We extract product listings, brand presentations (PT), pricing signals, stock depth, and photo reviews from 29cm.co.kr. 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 29cm.co.kr. All fields typed and schema-versioned.
"item_no": "2148932", "title": "Oversized Oxford Shirt (Blue)", "brand_name": "ANOTHER OFFICE", "price": 89000, "discount_price": 75650, "discount_rate": 15, "is_sold_out": false, "heart_count": 1429
| # | item_no | title | brand_name | brand_name_kor | category_id | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Brand Intelligence objects from 29cm.co.kr. All fields typed and schema-versioned.
"brand_no": "8432", "brand_name": "BROWNYARD", "brand_name_kor": "브라운야드", "follower_count": 48291, "item_count": 142, "origin": "South Korea"
| # | brand_no | brand_name | brand_name_kor | follower_count | description | origin |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Photo Reviews objects from 29cm.co.kr. All fields typed and schema-versioned.
"review_no": "984211", "item_no": "2148932", "rating": 5, "size_fit": "True to size", "review_text": "Fabric is sturdy but breathable. Colour matches the editorial photos perfectly.", "helpful_votes": 14
| # | review_no | item_no | user_id | rating | size_fit | color_fit |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Editorials & PT objects from 29cm.co.kr. All fields typed and schema-versioned.
"post_no": "PT_184", "type": "Presentation", "title": "The New Standard of Denim", "brand_focus": "YOUTH", "publish_date": "2026-03-14", "view_count": 34912
| # | post_no | type | title | subtitle | author | publish_date |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Categories & Ranks objects from 29cm.co.kr. All fields typed and schema-versioned.
"category_no": "2681", "category_name": "Shirts/Blouses", "parent_category": "Women's Apparel", "level": 2, "item_count": 18492, "is_active": true
| # | category_no | category_name | parent_category | level | item_count | url |
|---|---|---|---|---|---|---|
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Our 29CM scraper handles complex React state hydration, Korean text normalisation, and heavy image CDNs to deliver structured catalogue data without the bot-blocking headaches.
Extract titles, prices, discounts, option matrices, sizing charts, and material compositions across all active apparel and lifestyle categories.
Capture base price, 29CM exclusive discounts, coupon-applied prices, and limited-time sale flags timestamped per run.
Paginate through customer reviews to extract raw text, star ratings, fit metrics (size/colour accuracy), and user-uploaded image URLs.
Parse 29CM's unique 'Presentation' (PT) and 'Welove' editorial content, linking narrative features directly to the featured item numbers.
Monitor sold-out statuses, restock notifications, and variant-level inventory depth across high-demand K-fashion drops.
Track follower counts, brand descriptions, origin data, and total active SKUs for over 8,000 domestic and international brands.
Scrape daily, weekly, and monthly best-seller ranks across primary and sub-categories to identify trending items and brands.
Route requests through South Korean residential and mobile IP pools to bypass region-based rate limiting and currency localisation shifts.
Maintain hash indexes of last-seen values per item. Emit only diffs for price changes or stock shifts to reduce downstream processing.
Brief in. Clean data out.
Provide category URLs, brand IDs, or search terms. We design the extraction schema together.
We configure Scrapy/Playwright crawlers, KR proxy rotation, and payload hydration logic for 29cm.co.kr.
Schema validation, null-rate checks, and KR text encoding verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Scraping modern Korean eCommerce platforms requires handling heavy client-side rendering and strict API rate limits. Here is how we build resilience.
29CM relies heavily on client-side rendering. Instead of fragile DOM scraping, our pipeline intercepts and parses the underlying JSON payloads embedded in the page state, ensuring 100% data fidelity for complex option matrices.
29CM frequently alters pricing, shipping data, or blocks access entirely for non-KR IP addresses. We route all extraction requests through premium South Korean residential proxies to guarantee accurate domestic data.
Fashion data relies on visuals. We extract direct URLs to high-resolution product images, editorial banners, and user-generated review photos from 29CM's image CDNs, bypassing low-res thumbnails.
29CM's category and search APIs often cap pagination at 100 pages. We use recursive sub-category traversal and granular price-bracket filtering to extract complete catalogues without hitting hard limits.
eCommerce APIs evolve. Our observability stack monitors the 29CM pipeline for null-rate spikes in critical fields like discount_price or stock_status, pausing the pipeline and alerting engineers before corrupted data reaches your warehouse.
Fashion forecasters monitor best-seller ranks, heart counts, and editorial features to identify emerging South Korean streetwear and contemporary trends.
Apparel brands track competitor pricing, discount cadences, and new product launch velocity within the 29CM ecosystem.
International retailers scrape 29CM catalogues to source trending Korean brands, mapping domestic prices to calculate export margins.
Product teams analyse thousands of photo reviews to extract common complaints about sizing, fabric quality, and colour discrepancies.
Agencies track brand follower growth, editorial placements (PT), and customer engagement metrics to measure brand health.
Machine learning teams use 29CM's high-quality editorial images and user-uploaded review photos to train fashion classification and styling models.
"29CM dictates South Korean fashion trends, but extracting its heavily curated, editorial-driven catalogue requires specialised infrastructure."
Most teams fail at scraping 29CM due to its React-heavy frontend, dynamic API payloads, and strict KR-region rate limits. DataFlirt manages residential proxies, JavaScript rendering, and payload hydration so your engineers can focus on K-fashion market analysis rather than bot mitigation.
Everything supported by our 29cm.co.kr scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Instead of fragile DOM parsing, we intercept 29CM's internal API responses and hydrate Next.js state objects, ensuring pristine data structure for complex variant matrices.
We maintain dedicated pools of South Korean residential and mobile proxies. Rotation occurs per-request to bypass rate limits and ensure accurate domestic pricing.
Pipelines execute on AWS ECS with Airflow handling scheduling and retry logic. Postgres stores historical state for diff calculation and anomaly detection.
Data delivered to where your team already works — no new tooling required.
About 29cm.co.kr scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available, non-authenticated data from 29cm.co.kr is generally permissible. DataFlirt extracts only public product catalogues, prices, and reviews. We do not bypass login walls to extract user PII or private order histories. Clients must consult legal counsel regarding their specific commercial use of the data.
29CM frequently restricts or alters content for non-Korean IP addresses. We route all extraction requests through premium South Korean residential proxies, ensuring the data reflects exactly what a domestic user sees.
Our core pipeline extracts the raw Korean text (UTF-8 encoded) directly from the platform. We can implement secondary processing steps via LLM APIs to translate titles, descriptions, and reviews into English before delivery, subject to additional compute costs.
For targeted lists of high-priority SKUs, we can configure pipelines to run at sub-hourly intervals. Full catalogue refreshes typically run on a daily cadence.
Yes. We extract the narrative text, high-resolution imagery, and the specific item numbers linked within the editorial features, allowing you to correlate content marketing with product visibility.
Our minimum engagement typically starts at weekly deliveries for a defined set of brands or categories (e.g., 10,000 SKUs). Pricing scales based on extraction frequency and total record volume.
Yes. We provide a sample extraction of up to 500 products or 5 brands during the scoping phase. This allows your engineering team to validate the schema, variant mapping, and Korean text encoding before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of K-fashion brands or continuous tracking of 29CM best-sellers — we scope, build, and operate the pipeline. Tell us what you need.
