Amazon Product Scraper — Price, Rating, Seller & ASIN Data

🛒 Amazon Product Scraper – Price, Rating, Seller & ASIN Data Extraction

The Amazon Product Scraper turns any list of Amazon product URLs or bare ASINs into clean, structured JSON containing price, rating, review count, seller identity, availability, images, bullet features and full product specifications. Point it at a handful of listings or a batch of thousands, and it returns one flat record per product that drops straight into a spreadsheet, a pricing database, or a BI dashboard.

This Amazon scraper is built for people who need reliable retail data rather than screenshots: e-commerce analysts tracking competitor pricing, brand managers policing MAP violations, dropshippers validating margins, and market researchers mapping a category before they commit inventory. It fetches product detail pages directly over HTTP with rotated TLS fingerprints, parses them with a fast HTML engine, and never depends on a headless browser — so runs stay lightweight and predictable.

Every field in the output comes from the live product detail page. Nothing is estimated, enriched, or filled in from a cached third-party catalogue.

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📊 What Data Can You Extract with This Amazon Product Scraper?

The Amazon Product Scraper returns a single record per product URL, covering identity, commercial terms, social proof and full merchandising content.

Category	Fields	What it gives you
🆔 Product identity	url, asin, title	Canonical listing URL, the 10-character ASIN, and the full product title as rendered on the page
💰 Pricing	price, priceText, currency	Numeric price ready for arithmetic, the price exactly as displayed, and the currency symbol/code
⭐ Ratings & reviews	rating, ratingText, reviewCount, reviewCountText, topReviews	Average star score, raw rating string, total review volume, and the top customer reviews shown on the page
📦 Availability & seller	availability, soldBy, shipsFrom, condition, bylineText	Stock status, the merchant of record, the fulfilment origin, item condition, and the brand byline link text
🖼️ Media & marketing copy	imageUrls, features, description, aboutProduct, importantInformation	All gallery image URLs, the bullet feature list, long-form description, structured attribute pairs, and safety/compliance notes
🗂️ Taxonomy & variants	breadcrumbs, productDetails, variationAsins, variationDimensions	Category path with links, the specification table, sibling ASINs for other variants, and the dimensions those variants vary along
🔎 Run metadata	statusMessage, errorMessage, scrapedAt	Per-record outcome, failure reason if any, and the exact scrape timestamp

The genuinely underrated field here is variationAsins. A single parent listing often hides dozens of child ASINs across sizes and colours, each with its own price and stock position. Capturing them means you can expand one seed URL into a complete variant map instead of tracking only the default child Amazon happens to show you.

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🌟 Key Features of the Amazon Product Scraper

Feature	Description
🔗 URL or ASIN input	Accepts full https://www.amazon.com/dp/ASIN links or bare 10-character ASINs in the same startUrls list, so you never have to reformat an existing product sheet
🔄 Automatic proxy rotation	Proxy sessions rotate behind the scenes on every retry — no proxy configuration, credentials, or IP pool management on your side
🧬 Rotating TLS fingerprints	Each retry attempt uses a fresh browser TLS fingerprint and a randomised delay, which keeps request patterns from looking mechanical
⚙️ Tunable concurrency	maxConcurrency controls how many product pages are fetched in parallel, letting you trade throughput against a gentler request rate
🔁 Configurable retries	maxRetries sets how many attempts each product URL gets before the scraper gives up on it, with each attempt using a new session
🐤 Canary diagnostic mode	canaryMode scrapes only the first URL and logs HTTP status and response length per attempt — a 30-second sanity check that selectors still work
🚫 Explicit not-found records	With includeNotFound enabled (the default), dead or 404 listings return a record with statusMessage: "NOT_FOUND" rather than vanishing from the dataset
⚡ No headless browser	Pages are fetched over plain HTTP and parsed with a fast C-backed HTML parser, so memory use stays low and runs finish without Chromium overhead
🧾 Deep specification capture	productDetails, aboutProduct and importantInformation preserve Amazon's structured attribute tables instead of flattening them into free text

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🚀 Why Choose This Amazon Product Scraper?

