We extract product listings, pricing signals, BSR rankings, seller intelligence, reviews, and Q&A from Amazon. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Product Listings objects from amazon.com. All fields typed and schema-versioned.
"asin": "B09G9BL5CP", "title": "Sony WH-1000XM5 Wireless Headphones", "brand": "Sony", "price": 24990.00, "currency": "INR", "discount_pct": 17, "bsr_rank": 4, "bsr_category": "Electronics > Headphones", "rating": 4.4, "review_count": 18472, "prime_eligible": true, "in_stock": true
| # | ASIN | title | brand | manufacturer | model_number | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Offers objects from amazon.com. All fields typed and schema-versioned.
"asin": "B09G9BL5CP", "price": 24990.00, "list_price": 29990.00, "discount_pct": 17, "deal_type": "LIGHTNING_DEAL", "coupon_amount": 500, "subscribe_save_price": 23690.00, "buybox_price": 24990.00, "price_timestamp": "2026-05-12T09:14:00Z"
| # | asin | price | list_price | discount_pct | discount_abs | deal_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from amazon.com. All fields typed and schema-versioned.
"review_id": "R3K2N8X1P9V4TM", "asin": "B09G9BL5CP", "star_rating": 5, "verified_purchase": true, "review_title": "Best ANC headphones money can buy", "helpful_votes": 247, "review_date": "2026-04-18", "vine_review": false
| # | review_id | asin | reviewer_name | reviewer_profile_url | verified_purchase | star_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Seller & FBA Data objects from amazon.com. All fields typed and schema-versioned.
"seller_id": "A3M4E83S0Q9ZSE", "seller_name": "Sony India Official Store", "feedback_rating": 4.8, "feedback_count": 12841, "positive_pct": 97, "fulfilled_by": "Amazon", "business_seller": true, "fba_eligible": true
| # | seller_id | seller_name | seller_url | feedback_rating | feedback_count | positive_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Search Results objects from amazon.com. All fields typed and schema-versioned.
"keyword": "wireless headphones", "position": 1, "asin": "B09G9BL5CP", "sponsored": false, "amazon_choice_badge": true, "best_seller_badge": false, "price": 24990.00, "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | marketplace | position | asin | title | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Amazon scraper handles every layer of the platform: storefront listings, dynamic pricing, BSR tracking, seller intelligence, and the review corpus — with JavaScript rendering, session management, and anti-bot circumvention built in.
Title, bullets, description, dimensions, weight, images, variations, and every metadata field Amazon surfaces — scraped at ASIN level with parent-child variant mapping.
Capture price, list price, deal badges, coupons, Subscribe & Save rates, business pricing, and used/new buybox prices — timestamped per crawl.
Extract Best Seller Rank across primary and sub-categories. Track rank movement over time across millions of ASINs.
Full review text, star ratings, helpful vote counts, verified purchase flags, variant reviewed, and Vine program attribution — paginated across all review pages.
Seller name, feedback score, fulfillment type, storefront URL, active listing count, response time, and return policy — for every offer on a listing.
Track organic vs sponsored position for any keyword, marketplace, and device type — with Amazon Choice and Best Seller badge capture.
amazon.in, amazon.com, amazon.co.uk, amazon.de, amazon.co.jp and 14 other marketplaces — all from a unified schema.
Monitor deal eligibility windows, claim percentages, and coupon stacking opportunities — useful for repricing and competitor alerting.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide ASIN lists, category URLs, keyword sets, or seller IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for amazon.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Amazon invests heavily in scraping detection. Here's how we stay resilient — and why teams choose managed infrastructure over DIY.
Amazon's bot detection operates on TLS fingerprints, browser headers, mouse-movement heuristics, and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management — trained on real user behaviour patterns.
Amazon product pages, seller storefronts, and search results are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution, lazy-load triggering, and dynamic price widget hydration — capturing data that headless HTTP clients miss entirely.
Amazon changes its DOM structure frequently. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, text-pattern matching, and structured data extraction (LD+JSON) — so a layout change doesn't break your data pipeline overnight.
For large ASIN catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost, storage bloat, and downstream processing load. You get a clean changelog rather than full re-dumps.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops — and respond before you notice. SLA uptime is contractual, not aspirational.
eCommerce brands and 3P sellers monitor pricing, deal windows, and Buy Box to reprice and protect margin.
Brands audit third-party sellers for MAP violations, counterfeit listings, and unauthorised resellers — protecting brand equity at scale.
Analysts track BSR movements, new entrant launches, and category saturation trends to identify whitespace and investment opportunities.
ML teams use Amazon datasets to train recommendation engines, NLP classifiers, and sentiment models.
Supply chain teams correlate BSR signals, review velocity, and stock depth indicators with sales velocity to improve procurement models.
PE firms and analysts track category leaders, seller growth curves, and review-to-rating ratios to evaluate marketplace companies.
"Amazon is the world's largest product catalogue and the richest price-signal dataset on earth — but none of it is queryable unless you build the pipeline."
Most teams underestimate the investment required: reliable Amazon scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our amazon.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across IN/US/UK/DE regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About amazon.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Amazon is generally permissible under applicable law in India, the US, and the UK — reinforced by the hiQ v. LinkedIn ruling and similar precedents. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data, circumvent authentication walls, or violate GDPR. We recommend clients review Amazon's ToS independently and consult legal counsel for specific use cases.
We use residential ISP proxies that appear as real consumer traffic, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes don't break the pipeline. We monitor for 503/CAPTCHA rate spikes in real time and trigger pool rotation or solver queues automatically.
We support amazon.in, amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.ca, amazon.com.au, amazon.fr, amazon.it, amazon.es, amazon.nl, amazon.pl, amazon.se, amazon.sg, and amazon.ae — all from a unified schema with marketplace-normalised pricing.
Latency depends on your agreed cadence. Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined ASIN set. Full catalogue refreshes at daily cadence complete within a 6–12 hour window depending on size. Historical snapshots are available from the day your pipeline is commissioned.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series table per ASIN for BSR rank, price, review count, and availability. History is available from the date your pipeline starts. We do not have historical pre-engagement data.
Our smallest packages start at a defined ASIN list (typically 1,000–50,000 ASINs) with weekly delivery. For larger catalogues, ongoing monitoring contracts, or custom schema requirements, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
Yes — including full pagination across all star-filter views, not just the top 10 reviews. Each review record includes rating, title, body, helpful votes, verified purchase flag, variant reviewed, Vine attribution, review date, and reviewer profile URL where public.
Absolutely. We provide a sample run of up to 500 ASINs or 50 search result pages as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off product catalogue dump or a continuous price-monitoring feed across 2M ASINs — we scope, build, and operate the pipeline. Tell us what you need.
