Amazon Product & Best Sellers Scraper

Track where products rank for a keyword, watch competitors' prices and sponsored slots, or pull Best Sellers for product research. Give it search terms, Best Sellers categories, ASINs or Amazon links and it returns JSON rows from 21 Amazon stores. Search rows carry position, sponsored flag, ASIN, title, price, list price, rating, rating count, badges and "bought in past month" at $0.54 per 1,000. Best Sellers, New Releases and Movers & Shakers rows carry rank, price and rating for all 100 ranks; product rows per ASIN carry the Buy Box price and seller, ships-from, delivery promise, the star split and every other offer. You pay only for the rows you get.

$0.54 per 1,000 search results

Why this actor

• About half the price per search row. $0.54 per 1,000 against $1 at apt_marble and santamaria-automations, the two most used Amazon search actors, and $2 at khadinakbar (free plan, Apify Store, 2026-10-31). 51 of our 51 runs since 2026-10-22 succeeded (scheduled and test runs, Apify run history).
• 21 stores, Best Sellers and Buy Box in one actor. Search, Best Sellers / New Releases / Movers & Shakers ranks and Buy Box + offers per ASIN, with local prices and sellers: non-US stores are read from an IP in their own country (US, DE and JP are checked every day).
• No login, no Amazon account, no customer reviews or reviewer names. Unknown ASINs, bad URLs and temporary blocks come back as free error rows with a code.

Drop-in input

Drop-in input. Input written for apt_marble/amazon-search-results-scraper (keywords, maxResultsPerKeyword, sortBy, excludeSponsored, marketplace: "us"), santamaria-automations/amazon-search-scraper (searchQueries, country, maxResultsPerQuery, maxPages, minStars), khadinakbar/amazon-product-search-scraper (searchQuery, maxResults, maxSearchPages) or junglee/Amazon-crawler (categoryOrProductUrls, maxItemsPerStartUrl) works as it is.

As stated in the actor’s README. The full list of accepted input names is on the Store page.

Switching from another actor

• From Amazon Search Results Scraper apt_marble/amazon-search-results-scraper, 8 input fields work as they are

What you get

A product row:

Sample row (from the README example; long text shortened, lists cut to two items):

{
  "rowType": "searchResult",
  "marketplace": "US",
  "domain": "amazon.com",
  "currency": "USD",
  "searchTerm": "wireless earbuds",
  "page": 1,
  "position": 2,
  "organicPosition": null,
  "asin": "B0C1BTXM9W",
  "sponsored": true,
  "title": "Wireless Earbuds, Bluetooth 5.4 Ear Buds LED Power Display Headphones Bass Stereo ...",
  "url": "https://www.amazon.com/dp/B0C1BTXM9W",
  "imageUrl": "https://m.media-amazon.com/images/I/614gb9uXQuL.jpg",
  "price": 19.99,
  "priceText": "$19.99",
  "listPrice": 28.49,
  "listPriceText": "$28.49",
  "rating": 4.3,
  "ratingCount": 14589,
  "badges": [],
  "boughtPastMonth": 6000,
  "boughtPastMonthText": "6K+ bought in past month",
  "deliveryText": "Join Prime to get FREE delivery Tomorrow, Oct 23",
  "scrapedAt": "2026-10-22T08:00:00.000Z"
}

Price

Live Apify price on 2026-11-01, per 1,000 rows, by Apify plan. You pay only for rows delivered; error and summary rows marked free in the README cost nothing. Plus $0.001 per GB of memory when a run starts.

Use cases

• Price and Buy Box monitoring: who holds the Buy Box for your ASINs, at what price, and which sellers undercut it, on a daily schedule.
• Keyword and shelf research: where your product and your rivals rank for a search, organic and sponsored, with "bought in past month".
• Category trends: Best Sellers, New Releases and Movers & Shakers per category and store, all 100 ranks.
• Cross-border pricing: the same ASIN on amazon.com, .co.uk, .de and .co.jp in local currency.
• Agents: "find the top-rated products for X under $50 and tell me who sells them".

Run it from code or an AI agent

Actor ID arcadium/amazon-products. Set APIFY_TOKEN to your Apify API token. The input below is the actor’s prefilled example; see the guide for every field.

curl -X POST "https://api.apify.com/v2/acts/arcadium~amazon-products/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searches":["wireless earbuds"],"categories":[],"asins":[],"urls":[],"marketplace":"US","maxResultsPerSearch":20,"includeSponsored":true}'

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('arcadium/amazon-products').call({
  "searches": [
    "wireless earbuds"
  ],
  "categories": [],
  "asins": [],
  "urls": [],
  "marketplace": "US",
  "maxResultsPerSearch": 20,
  "includeSponsored": true
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

