Amazon Seller Data Extractor

Amazon Seller Data Extractor — Contacts, Ratings and Reviews

Amazon Seller Data Extractor pulls public Amazon seller profiles from product codes (ASINs), seller IDs, seller links or keywords: business name and address, phone and email, star rating, positive percentage, 30-day to lifetime rating counts, recent reviews, return policy and FBA or FBM fulfillment, plus each seller's storefront products. Every response is structured JSON — ready to pass directly to an LLM, index into a vector store, or feed a lead generation pipeline. No Amazon account or cookies needed. Start with one keyword, then map every seller in your category.

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What data can I extract with Amazon Seller Data Extractor?

Using this Amazon Seller API, you will be able to extract the following Amazon seller data:

🏬 Seller name	🆔 Seller ID	🏢 Business name	📍 Business address (split into street, city, state, postal code, country)
📞 Contact phone (if listed)	✉️ Contact email (if listed)	⭐ Star rating	👍 Positive rating % (12 months)
📅 Ratings in the last 30 days	🗓️ Ratings in the last 90 days	📆 Ratings in the last 12 months	🔢 Lifetime ratings
📊 Share of ratings per star level	💬 Recent reviews with stars, text and date	↩️ Return and refund policy	🚚 Shipping policy
🔒 Privacy texts	📝 About the seller	📦 Fulfillment type (FBA or FBM)	🌍 Marketplace country
🛒 Storefront link	🏷️ Storefront products (ASIN, title)	💵 Product price and currency	🌟 Product rating and review count
🔗 Seller and product links	🎯 Input each row came from	⚠️ Reason an input gave no seller	🕒 Time scraped

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How to use Amazon Seller Data Extractor

Built for sales teams, brand protection analysts and Amazon agencies: one run turns product codes, seller IDs or a keyword into a table of Amazon sellers with their contacts, ratings and reviews.

Copy to your AI assistant:

`amazon-seller-data-extractor` (Apify Actor ID: fastdataapi/amazon-seller-data-extractor, https://apify.com/fastdataapi/amazon-seller-data-extractor) is an Apify Actor that returns public Amazon seller profiles as structured JSON: seller name and ID, business name and address, contact phone and email, star rating, positive rating percentage, rating counts for 30 days, 90 days, 12 months and lifetime, recent reviews, return policy, fulfillment type (FBA or FBM), and optionally each seller's storefront products with price and rating. Use it whenever someone needs Amazon seller data without cookies, a login, or a browser - finding contact details of the sellers behind a list of ASINs, prospecting new sellers in a product category, or checking who sells your brand and how well they are rated. Run it with curl: curl -X POST "https://api.apify.com/v2/acts/amazon-seller-data-extractor/run-sync-get-dataset-items?token=APIFY_TOKEN" -H "Content-Type: application/json" -d '{"asinInputs":["B00P8XQPY4"],"keywordInputs":["coffee grinder"],"maxComments":10}'. Or in Python: ApifyClient("APIFY_TOKEN").actor("amazon-seller-data-extractor").call(run_input={"usernameInputs": ["AECXT73EGS1XW"], "includeProducts": True, "maxProductsPerSeller": 20}) then client.dataset(run["defaultDatasetId"]).list_items().items. Inputs: asinInputs (array of strings, product codes or product links; the seller of the current offer is scraped), usernameInputs (array of strings, seller IDs such as A33W53J5GVPZ8K), keywordInputs (array of strings; the first results page, about 20 products, is checked and their third-party sellers scraped), categoryUrls (array of strings, Amazon search or category links, used like keywords), startUrls (array of strings, seller page links), includeProducts (boolean, add storefront product rows, default false), maxProductsPerSeller (integer 0-500, 0 = all up to 20 storefront pages, default 20), maxFeedbackPages (integer 1-50, review pages per seller, about 5 reviews each, default 1), maxComments (integer 0-1000, reviews kept per seller, 0 = all read, default 10), sortOrder (string, "recent" | "helpful" | "rating", default "recent"), minRatingPositive (integer 0-100, skip sellers below this positive %, default 0), minLifetimeRatings (integer 0-1000000, skip sellers with fewer lifetime ratings, default 0), fulfillmentType (string, "any" | "FBA" | "FBM", default "any"; known only for sellers found through a product, keyword or category), amazonDomain (string, marketplace such as amazon.com or amazon.de, default "amazon.com"), language (string, page language such as de-DE, default empty), proxyCountry (string, two-letter connection country or "AUTO" for the marketplace's country, default "AUTO"), maxConcurrency (integer 1-20, pages loaded at once, default 10), proxyConfiguration (object, optional own proxy; default is Apify residential proxy in the marketplace's country). Rows have type "seller" (one per seller per run, charged as the row_result event), "product" (one per storefront product, charged as row_result) or "error" (an input that gave no seller, with the reason in error; not charged). Sellers skipped by the filters are not saved and not charged. Full input schema, every enum and default, and the complete output field list: GET https://api.apify.com/v2/acts/amazon-seller-data-extractor/builds/default

