1K products.", "version": "1.0", "x-build-id": "EcjdtgaoZ5z39Hc51" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dltik~amazon-bestsellers/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dltik-amazon-bestsellers", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/dltik~amazon-bestsellers/runs": { "post": { "operationId": "runs-sync-dltik-amazon-bestsellers", "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/dltik~amazon-bestsellers/run-sync": { "post": { "operationId": "run-sync-dltik-amazon-bestsellers", "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": { "categories": { "title": "Categories", "type": "array", "description": "Amazon bestseller category slugs (e.g. 'electronics', 'books', 'fashion', 'kitchen', 'beauty', 'sports', 'toys', 'grocery'). See amazon.com/gp/bestsellers for the full list.", "items": { "type": "string" }, "default": [] }, "marketplace": { "title": "Amazon marketplace", "enum": [ "com", "fr", "de", "co.uk", "es", "it", "ca", "co.jp" ], "type": "string", "description": "Amazon country: com (US), fr (France), de (Germany), co.uk (UK), es (Spain), it (Italy), ca (Canada), co.jp (Japan).", "default": "com" }, "maxProductsPerCategory": { "title": "Max products per category", "minimum": 1, "maximum": 100, "type": "integer", "description": "Top N bestsellers per category. Amazon shows 50 per page (2 pages = top 100).", "default": 100 }, "proxyConfig": { "title": "Proxy (optional)", "type": "object", "description": "Optional Residential proxy. Bestsellers pages work without proxy in most cases. Add proxy if you hit rate limits.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```