Amazon Product Search Scraper — Full Detail Data

Amazon Product Search Scraper is an Apify Actor for teams, apps, and AI agents that need Amazon product listings from a keyword search or an Amazon search/category URL. It accepts a single search keyword, multiple keywords, or search/category URLs, and returns one dataset record per product. Each record can include search-result fields such as ASIN, title, URL, marketplace, price, rating, review count, rank signals, and sponsored placement, plus detail-page fields such as brand, feature bullets, description, all images, suitable-sellers rank, buybox seller, breadcrumbs, variations, and product details. The output is structured for analysis, routing, and downstream agent workflows, and the actor is usable through Apify MCP.

Best fit and connected workflows

This actor fits workflows that start with Amazon discovery and continue into structured product handling.

Good workflow routes include:

• Keyword discovery for a category, followed by shortlist creation from the returned product records.
• Marketplace-specific monitoring when you already know which Amazon domain you want to search.
• SERP analysis where organicRank, globalPosition, and isSponsored help you read the result order.
• Product research and catalog building when you want search data and detail-page data in one dataset.
• AI agent workflows that need a predictable tool for Amazon product search.

If you already have a filtered Amazon search page or category page, paste the URL into startUrls. If you are starting from a topic, use searchQuery or searchQueries.

Use A natural next workflow step is Amazon Product Details Scraper for focused record-level enrichment. When discovery is complete and the next step is ranking-oriented analysis of selected Amazon records, Amazon Bestsellers Scraper fits that handoff. If the workflow shifts from product discovery to seller research, Amazon Seller Email Scraper - Public Contact Finder continues from the returned product records.

Practical scenario

Maya is preparing a buying brief for "wireless earbuds" in the US marketplace. She starts with searchQuery, keeps enrichDetails enabled, and limits the run with maxResults. The actor returns rows with ASIN, title, price, rating, review count, organic rank, sponsored flag, brand, feature bullets, images, and availability. Maya uses those fields to compare products, then opens the returned product URLs for selected items that need a deeper review.

Input fields

Field	Type	Purpose
searchQuery	string	Single Amazon search keyword. Example: wireless earbuds.
searchQueries	array of strings	Bulk keyword mode. Example: ["gaming mouse", "mechanical keyboard"].
startUrls	array of objects	Amazon search-result or category URLs to scrape directly. Example: { "url": "https://www.amazon.com/s?k=running+shoes" }.
country	string	Marketplace code for keyword searches. Example: US, UK, or DE.
maxResults	integer	Maximum number of products to return across the run. Example: 50.
enrichDetails	boolean	Adds detail-page fields such as brand, bullets, description, images, BSR, buybox seller, breadcrumbs, and variations. Example: true.
sortBy	string	Search sort order for keyword searches. Example: relevance, priceAsc, avgCustomerReview.
includeSponsored	boolean	Includes sponsored placements and flags them with isSponsored. Example: true.
maxSearchPages	integer	Maximum search-result pages to explore per seed. Example: 5.
proxyConfiguration	object	Proxy settings for the run. Default uses Apify Proxy; select UNBLOCKER to route the whole run through it.
useUnblockerFallback	boolean	On by default: after a zero-result classified block, retry at most two unique search seeds through Unblocker once. Set false to use only the selected proxy route.

Focused input example

{
  "searchQuery": "wireless earbuds",
  "country": "US",
  "maxResults": 25,
  "enrichDetails": true,
  "sortBy": "relevance",
  "includeSponsored": true,
  "maxSearchPages": 3
}

Output fields

Each dataset row represents one Amazon product record. The actor writes product rows to the dataset, and the output object also includes execution metadata in the key-value store.

