We extract product listings, dynamic pricing, flash sale signals, seller intelligence, and reviews from Qoo10.sg. 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 qoo10.sg. All fields typed and schema-versioned.
"item_code": "684920184", "title": "Korean Style Oversized T-Shirt", "brand": "K-Fashion", "base_price": 12.9, "discount_pct": 35, "shipping_origin": "South Korea", "rating": 4.7, "review_count": 1428
| # | item_code | title | brand | seller_name | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from qoo10.sg. All fields typed and schema-versioned.
"item_code": "684920184", "base_price": 19.9, "time_sale_price": 12.9, "daily_deal": false, "group_buy_price": "None", "coupon_eligible": true, "currency": "SGD", "price_timestamp": "2026-05-12T09:14:00Z"
| # | item_code | base_price | time_sale_price | group_buy_price | daily_deal | discount_amount |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Options & Variations objects from qoo10.sg. All fields typed and schema-versioned.
"item_code": "684920184", "option_name": "Colour", "option_value": "Navy Blue", "price_modifier": 2.0, "final_price": 14.9, "stock_status": "In Stock", "sku": "KF-TSHIRT-NAVY-M"
| # | item_code | option_id | option_name | option_value | price_modifier | final_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from qoo10.sg. All fields typed and schema-versioned.
"review_id": "REV-9928174", "item_code": "684920184", "star_rating": 5, "buyer_name": "s***9", "purchase_option": "Colour: Navy Blue, Size: L", "review_text": "Good material and fast delivery.", "helpful_votes": 12, "review_date": "2026-04-18"
| # | review_id | item_code | buyer_name | star_rating | review_text | purchase_option |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seller Intelligence objects from qoo10.sg. All fields typed and schema-versioned.
"seller_id": "SEL-4921", "shop_name": "Seoul Style Official", "power_seller_badge": true, "total_items": 4291, "positive_feedback_pct": 98.2, "follower_count": 15822, "shipping_speed": "Fast", "country": "South Korea"
| # | seller_id | shop_name | shop_url | power_seller_badge | total_items | positive_feedback_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Qoo10 scraper handles every layer of the platform: dynamic option pricing, Time Sale tracking, cross-border shipping variations, and the review corpus. Built with JavaScript rendering and anti-bot circumvention.
Title, description, images, brand, and every metadata field Qoo10 surfaces. Scraped at the item level with full option mapping.
Capture base price and calculate final prices across hundreds of option combinations that add or subtract from the base cost.
Monitor Time Sale windows, Group Buy thresholds, and Daily Deal pricing to track competitor promotional cadences.
Full review text, star ratings, helpful vote counts, and specific purchased options paginated across all review pages.
Shop name, Power Seller status, feedback score, total items, and follower counts for every merchant on the platform.
Extract shipping origins, estimated delivery windows, and Qprime eligibility for local versus international sellers.
Track organic position for any keyword across Qoo10.sg with Plus Listing and Power Listing ad detection.
Identify items eligible for cart coupons, shop coupons, and Q-point redemption to calculate true minimum advertised price.
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 item codes, 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 qoo10.sg.
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.
Qoo10 relies heavily on client-side rendering for pricing and options. Here is how we stay resilient and deliver accurate data.
Qoo10 displays a base price, but selecting options often adds or subtracts from that base. Our JavaScript rendering engine executes these selection events to capture the true final price for every SKU variant.
We route requests through SG-based residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass rate limits and IP bans.
Product options, reviews, and Q&A sections are heavily JavaScript-rendered. We run full Playwright browser sessions with lazy-load triggering to capture data that headless HTTP clients miss entirely.
Our selector strategy uses multiple fallback chains per field. We combine CSS selectors, XPath, and API interception so a layout change does not break your data pipeline overnight.
For large item catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
eCommerce brands monitor Time Sale pricing, Group Buy discounts, and base prices to optimise their own promotional calendars.
Analysts track shipping origins and delivery times to understand the balance of local Singaporean inventory versus Korean or Chinese imports.
Brands audit third-party sellers for MAP violations, counterfeit listings, and unauthorised resellers on the platform.
ML teams use Qoo10 datasets to train recommendation engines, NLP classifiers, and sentiment models for the Southeast Asian market.
Supply chain teams correlate review velocity, stock status, and Group Buy participation with sales volume to improve procurement models.
Competitors track Daily Deal and Time Sale frequency per seller to map out merchant promotional strategies.
"Qoo10.sg drives significant cross-border e-commerce volume in Southeast Asia, but its complex option-pricing structures make data extraction notoriously difficult."
Most teams underestimate the investment required: reliable Qoo10 scraping requires residential proxies, full JavaScript rendering for dynamic price calculation, CAPTCHA handling, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis.
Everything supported by our qoo10.sg 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 SG 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 qoo10.sg scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Qoo10 is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review Qoo10's ToS and consult legal counsel for specific use cases.
Qoo10 uses a base price system where selecting options alters the final cost. We use Playwright to render the page, execute the JavaScript logic tied to option selection, and extract the precise final price for every SKU variant.
Yes. We extract specific promotional states, including Time Sale countdowns, Daily Deal flags, and Group Buy minimum purchase thresholds.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined item set. Full catalogue refreshes at daily cadence complete within a 6-12 hour window depending on size.
Yes. We scrape seller storefronts to capture Power Seller badges, total inventory counts, feedback percentages, and shipping origins.
Our smallest packages start at a defined item 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.
Absolutely. We provide a sample run of up to 500 items 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 500K items, we scope, build, and operate the pipeline. Tell us what you need.
