We extract product listings, Rocket Wow pricing, item winner dynamics, and review corpora from Coupang. 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 coupang.com. All fields typed and schema-versioned.
"product_id": "7348921045", "title": "Samsung Galaxy S24 Ultra 256GB", "brand": "Samsung", "rocket_delivery": true, "rocket_wow": true, "base_price": 1698400.0, "wow_price": 1528560.0, "discount_pct": 10, "rating": 4.9, "review_count": 4821
| # | product_id | title | brand | category | rocket_delivery | rocket_wow |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Winners objects from coupang.com. All fields typed and schema-versioned.
"product_id": "7348921045", "item_winner_seller": "Coupang", "winner_price": 1528560.0, "shipping_fee": 0.0, "wow_member_price": 1528560.0, "card_discount_pct": 5, "other_sellers_count": 14, "out_of_stock": false, "last_updated": "2026-05-12T09:14:00Z"
| # | product_id | item_winner_seller | winner_price | shipping_fee | wow_member_price | card_discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from coupang.com. All fields typed and schema-versioned.
"review_id": "RVW98237492", "product_id": "7348921045", "rating": 5, "review_text": "Delivery was extremely fast via Rocket. Phone condition is perfect.", "review_date": "2026-04-18", "helpful_votes": 34, "verified_purchase": true, "variant_purchased": "Titanium Black / 256GB"
| # | review_id | product_id | author_name | rating | review_text | review_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seller Data objects from coupang.com. All fields typed and schema-versioned.
"seller_id": "SLR482910", "seller_name": "Samsung Authorized Dealer", "business_name": "Samsung Electronics Co., Ltd.", "representative": "Han Jong-hee", "contact_number": "1588-3366", "rating": 4.8, "total_products": 342, "store_url": "https://store.coupang.com/link/samsung"
| # | seller_id | seller_name | business_name | representative | contact_number | business_address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from coupang.com. All fields typed and schema-versioned.
"keyword": "smartphone", "rank_position": 1, "product_id": "7348921045", "ad_badge": false, "rocket_badge": true, "price": 1528560.0, "rating": 4.9, "review_count": 4821, "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | rank_position | product_id | title | price | rocket_badge |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Coupang scraper handles every layer of the platform: Rocket Delivery flags, Item Winner tracking, dynamic pricing, and the review corpus — with JavaScript rendering, session management, and anti-bot circumvention built in.
Title, specifications, images, variations, and every metadata field Coupang surfaces — scraped at product level with variant mapping.
Capture base price, Wow member price, card discount percentages, and shipping fees — timestamped per crawl.
Monitor which seller holds the Item Winner position, their pricing, and the count of competing sellers on the same listing.
Extract badges for Rocket Delivery, Rocket Wow, Rocket Fresh, and Rocket Jikgu to segment fulfillment types.
Full review text, star ratings, helpful vote counts, verified purchase flags, and variant purchased — paginated across all review pages.
Seller name, business registration details, representative contact, and overall rating — for every offer on a listing.
Track organic vs sponsored position for any keyword — with Rocket badges and ad placement capture.
Built-in encoding handling and normalisation for Korean characters, ensuring clean text output without mojibake.
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 product IDs, 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 coupang.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.
Coupang invests heavily in scraping detection and dynamic rendering. Here is how we stay resilient.
Coupang's bot detection operates on TLS fingerprints, browser headers, and IP reputation. Our crawlers use South Korean residential ISP proxies with realistic browser fingerprints and full cookie session management.
Coupang product pages and search results are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution, lazy-load triggering, and dynamic price widget hydration.
Coupang changes its DOM structure frequently. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, and text-pattern matching — so a layout change does not break your data pipeline.
For large product 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.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops. SLA uptime is contractual, not aspirational.
eCommerce brands and sellers monitor pricing, Item Winner status, and card discounts to reprice and protect margin.
Brands audit third-party sellers for MAP violations, counterfeit listings, and unauthorised resellers on Coupang.
Merchants track Rocket Jikgu listings to understand demand for imported electronics and gadgets in the Korean market.
Analysts track category rankings, new entrant launches, and review velocity to identify whitespace and investment opportunities.
ML teams use Coupang datasets to train recommendation engines, NLP classifiers, and sentiment models on Korean text.
Supply chain teams correlate ranking signals, review velocity, and stock depth indicators with sales velocity to improve procurement models.
"Coupang is the dominant force in South Korean eCommerce, but its dynamic rendering and strict WAF make it one of the hardest platforms to query at scale."
Most teams underestimate the investment required: reliable Coupang scraping requires South Korean 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.
Everything supported by our coupang.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 for Coupang's dynamic pages.
We maintain pools of residential ISP proxies specifically in South Korea. Rotation happens per-request with sticky sessions where required to bypass Coupang's regional blocks.
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 coupang.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Coupang is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls. Clients should review Coupang's ToS and consult legal counsel for specific use cases.
We use South Korean residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for WAF blocks in real time and trigger pool rotation or solver queues automatically.
Yes. We identify the specific seller holding the Item Winner position during the crawl, along with their price and the number of competing sellers on the same listing.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined product set. Full catalogue refreshes at daily cadence complete within a 6-12 hour window depending on size.
Yes. Our pipelines are built to handle Korean character encoding natively, ensuring that product titles, reviews, and seller details are extracted and delivered without mojibake or corruption.
Our smallest packages start at a defined product list (typically 1,000-50,000 items) with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency.
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 1M items — we scope, build, and operate the pipeline. Tell us what you need.