Field	Description	Example
recordType	Dataset record kind.	product
asin	Amazon Standard Identification Number for the returned product.	B0EXAMPLE12
title	Product title from search results or the detail page.	Wireless Earbuds
url	Canonical product URL for the returned ASIN.	https://www.amazon.com/dp/B0EXAMPLE12
marketplace	Marketplace where the row was collected.	US
searchQuery	Search keyword that produced the row.	wireless earbuds
searchUrl	Search or category URL used as the seed.	https://www.amazon.com/s?k=wireless+earbuds
sourceType	Seed type that produced the row, such as keyword or URL-based search.	search
page	Search page number where the product appeared.	1
positionOnPage	Position of the product on that page.	1
organicRank	Organic position in the search results.	1
globalPosition	Overall position across the run.	1
isSponsored	Sponsored placement flag.	false
price	Current price.	39.99
listPrice	Strike-through list price, when available.	49.99
currency	Currency code.	USD
discountPercent	Price discount versus list price.	20
rating	Star rating.	4.6
reviewCount	Number of ratings or reviews.	18234
boughtInPastMonth	Purchase activity text shown by Amazon.	10K+ bought in past month
isPrime	Prime-eligibility flag.	true
thumbnail	Search result thumbnail URL.	https://example.com/thumb.jpg
badgeText	Badge text shown in the listing.	Sponsored
deliveryText	Delivery text from the listing.	FREE delivery Tue, ...
couponText	Coupon text from the listing.	Save 10%
availabilityText	Availability text from the listing.	In Stock
detailScraped	Indicates whether detail-page enrichment was collected.	true
brand	Brand from the detail page.	Example Brand
featureBullets	Feature bullets from the detail page.	["Bluetooth 5.3", "USB-C case"]
description	Product description text.	Wireless earbuds with charging case.
images	Detail-page image URLs.	["https://example.com/image1.jpg"]
imageCount	Number of collected images.	5
breadcrumbs	Category breadcrumb trail.	["Electronics", "Headphones", "Earbud Headphones"]
category	Category text from the product page.	Earbud Headphones
bestSellersRank	BSR entries from the detail page.	[{ "rank": 12, "category": "Earbud Headphones" }]
availability	Availability text from the product page.	In Stock
soldBy	Buybox seller or merchant.	Example Seller
shipsFrom	Shipping origin.	Amazon
brandStoreUrl	Brand store link, when present.	https://www.amazon.com/stores/...
hasAplusContent	Indicates A+ content presence.	true
variations	Variation data such as color or size.	[{ "theme": "Color", "values": ["Black"] }]
productDetails	Key-value technical details from the product page.	{"Connectivity": "Bluetooth"}
scrapedAt	Timestamp for the record.	2026-06-19T00:00:00.000Z
_warnings	Record-level notes captured during collection.	["detail page partial"]

Illustrative output record

{
  "recordType": "product",
  "asin": "B0EXAMPLE12",
  "title": "Wireless Earbuds",
  "url": "https://www.amazon.com/dp/B0EXAMPLE12",
  "marketplace": "US",
  "searchQuery": "wireless earbuds",
  "searchUrl": "https://www.amazon.com/s?k=wireless+earbuds",
  "sourceType": "search",
  "page": 1,
  "positionOnPage": 1,
  "organicRank": 1,
  "globalPosition": 1,
  "isSponsored": false,
  "price": 39.99,
  "listPrice": 49.99,
  "currency": "USD",
  "discountPercent": 20,
  "rating": 4.6,
  "reviewCount": 18234,
  "detailScraped": true,
  "brand": "Example Brand",
  "featureBullets": [
    "Bluetooth connectivity",
    "Charging case included"
  ],
  "description": "Example product description.",
  "images": [
    "https://example.com/image1.jpg",
    "https://example.com/image2.jpg"
  ],
  "breadcrumbs": [
    "Electronics",
    "Headphones",
    "Earbud Headphones"
  ],
  "bestSellersRank": [
    {
      "rank": 12,
      "category": "Earbud Headphones"
    }
  ],
  "availability": "In Stock",
  "soldBy": "Example Seller",
  "shipsFrom": "Amazon",
  "scrapedAt": "2026-06-19T00:00:00.000Z"
}

How it works

The actor uses two phases in one run:

1. Search Amazon by keyword or by Amazon search/category URL.
2. Optionally enrich each product by loading its /dp/ detail page and merging the result into the same row.

The live contract uses a CheerioCrawler with a session pool and proxy handling that prefers residential traffic and falls back to datacenter when needed. The dataset keeps search rank, sponsored placement, pricing signals, and detail-page fields together, which makes it straightforward to sort, filter, and pass downstream.

Handling verified anti-bot blocks

The default route remains the least-cost standard proxy path. When it returns zero products after a retry-exhausted classified 403, 429, 5xx, robot-check, or soft-block response, useUnblockerFallback: true retries at most two unique search seeds once through Apify Unblocker. This protects normal runs from a broad smart-proxy fan-out while giving an isolated blocked run a bounded recovery path. Set it to false if you want to use only the selected proxy route.