Amazon Seller Data Extractor MCP Server: use these Actors from ChatGPT, Claude or Cursor

Point your AI assistant at Apify and it can read Amazon on its own: sellers by product code, seller ID or keyword, with their contacts, ratings, reviews and storefront products. No glue code, no scraping logic in your prompts.

$claude mcp add --transport http apify "https://mcp.apify.com?tools=fastdataapi/amazon-seller-data-extractor"

Step by step

1. Create a free Apify account.
2. Open Amazon Seller Data Extractor in the Apify Store.
3. Enter Amazon product codes (ASINs), seller IDs, seller links or keywords, and pick the marketplace.
4. Click Start (or send your API request).
5. Download or stream your results in JSON, CSV or Excel.

How to scale Amazon Seller Data Extractor to bulk

Put any number of ASINs, seller IDs, seller links, keywords and category links in one run; all of them run at the same time, and every seller is saved as soon as it is loaded. A seller reached from several inputs is saved once. A recorded run with one ASIN, one seller ID, two seller links and one keyword returned 16 sellers and 73 storefront products in 26.3 seconds. To build an Amazon seller list for a whole category, add every related keyword, then export Amazon sellers to CSV or Excel when the run ends. To watch the same sellers over time, schedule the run daily or weekly in Apify Console.

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✨ Features

Amazon Seller Data Extractor fetches clean, structured seller profiles from Amazon ⚡. It's ideal for Amazon seller lead lists, brand protection, supplier research and marketplace analysis — an Amazon seller scraper, Amazon seller contact scraper, Amazon seller feedback scraper and Amazon storefront scraper in one, across 20 Amazon marketplaces. It extracts, per seller:

• Contact details – the seller's listed phone number, an email found in its details, business name and business address
• Rating counts – ratings in the last 30 days, 90 days, 12 months and lifetime
• Reputation – star rating, positive rating percentage and the share of ratings per star level
• Reviews – recent reviews with stars, text and date, newest first, highest stars first or in Amazon's order
• Policies – return and refund policy, shipping policy and privacy texts
• Fulfillment – FBA or FBM, read from the product offer the seller was found through
• Storefront products – ASIN, title, price, currency, rating and review count for each product, when turned on

⚡ Keyword searches check the whole first results page at once, and sellers that fail your rating or fulfillment filters are skipped without being charged.

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Use cases 💡

• Sales rep — collect phone numbers and business addresses of sellers in a product category.
• Brand protection analyst — list every seller behind your ASINs with their rating counts.
• Amazon agency — find FBM sellers with few lifetime ratings and pitch them your services.
• Sourcing manager — compare return policies and positive ratings of competing suppliers.
• AI engineer — index seller reviews and policies into a RAG store for marketplace questions.