Complete listing coverage in one pass. Most Amazon scrapers stop at title, price and rating. This one also returns the specification table, the "About this item" attribute pairs, gallery image URLs, category breadcrumbs, variant ASINs and top reviews — so a single run gives you enough to rebuild a product page, not just a price alert.

Failures are visible, not silent. Every record carries statusMessage and errorMessage, and not-found listings are pushed as explicit NOT_FOUND rows by default. When you feed in 5,000 ASINs and get 4,900 rows back, you can tell exactly which 100 failed and why, instead of guessing.

Diagnostics built into the input. Amazon changes its markup regularly. canaryMode exists so you can verify selectors against one live URL — with HTTP status and response length logged per attempt — before spending a run on a large batch that might come back empty.

Predictable, browser-free execution. Because the scraper uses direct HTTP requests with rotated TLS fingerprints and a lightweight parser rather than a headless browser, runs consume far less memory and behave consistently under load.

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📥 Input

{
  "startUrls": [
    { "url": "https://www.amazon.com/dp/B07DF46NW9" },
    { "url": "https://www.amazon.com/dp/B08N5WRWNW" }
  ],
  "canaryMode": false,
  "includeNotFound": true,
  "maxConcurrency": 5,
  "maxRetries": 5
}

🔧 Amazon Product Scraper Input Fields

Field	Type	Required	Default	Description
startUrls	array	✅ Yes	—	Amazon product URLs (e.g. https://www.amazon.com/dp/ASIN) or bare 10-character ASINs to scrape
canaryMode	boolean	No	false	Scrapes only the first start URL and logs extra diagnostic info (HTTP status and response length per attempt). Use to quickly verify selectors still work before running a full batch
includeNotFound	boolean	No	true	When enabled, pushes a record with statusMessage "NOT_FOUND" for URLs that 404 or resolve to Amazon's page-not-found template, instead of silently skipping them
maxConcurrency	integer	No	5	Maximum number of product pages fetched in parallel
maxRetries	integer	No	5	Attempts per product URL before giving up. Each retry uses a fresh proxy session, a randomised delay, and a rotated browser TLS fingerprint

💡 Input Examples

Quick selector health check before a large run:

{
  "startUrls": [{ "url": "https://www.amazon.com/dp/B07DF46NW9" }],
  "canaryMode": true
}

High-throughput batch with aggressive retries:

{
  "startUrls": [
    { "url": "https://www.amazon.com/dp/B07DF46NW9" },
    { "url": "https://www.amazon.com/dp/B0BSHF7WHW" },
    { "url": "https://www.amazon.com/dp/B09B8V1LZ3" }
  ],
  "maxConcurrency": 10,
  "maxRetries": 8
}

Clean dataset with dead listings excluded:

{
  "startUrls": [{ "url": "https://www.amazon.com/dp/B08N5WRWNW" }],
  "includeNotFound": false,
  "maxConcurrency": 3
}

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📤 Output

{
  "url": "https://www.amazon.com/dp/B07DF46NW9",
  "asin": "B07DF46NW9",
  "title": "DEWALT 9-in-1 Painter's Tool | Straight Scraper, Curved Scraper, Gouger, Roller Cleaner, Can Opener…",
  "price": 13.04,
  "priceText": "$13.04",
  "currency": "$",
  "rating": 4.8,
  "ratingText": "4.8 out of 5",
  "reviewCount": 2368,
  "reviewCountText": "(2,368)",
  "imageUrls": ["https://m.media-amazon.com/images/I/61y7JLUgQPL._AC_SL1500_.jpg"],
  "aboutProduct": [
    { "label": "Material", "value": "Carbon Steel" },
    { "label": "Brand", "value": "DEWALT" }
  ]
}