For a deliberately full-Unblocker run, select Apify's UNBLOCKER proxy group:

{
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["UNBLOCKER"]
  }
}

Unblocker is not a claim that every Amazon request can be bypassed. It chooses the best country by default and is billed separately by Apify per successful request; check the live proxy pricing for the account before large runs. The actor accepts the valid application/octet-stream HTML response that Unblocker can return, applies a bounded 1–10 second cooldown before retrying an Amazon block or empty page, and exposes only a safe proxyRoute label, fallback counts, and bounded page-category diagnostics in OUTPUT and RUN_SUMMARY.

Pricing

This actor uses Pay per event plus Apify platform usage. Open the live Pricing tab on the actor page for the current charges and the platform usage components.

The event model is based on the work performed:

• actor start
• product found
• product detail enriched, when detail-page enrichment is collected

Example in words: if a run returns twenty products and detail enrichment is enabled for each returned product, the execution includes a product-found event for each product, plus a product-detail-enriched event for each product whose detail page is collected. The live Pricing tab shows the current amounts and the final breakdown.

Use with AI agents (MCP)

This actor is available as an Apify Actor usable through Apify MCP. It lets an agent search Amazon by keyword or Amazon search/category URL and receive structured product records with optional detail-page enrichment.

Precise tool description: search Amazon across the configured marketplace, collect product rows from search results, and enrich those rows with product detail data when enrichDetails is enabled.

Exact Actor identity: khadinakbar/amazon-product-search-scraper

Search Amazon for "wireless earbuds" in the US marketplace, return the first 20 products with detail enrichment enabled, and summarize the results by title, price, rating, review count, organic rank, and brand. Keep sponsored placements in the dataset and mark which rows were enriched.

Output interpretation:

• organicRank shows the organic position.
• globalPosition shows the overall position across the run.
• isSponsored marks ad placements.
• detailScraped shows whether the detail page was collected for the row.
• searchQuery, searchUrl, and marketplace preserve provenance.
• maxSearchPages controls how many search pages are explored per seed.
• maxResults sets the overall product cap and therefore the cost cap.
• When enrichDetails is on, each returned row can include product-page fields from the detail page.

JavaScript Apify API example

import { ApifyClient } from 'apify-client';

const APIFY_TOKEN = process.env.APIFY_TOKEN;

const client = new ApifyClient({
  token: APIFY_TOKEN,
});

const run = await client.actor('khadinakbar/amazon-product-search-scraper').call({
  searchQuery: 'wireless earbuds',
  country: 'US',
  maxResults: 10,
  enrichDetails: true,
});

const dataset = await client.dataset(run.defaultDatasetId).listItems();
console.log(dataset.items);

Best results and outcome guidance

Use searchQuery when you want one topic in one run. Use searchQueries when you want several topics to share one dataset. Use startUrls when you already have a search-result page or category page and want the actor to collect products from that exact source.

For a focused run:

• Align country with the Amazon marketplace you want to analyze.
• Set includeSponsored based on whether you want ad placements in the same dataset.
• Use maxSearchPages to shape how deep the run goes into the result set.
• Keep enrichDetails on when you want brand, bullets, images, BSR, buybox seller, breadcrumbs, and variations.
• Lower maxResults when you want a smaller, tighter product set.

Continue the workflow

• Then use 🛒 Amazon Reviews Scraper — Ratings & Sentiment to continue from Amazon Product Search Scraper — Full Detail Data discovery into engagement data for the selected records.
• Then use Amazon Search Scraper to extend Amazon Product Search Scraper — Full Detail Data research with a complementary discovery contract.

Design note

I found that the output contract always requires recordType, asin, and scrapedAt, which gives every row a stable identity and timestamp even when other fields are empty.

FAQ

Can I start from a keyword and a marketplace at the same time?

Yes. Use searchQuery or searchQueries together with country to choose the marketplace for keyword searches.

Can I paste an Amazon search page URL?

Yes. startUrls accepts Amazon search-result and category URLs, and the marketplace is read from each URL's domain.

What records end up in the dataset?

One record per returned product. The dataset is centered on recordType: "product" with one row per ASIN.

How do I connect discovery to deeper product research?

Use this actor first to discover products, then route selected records into a downstream actor such as Amazon Product Details Scraper.

How can I keep search runs focused?

Use maxResults to cap the total number of products and maxSearchPages to limit how deep each seed is explored.

Responsible use

Use this actor for public Amazon search and product-page data in a way that follows applicable laws, Amazon's terms, and your own data-handling obligations. Review how you store, transform, and republish scraped content, especially when product descriptions, images, or seller data are involved.