Building an AI agent? Connect Amazon Seller Data Extractor over MCP and let it call the actor on its own.

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Why choose this actor?

1. Sellers from a keyword in seconds. A recorded run turned one ASIN, one seller ID, two seller links and the keyword "coffee grinder" into 16 sellers and 73 storefront products in 26.3 seconds.
2. The numbers behind each seller. A recorded seller came back with 25,768 lifetime ratings, 447 in the last 30 days, 99% positive, a listed phone number, a business address in Lavergne, TN and three return policy paragraphs.
3. Five ways in, three filters. ASINs, seller IDs, seller links, keywords and category links mix in one run, filtered by positive rating, lifetime ratings and FBA or FBM, with 42 fields for every seller.

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⬇️ Input

Enter at least one ASIN, seller ID, seller link, keyword or search / category link; every list is optional on its own, and you can mix them.

Parameter	Required	Type	Description	Example value
asinInputs	No	array	Amazon product codes or product links. The seller of the product's current offer is scraped, with its fulfillment type. Products sold only by Amazon get an error row.	["B00P8XQPY4"]
usernameInputs	No	array	Amazon seller IDs (the value after seller= in a seller link); seller links also work.	["A33W53J5GVPZ8K"]
keywordInputs	No	array	Search phrases. The first results page (about 20 products) is checked and their third-party sellers are scraped.	["coffee grinder"]
categoryUrls	No	array	Amazon search or category links, used like keywords.	["https://www.amazon.com/s?k=coffee+grinder"]
startUrls	No	array	Seller page links (/sp?seller=…); storefront and product links also work. The marketplace is taken from each link.	["https://www.amazon.com/sp?seller=AECXT73EGS1XW"]
includeProducts	No	boolean	Add each seller's storefront products as separate rows. Default false.	true
maxProductsPerSeller	No	integer	Product rows per seller, 0–500; 0 = every product, up to 20 storefront pages. Default 20. Free plan: up to 20 rows per run (all sellers and products together) and 200 per month; paid plans have no limit.	5
maxFeedbackPages	No	integer	Review pages read per seller, 1–50 (about 5 reviews per page). Default 1.	2
maxComments	No	integer	Reviews kept per seller, 0–1000; 0 = all reviews read. Default 10.	10
sortOrder	No	string	Review order: recent (newest first), helpful (Amazon's order) or rating (highest stars first). Default recent.	"recent"
minRatingPositive	No	integer	Skip sellers below this positive rating %, 0–100. Default 0 (no filter).	90
minLifetimeRatings	No	integer	Skip sellers with fewer lifetime ratings, 0–1,000,000. Default 0 (no filter).	100
fulfillmentType	No	string	any, FBA or FBM. Known only for sellers found through an ASIN, keyword or category; sellers entered by ID or link are skipped when FBA or FBM is chosen. Default any.	"any"
amazonDomain	No	string	Marketplace for ASINs, seller IDs and keywords, such as amazon.com, amazon.co.uk, amazon.de. Default amazon.com.	"amazon.com"
language	No	string	Page language such as en-US or de-DE. Default empty (the marketplace's default).	"en-US"
proxyCountry	No	string	Two-letter connection country, or AUTO for the marketplace's own country. Default AUTO.	"AUTO"
maxConcurrency	No	integer	Pages loaded at the same time, 1–20. Default 10.	10
proxyConfiguration	No	object	Optional. By default the actor uses Apify residential proxy in the marketplace's country; a proxy you select is used instead.	{"useApifyProxy": false}

Accepted link formats: seller pages (https://www.amazon.com/sp?seller=A33W53J5GVPZ8K), storefronts (https://www.amazon.com/s?me=A33W53J5GVPZ8K), product pages (https://www.amazon.com/dp/B00P8XQPY4) and search or category pages (https://www.amazon.de/s?k=kaffeemühle).