🧾 Amazon Product Output Fields

Field	Type	Description
url	string | null	Canonical URL of the scraped item
asin	string | null	Amazon Standard Identification Number
statusMessage	string | null	Status message of the item
errorMessage	string | null	Error message of the item
scrapedAt	string | null	When this record was scraped
title	string | null	Title of the item
price	number | null	Price of the item
priceText	string | null	Price as displayed, including currency symbol
currency	string | null	Currency code of the price
rating	number | null	Average rating score
ratingText	string | null	Text of the rating
reviewCount	integer | null	Number of reviews
reviewCountText	string | null	Text of the review count
availability	string | null	Availability of the item
bylineText	string | null	Text of the byline
shipsFrom	string | null	Ships from of the item
soldBy	string | null	Sold by of the item
condition	string | null	Condition of the item
imageUrls	array | null	Image URLs values collected for the item
features	array | null	Features values collected for the item
description	string | null	Long-form description text
breadcrumbs	array | null	Breadcrumbs values collected for the item
productDetails	object | null	Product details of the item
aboutProduct	array | null	About product values collected for the item
importantInformation	array | null	Important information values collected for the item
variationAsins	object | null	Variation ASINs of the item
variationDimensions	object | null	Variation dimensions of the item
topReviews	array | null	Top reviews values collected for the item

Fields that Amazon does not render on a given listing come back as empty strings or null rather than being omitted, so every record keeps a stable shape across the whole dataset.

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💻 How to Use the Amazon Product Scraper (Step by Step)

Step 1: Assemble Your ASIN or Product URL List

Start by collecting the listings you care about. The startUrls field accepts full product URLs in the https://www.amazon.com/dp/ASIN form as well as bare 10-character ASINs, which means an existing inventory export with an ASIN column can be pasted in without transformation. Mixing both formats in the same list is fine. If you are building a competitor set from scratch, work category by category so you can attribute results back to a specific segment later using the breadcrumbs field.

Step 2: Run a Canary Check First

Before committing a large batch, set canaryMode to true and run with a single representative URL. The scraper will fetch only the first start URL and log the HTTP status and response length for each attempt. This tells you in seconds whether the page is being served normally and whether the parser is still finding the elements it expects. It is a cheap habit that saves you from discovering a markup change halfway through a several-thousand-URL run.

Step 3: Tune Concurrency and Retries for Your Batch

maxConcurrency defaults to 5 parallel page fetches and maxRetries defaults to 5 attempts per URL. For a small batch of a few dozen products, the defaults are usually right. For large runs, raising concurrency shortens wall-clock time but increases the request rate; lowering it produces a gentler, more patient crawl that tends to yield a higher completion rate on stubborn listings. Retries matter more than raw speed — each retry uses a fresh proxy session, a randomised delay and a rotated TLS fingerprint, so a URL that fails on attempt one frequently succeeds on attempt three.

Step 4: Decide How to Handle Missing Listings

includeNotFound is enabled by default, which means URLs that 404 or land on Amazon's page-not-found template are pushed as records with statusMessage set to "NOT_FOUND". Keep this on when you are reconciling a catalogue and need to know which ASINs have been delisted. Switch it off when you want a clean analytical dataset with no placeholder rows and are tracking coverage separately.

Step 5: Start the Run and Watch the Log

Click Start in the Apify console, or trigger the run through the API. The log reports per-URL progress along with retry activity, so you can see in real time whether pages are being served cleanly or whether the scraper is working through repeated attempts. A run that shows retries succeeding on later attempts is behaving exactly as designed; a run where every URL exhausts maxRetries is a signal to reduce concurrency.

Step 6: Export the Dataset in Your Preferred Format

When the run finishes, the dataset is available as JSON, CSV, Excel, XML or RSS from the Storage tab. CSV is convenient for pricing spreadsheets, but note that nested fields such as productDetails, variationAsins, breadcrumbs and topReviews flatten awkwardly in a spreadsheet. If you need those structures intact, export JSON and load it into your database or analysis notebook instead.