# pip install apify-client
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/amazon-products").call(run_input={
    "searches": ["wireless earbuds"],
    "categories": [],
    "asins": [],
    "urls": [],
    "marketplace": "US",
    "maxResultsPerSearch": 20,
    "includeSponsored": True,
})
items = client.dataset(run.default_dataset_id).list_items().items  # apify-client 3.x returns a Run object
print(items)

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=arcadium/amazon-products",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>"
      }
    }
  }
}

# pip install langchain-apify   (reads APIFY_API_TOKEN from the environment)
from langchain_apify import ApifyActorsTool

tool = ApifyActorsTool("arcadium/amazon-products")
rows = tool.invoke({"run_input": {
    "searches": ["wireless earbuds"],
    "categories": [],
    "asins": [],
    "urls": [],
    "marketplace": "US",
    "maxResultsPerSearch": 20,
    "includeSponsored": True,
}})
# or give `tool` to an agent: create_react_agent(llm, [tool])

# pip install llama-index-readers-apify
import os
from llama_index.core import Document, VectorStoreIndex
from llama_index.readers.apify import ApifyActor

reader = ApifyActor(os.environ["APIFY_TOKEN"])
documents = reader.load_data(
    actor_id="arcadium/amazon-products",
    run_input={
        "searches": ["wireless earbuds"],
        "categories": [],
        "asins": [],
        "urls": [],
        "marketplace": "US",
        "maxResultsPerSearch": 20,
        "includeSponsored": True,
    },
    dataset_mapping_function=lambda item: Document(text=str(item.get("title") or ""), metadata={"url": item.get("url")}),
)
index = VectorStoreIndex.from_documents(documents)

# pip install crewai crewai-tools langchain-apify   (reads APIFY_API_TOKEN from the environment)
from crewai import Agent
from crewai_tools import ApifyActorsTool

tool = ApifyActorsTool(actor_name="arcadium/amazon-products")
researcher = Agent(
    role="Research analyst",
    goal="Answer with data collected by the tool",
    backstory="Uses public web data.",
    tools=[tool],
)

{
  "nodes": [
    {
      "name": "Run arcadium/amazon-products",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [
        0,
        0
      ],
      "parameters": {
        "method": "POST",
        "url": "https://api.apify.com/v2/acts/arcadium~amazon-products/run-sync-get-dataset-items",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"searches\":[\"wireless earbuds\"],\"categories\":[],\"asins\":[],\"urls\":[],\"marketplace\":\"US\",\"maxResultsPerSearch\":20,\"includeSponsored\":true}",
        "options": {
          "timeout": 300000
        }
      }
    }
  ],
  "connections": {}
}

// Extensions > Apps Script. Store your token once: Project Settings > Script properties > APIFY_TOKEN.
function importLastRun() {
  const token = PropertiesService.getScriptProperties().getProperty('APIFY_TOKEN');
  const url = 'https://api.apify.com/v2/acts/arcadium~amazon-products/runs/last/dataset/items?status=SUCCEEDED&clean=true&format=json';
  const res = UrlFetchApp.fetch(url, { headers: { Authorization: 'Bearer ' + token } });
  const rows = JSON.parse(res.getContentText());
  if (!rows.length) return;
  const keys = Object.keys(rows[0]);
  const values = rows.map((r) => keys.map((k) => (typeof r[k] === 'object' ? JSON.stringify(r[k]) : r[k])));
  const sheet = SpreadsheetApp.getActiveSheet();
  sheet.clearContents();
  sheet.getRange(1, 1, 1, keys.length).setValues([keys]);
  sheet.getRange(2, 1, values.length, keys.length).setValues(values);
}

Tutorials

• Track Amazon Best Sellers ranks with Python

Limitations

• Search, ranked lists and the light product row only. The full product page (bullets, brand, BSR, variations, dimensions) is not part of this actor.
• Customer reviews are not collected: Amazon shows them only to signed-in visitors, and we never sign in.
• Delivery and prices are those of a shopper in the store's country without a postcode; a specific postcode needs a sign-in, so it is not supported.
• Search results follow Amazon's own ranking and personalisation for a logged-out visitor; ads and positions move during the day.
• Amazon answers some requests with a captcha or a "Something went wrong" page. The actor retries those on a new IP; inputs that still fail come back as free blocked or unavailable rows.

FAQ

Why do non-US stores cost the same but run a little slower? They are read from an IP in their own country, so prices, sellers and delivery are the local ones (a US IP sees export prices). Those IPs are slower than our datacenter IPs.

A category returned nothing. Why? Look at its error row: not_found means the category path does not exist on that store (paths differ per store, e.g. ce-de on amazon.de); no_match means Amazon shows the list as empty right now (Movers & Shakers is often empty, at times in every category of a store); unavailable means the page could not be read. These rows are free.

How fast is it? Search: about 50 results per second. Ranked lists: 50 ranks in about two seconds. Product rows: about two per second.

Something looks wrong in the output. Who do I tell? Open an issue on the actor page with the run link. We read them all.

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