Free plan limits

Free plan: up to 20 rows per run (all sellers and products together) and 200 per month; paid plans have no limit.

Example input

{
  "asinInputs": ["B00P8XQPY4"],
  "usernameInputs": ["A33W53J5GVPZ8K"],
  "keywordInputs": ["coffee grinder"],
  "categoryUrls": [],
  "startUrls": ["https://www.amazon.com/sp?seller=AECXT73EGS1XW"],
  "includeProducts": true,
  "maxProductsPerSeller": 5,
  "maxFeedbackPages": 2,
  "maxComments": 10,
  "sortOrder": "recent",
  "minRatingPositive": 0,
  "minLifetimeRatings": 0,
  "fulfillmentType": "any",
  "amazonDomain": "amazon.com",
  "language": "",
  "proxyCountry": "AUTO",
  "maxConcurrency": 10,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

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⬆️ Output

Every seller is one typed, normalized JSON item with the same 42 fields on every run; values a seller does not publish are empty or null. Product rows (when turned on) and error rows for inputs that gave no seller sit in the same dataset, which you can export as JSON (default), CSV or Excel.

Example output

A recorded seller (description and privacy texts shortened, two of ten reviews shown), one of its storefront products, and the row for a seller ID that does not exist:

[
  {
    "section_index": 4,
    "section": "https://www.amazon.com/sp?ie=UTF8&seller=AECXT73EGS1XW",
    "type": "seller",
    "isChild": false,
    "url": "https://www.amazon.com/sp?ie=UTF8&seller=AECXT73EGS1XW",
    "canonicalSellerUrl": "https://www.amazon.com/sp?seller=AECXT73EGS1XW",
    "sellerId": "AECXT73EGS1XW",
    "sellerName": "HiTouch Business Services a BU of Staples",
    "seller_id": "AECXT73EGS1XW",
    "seller_name": "HiTouch Business Services a BU of Staples",
    "description": "HiTouch Business Services is one of the largest office products dealers in the nation…",
    "detailed_info": [
      {"title": "Business Name", "value": "Staples, Inc."},
      {"title": "Business Address", "value": "601 Mason Drive, Suite 100, Lavergne, TN, 37086, US"}
    ],
    "businessName": "Staples, Inc.",
    "businessAddress": {
      "raw": "601 Mason Drive, Suite 100, Lavergne, TN, 37086, US",
      "line1": "601 Mason Drive",
      "city": "Lavergne",
      "state": "TN",
      "postalCode": "37086",
      "country": "US"
    },
    "contactPhone": "866-944-8269",
    "contactEmail": null,
    "seller_phone_number": "866-944-8269",
    "feedbacks": [
      {"stars": "5 out of 5 stars", "starsNumeric": 5.0, "text": "Prompt service", "date": "By Nancy K. Vogel on October 13, 2026."},
      {"stars": "5 out of 5 stars", "starsNumeric": 5.0, "text": "Quality product, price is right. Box was pretty hammered when it arrived but was on time.", "date": "By Happy buyer on October 13, 2026."}
    ],
    "feedbackCount": 10,
    "stars": "5 out of 5 stars",
    "ratingStarsNumeric": 5.0,
    "rating_positive": "99% positive",
    "ratingPositivePercent": 99,
    "return_policy": [
      "To get information about the Return and Refund policies that may apply, please refer to Amazon’s Return and Refund policy.",
      "To initiate a return, visit Amazon's Online Return Center to request a return authorization from the seller.",
      "For any issues with your return, if the product was shipped by the seller, you can get help here ."
    ],
    "shipping_policies": "",
    "privacy_security": "Amazon knows that you care how information about you is used and shared…",
    "privacy_policy": "HiTouch Business Services a BU of Staples values the privacy of your personal data.",
    "help_content": "For questions about a charge that has been made to your credit card, please contact Amazon . Questions about how to place an order? Search Amazon Help .",
    "products_link": "https://www.amazon.com/s?ie=UTF8&me=AECXT73EGS1XW",
    "feedbacks_percentages": {"star_5": "86%", "star_4": "6%", "star_3": "1%", "star_2": "1%", "star_1": "6%"},
    "ratingCountM1": 447,
    "ratingCountM3": 1465,
    "ratingCountM12": 6007,
    "rating_count_m1": 447,
    "rating_count_m3": 1465,
    "rating_count_m12": 6007,
    "rating_count_lifetime": 25768,
    "productCount": 5,
    "fulfillment": null,
    "country": "US",
    "timestamp": "2026-10-13T06:54:05.923809Z",
    "scrapedAt": "2026-10-13T06:54:05.923809Z"
  },
  {
    "type": "product",
    "isChild": true,
    "section_index": 4,
    "section": "https://www.amazon.com/sp?ie=UTF8&seller=AECXT73EGS1XW",
    "parentSellerId": "AECXT73EGS1XW",
    "parentSellerName": "HiTouch Business Services a BU of Staples",
    "asin": "B00006JPHI",
    "title": "Duracell N 1.5V Alkaline Battery, 2 Count Pack, N 1.5 Volt Battery, Long-Lasting for Key Fobs, GPS Trackers, and More",
    "price": 5.99,
    "priceRaw": "$5.99",
    "currency": "USD",
    "rating": 4.7,
    "reviewCount": 113,
    "url": "https://www.amazon.com/Duracell-Coppertop-Alkaline-Medical-Battery/dp/B00006JPHI",
    "scrapedAt": "2026-10-13T06:54:14.381136Z"
  },
  {
    "section_index": 4,
    "section": "AZZZZZZZZZZZZ9",
    "type": "error",
    "isChild": false,
    "url": "https://www.amazon.com/sp?seller=AZZZZZZZZZZZZ9",
    "sellerId": "AZZZZZZZZZZZZ9",
    "asin": null,
    "error": "Amazon has no seller page for AZZZZZZZZZZZZ9 on amazon.com",
    "scrapedAt": "2026-10-13T06:44:48.475373Z"
  }
]