Step 7: Schedule Recurring Amazon Price Monitoring

Pricing and stock data ages quickly. Use Apify's scheduler to re-run the same input on a fixed cadence — daily for fast-moving categories, weekly for stable ones — and append each run's dataset to a warehouse table keyed on asin and scrapedAt. That combination gives you a proper price history instead of a series of disconnected snapshots, which is what makes trend analysis and MAP violation detection possible.

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🔌 API Access & Integrations

Run the Amazon Product Scraper synchronously and get dataset items back in a single HTTP call:

curl -X POST "https://api.apify.com/v2/acts/scrapers-hub~amazons-products-scrapers/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "startUrls": [{ "url": "https://www.amazon.com/dp/B07DF46NW9" }],
    "maxConcurrency": 5,
    "maxRetries": 5
  }'

Or drive it from Python with the official client:

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")

run_input = {
    "startUrls": [
        {"url": "https://www.amazon.com/dp/B07DF46NW9"},
        {"url": "https://www.amazon.com/dp/B08N5WRWNW"},
    ],
    "includeNotFound": True,
    "maxConcurrency": 5,
    "maxRetries": 5,
}

run = client.actor("scrapers-hub/amazons-products-scrapers").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["asin"], item["price"], item["rating"], item["reviewCount"])

The Actor also connects to Zapier, Make, Google Sheets, Slack and any HTTP webhook, so finished runs can push new price data into your own systems without manual export.

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💡 Best Use Cases for Amazon Product Data

💲 Competitor Price Tracking and Repricing

Schedule repeated runs across your competitor set and store price, priceText and currency alongside scrapedAt to build a time series per ASIN. Feeding that history into a repricing rule lets you react to undercutting within hours rather than discovering it at month-end. Pairing price with soldBy also reveals whether a price drop came from Amazon itself or from a third-party merchant.

🛡️ MAP Violation and Brand Protection Monitoring

Brands enforcing minimum advertised pricing need evidence, not anecdotes. Combining price, soldBy, shipsFrom and condition identifies exactly which seller is breaching policy and whether the item is new, used or refurbished. Because scrapedAt is stamped on every record, each violation comes with a defensible timestamp for enforcement correspondence.

📈 Product Research and Category Opportunity Analysis

Before launching into a category, pull a broad set of ASINs and analyse rating, reviewCount and price together. High review volume with a mediocre rating is the classic signature of unmet demand, and breadcrumbs lets you segment those findings by Amazon's own category taxonomy rather than by your guess at the market structure.

🧩 Catalogue Enrichment and Content Benchmarking

If you sell on Amazon, the title, features, description, aboutProduct, importantInformation and imageUrls fields let you benchmark your listing content against the best performers in your category. Counting bullet points, gallery images and populated attribute pairs across top-ranked competitors produces a concrete content checklist for your own listing optimisation.

🎨 Variant and Assortment Mapping

variationAsins and variationDimensions expose the full child-ASIN family behind a parent listing and the attributes those children vary along — size, colour, pack count. Expanding a seed list through these fields turns a shortlist of parent products into a complete assortment map, which is essential for gap analysis against your own SKU range.

🗣️ Review Mining and Voice-of-Customer Analysis

The topReviews array captures the customer reviews surfaced on the product page. Running those through a sentiment or topic model, grouped by asin and category from breadcrumbs, surfaces recurring complaints and praise themes that inform product development far more directly than an aggregate star score does.

📦 Availability and Stockout Intelligence

Tracking availability and shipsFrom over successive runs shows when competitors go out of stock and how long they stay there. Stockout windows are prime opportunities for promotional spend, and repeated fulfilment-origin changes in shipsFrom can signal a supply chain shift worth investigating.

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⚙️ Tips for Better Amazon Scraping Results

• Always canary before you batch. A canaryMode run against one URL costs almost nothing and confirms the parser is still aligned with Amazon's current markup before you commit a large job.
• Prefer more retries over more concurrency. Raising maxRetries improves completion rate on difficult listings because each attempt gets a fresh proxy session and TLS fingerprint. Raising maxConcurrency only makes the run faster, and past a point it makes failures more likely.
• Split very large ASIN lists into several runs. Batches of a few hundred to a few thousand URLs are easier to monitor, cheaper to retry, and let you spot a systemic failure early rather than after everything has finished.
• Key your warehouse on asin, not url. Amazon URLs carry tracking parameters and regional variations, whereas the ASIN is stable. Store url for reference but join on asin.
• Use price for maths and priceText for display. The numeric field strips formatting; the text field preserves exactly what a shopper saw, including the currency symbol, which matters when you need to evidence a price point.
• Keep includeNotFound on for catalogue reconciliation. Delisted ASINs are information. A NOT_FOUND row tells you a product has gone; a missing row tells you nothing at all.

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🛠️ Troubleshooting

Why are availability, soldBy and shipsFrom empty on some products? Amazon does not render these blocks consistently across every listing, category or buy-box state. When a field is absent from the page it is returned as an empty string rather than being dropped, which keeps the record shape uniform. If these fields are empty across the entire dataset rather than on scattered rows, run canaryMode to check whether the page is being served in full.

All my records have statusMessage of NOT_FOUND. What went wrong? Either the ASINs genuinely no longer exist, or the URLs are malformed. Check that each entry is a valid https://www.amazon.com/dp/ASIN link or a clean 10-character ASIN with no surrounding whitespace or quotation marks. A single valid URL run in canaryMode will confirm which of the two it is.

The run is slow or many URLs exhaust their retries. Lower maxConcurrency so fewer pages are requested in parallel, and raise maxRetries so each URL gets more attempts with fresh sessions. A patient configuration nearly always returns a higher completion rate than an aggressive one on a large batch.

Nested fields look like unreadable text in my CSV export. productDetails, variationAsins, breadcrumbs, aboutProduct and topReviews are objects and arrays. Spreadsheet exports serialise them into a single cell. Export the dataset as JSON when you need those structures, and reserve CSV for the flat pricing and rating fields.

Prices differ from what I see in my own browser. Amazon personalises pricing, currency and buy-box selection by region, account history and delivery address. The scraper sees an unauthenticated visitor's view of the page, which is the correct baseline for competitive analysis but will not match a logged-in session with Prime pricing or a local address applied.

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❓ Frequently Asked Questions About Amazon Product Scraping

What does this Amazon Product Scraper actually extract? It extracts the full product detail page for each URL or ASIN you supply: title, price, currency, star rating, review count, availability, seller and fulfilment details, condition, gallery image URLs, bullet features, long-form description, category breadcrumbs, the specification table, structured attribute pairs, variant ASINs and the top reviews shown on the page.

Can I use plain ASINs instead of full Amazon URLs? Yes. The startUrls field accepts bare 10-character ASINs as well as full https://www.amazon.com/dp/ASIN links, and you can mix both in the same list. This makes it straightforward to feed in an existing product export without reformatting it first.

Do I need to configure proxies for this Amazon scraper? No. Proxy rotation is handled automatically inside the Actor, and each retry attempt uses a fresh proxy session together with a rotated browser TLS fingerprint. There is no proxy configuration field and no credentials for you to manage.

How many Amazon products can I scrape in one run? There is no fixed cap in the input — the startUrls list can be as long as you need. In practice, splitting very large lists into batches of a few hundred to a few thousand makes runs easier to monitor and cheaper to retry if something goes wrong partway through.

Does the Amazon Product Scraper use a headless browser? No. It fetches product pages over direct HTTP requests and parses them with a fast HTML parser. That keeps memory use low and run behaviour predictable compared with browser-based scrapers.