The input column holds the ASIN, seller ID or link the row came from; keywords appear as keyword:<phrase> and category links as category:<link>. The fulfillment type is empty for sellers entered by ID or link, because it is read from a product offer. Rows of type error are not charged.

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How does it work?

The actor opens Amazon the way a regular shopper does, through Apify residential proxies in the marketplace's own country, and handles Amazon's access checks automatically. For a product code it reads the product page to find the seller of the current offer and how it ships; for a keyword it checks every product on the first results page at once. It then reads each seller's public profile, extra review pages and storefront when you ask for them. When Amazon refuses a page, the actor pauses, switches to a fresh connection and tries again. It returns only publicly visible data — what any visitor sees without logging in — and the output fields stay the same from run to run, so your code and spreadsheets keep working when Amazon changes its pages.

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How do you integrate Amazon Seller Data Extractor into your stack?

It works with what you already use: the REST API from any language, MCP for AI agents, and no-code tools.

Using Amazon Seller Data Extractor with the Apify API

import requests

response = requests.post(
    "https://api.apify.com/v2/acts/amazon-seller-data-extractor/run-sync-get-dataset-items",
    params={"token": "APIFY_TOKEN"},
    json={"keywordInputs": ["coffee grinder"], "maxComments": 5},
)
for row in response.json():
    if row["type"] == "seller":
        print(row["sellerName"], row["ratingPositivePercent"], row["contactPhone"])

Works in Go, Ruby, Node.js, cURL — any language that can make an HTTP request.

MCP integration for AI agents

Add the Apify MCP server to your AI client with one command:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=fastdataapi/amazon-seller-data-extractor"

This registers Amazon Seller Data Extractor as a tool your agent can call directly: the agent finds it through the server's search, adds it and runs it, then reads the sellers back as JSON. Ask for "the sellers of these five ASINs with their phone numbers" and it does the rest. It works in Claude Code, Cursor and Windsurf.