What is canary mode and when should I use it? canaryMode scrapes only the first start URL and logs extra diagnostic information — HTTP status and response length for each attempt. Use it as a pre-flight check before a large batch, or whenever a run returns unexpectedly sparse data, to confirm the page is being served and parsed correctly.

Why do some fields come back as null or empty strings? Amazon's product pages are not uniform. A grocery listing, a book and a power tool render different blocks, and buy-box state changes what is displayed. Rather than omitting absent fields, the scraper returns them empty so every record in the dataset has the same shape and your downstream schema stays stable.

Can I scrape Amazon marketplaces outside amazon.com? The input is designed around Amazon product detail page URLs. Marketplace behaviour varies by domain, so test a small batch with canaryMode against the specific marketplace URLs you intend to use before scaling up a run.

How do I track Amazon price changes over time? Schedule the same input to run on a recurring basis and append each dataset to a table keyed on asin and scrapedAt. Because every record carries its own scrape timestamp, the resulting history supports proper trend analysis, price-drop alerting and MAP violation evidence.

What is the difference between price and priceText? price is a number with formatting stripped, ready for calculations and comparisons. priceText is the price string exactly as displayed on the page, including the currency symbol. Use the numeric field for analysis and the text field when you need to show or evidence what a shopper actually saw.

Does it return product variations such as size and colour? Yes, through variationAsins and variationDimensions. The first lists the sibling ASINs belonging to the same parent listing; the second describes the attributes those variants differ on. You can feed the discovered ASINs back into startUrls to scrape each variant in full.

Are customer reviews included in the Amazon scraper output? The topReviews array captures the reviews Amazon surfaces on the product detail page itself. This is the on-page review sample rather than a complete review archive, and it is well suited to sentiment sampling and theme detection across a category.

What happens to Amazon URLs that no longer exist? With includeNotFound left at its default of true, those URLs produce a record with statusMessage set to "NOT_FOUND" so you can identify delisted products. Set it to false if you would rather have a clean dataset with no placeholder rows.

Which export formats does the Amazon product data support? Datasets can be exported as JSON, CSV, Excel, XML or RSS from the Apify console, or pulled through the API. Choose JSON when you need nested fields like productDetails and breadcrumbs intact; CSV works well for the flat pricing and ratings columns.

Can I integrate the Amazon Product Scraper with my own tools? Yes. Runs can be triggered through the Apify API or the Python and JavaScript clients, and finished runs can push data onward through Zapier, Make, Google Sheets, Slack or a custom webhook, so scraped Amazon data lands in your systems automatically.

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🆘 Support & Feedback

Found a bug, a listing layout the parser mishandles, or a field that consistently returns empty? Please open a report in the Issues tab of this Actor — include the exact input JSON and one affected product URL so it can be reproduced quickly.

Need a custom build? Variant expansion, a different Amazon marketplace, review pagination, or a bespoke output schema shaped to your warehouse — get in touch at scraperhubapi@gmail.com and describe what you need.

If the Amazon Product Scraper saves you time, please leave a review on the Actor page. Honest feedback about which fields matter most directly shapes what gets improved next.

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⚖️ Disclaimer

This Amazon Product Scraper collects only publicly available information from Amazon product detail pages — the same content any visitor can see without logging in. It does not access private accounts, order histories, customer data, or any content behind authentication.

You are responsible for how you use the data this Actor produces. Amazon product pages may contain personal data in customer reviews, including reviewer names and review text. If you process that information for users in the EU, UK or other regulated jurisdictions, you must establish a lawful basis under the GDPR or the equivalent local framework, honour data subject rights, and retain the data no longer than your stated purpose requires.

Scraping is also subject to Amazon's Terms of Service and robots directives. Review those terms and take your own legal advice before running large-scale or commercial collection. Nothing in this document constitutes legal advice.

If you believe personal data relating to you has been collected through this Actor and you would like it removed, contact scraperhubapi@gmail.com with the relevant details and the request will be handled promptly.