No-code tools (n8n, Make, LangChain)

n8n: add the Apify node and choose "Run an Actor", or use the HTTP Request node pointed at the run-sync endpoint with your token. Send each new seller to a Google Sheet or your CRM in the next node.

Make: use the Apify app's "Run an Actor" module, then "Get Dataset Items" to pull the sellers into the rest of your scenario.

LangChain: install langchain-apify and wrap the actor with ApifyActorsTool("amazon-seller-data-extractor") so your agent can look up Amazon sellers by product code or keyword.

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Is it legal to scrape Amazon data?

Collecting public Amazon seller pages is generally lawful: Amazon shows these seller profiles to every shopper so buyers know who they are buying from. This actor returns only publicly available data — what any visitor sees without logging in: seller names, business details Amazon requires sellers to display, ratings, reviews, policies and product listings. GDPR: scraping public data is generally permissible, but storing and using it must comply with local data-protection law. Consult legal counsel if your use case involves bulk storage of personal data.

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Frequently asked questions

What fields does Amazon Seller Data Extractor return?

It returns each seller's name, business name and address, contact phone and email, positive rating percentage and rating counts for 30 days, 90 days, 12 months and lifetime, plus reviews, return policy and fulfillment type. See the data fields section for the full list.

Does Amazon Seller Data Extractor require an Amazon account or login?

No. Only public Amazon seller data is extracted, and no credentials are needed.

How fast does Amazon Seller Data Extractor run?

A recorded run returned 16 sellers and 73 storefront products in 26.3 seconds from one ASIN, one seller ID, two seller links and one keyword. A keyword on amazon.de returned 8 sellers with 3 products each in about 25 seconds. Every run reads live data, not a cache.

What happens if a seller or product doesn't exist?

You get one free row of type error with the input and a reason, such as "Amazon has no seller page for this ID" or "this product has no third-party seller right now" for products sold only by Amazon. In code, keep rows where the type is seller or product. Sellers that hide details still return a full row, with those values empty or null.

Can I scrape multiple Amazon sellers at once?

Yes. Put any number of ASINs, seller IDs, seller links, keywords and category links in one run; they all run at the same time, and each seller is saved once even when several inputs lead to it.

Does Amazon Seller Data Extractor work with Claude, ChatGPT, and other AI agent tools?

Yes — Amazon Seller Data Extractor is available as an MCP tool. Register it in Claude Code, Cursor or Windsurf with claude mcp add --transport http apify "https://mcp.apify.com?tools=fastdataapi/amazon-seller-data-extractor". Any agent that can call an HTTP endpoint can use the REST API directly.

Does Amazon Seller Data Extractor return data in a format LLMs can use directly?

Yes. Each seller is typed, normalized JSON with consistent field names, so there is no HTML parsing and no selectors. Pass it straight to an LLM, index it into a vector store, or feed it to an agent tool — no transformation step.

What happens when Amazon changes its layout or updates its anti-bot system?

The actor is maintained, and when Amazon changes, it is updated so your calls keep returning the same JSON fields with no changes on your end.

Can I use Amazon Seller Data Extractor without managing proxies or browser infrastructure?

Yes. Residential proxies in the right country, Amazon's access checks, pauses and retries all run on the actor's side. You send one request and get structured JSON back, with no proxy accounts, no headless browser setup and no maintenance.

Which Amazon seller fields work best for AI training data and RAG indexing?

For RAG, use the review texts, the seller's description and its return and shipping policies. For training data and analytics, use the star rating, positive rating percentage, the 30-day to lifetime rating counts and product prices. All fields are plain strings, numbers, booleans and short lists, so no normalization is needed.

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Your feedback

Found a bug or missing a field? Let us know in the actor's Issues tab. Every report is read, and fixes ship as new versions of the actor.