We extract product listings, pricing signals, size availability, fabric compositions, and customer reviews from Gap. 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 gap.com. All fields typed and schema-versioned.
"product_id": "734521", "title": "Vintage Soft Classic Hoodie", "price": 34.99, "list_price": 59.95, "colour_name": "True Black", "size_range": "['XS', 'S', 'M', 'L', 'XL']", "washwell_certified": true, "fit_type": "Relaxed"
| # | product_id | title | brand | category | sub_category | price |
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Complete list of extractable fields for Inventory & Pricing objects from gap.com. All fields typed and schema-versioned.
"sku": "734521-00-1", "size": "M", "price": 34.99, "discount_pct": 41, "gapcash_eligible": true, "final_sale": false, "stock_status": "IN_STOCK", "low_stock_warning": false
| # | product_id | sku | colour | size | price | list_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from gap.com. All fields typed and schema-versioned.
"review_id": "REV-98234", "rating": 4, "review_title": "So soft, runs slightly large", "fit_rating": "Runs Large", "length_rating": "True to Size", "quality_rating": "Excellent", "helpful_votes": 12, "verified_purchaser": true
| # | review_id | product_id | reviewer_nickname | rating | review_title | review_text |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Gap scraper handles every layer of the platform: product catalogues, deep variant matrices, dynamic promotional pricing, and size-level stock availability — with JavaScript rendering and anti-bot circumvention built in.
Colour variants, size matrices, and fabric details mapped to parent SKUs across all main and sub-categories.
Track base prices, markdown events, GapCash eligibility, and promo code applicability at the SKU level.
Monitor size-level availability and low-stock indicators across regional storefronts.
Extract Washwell sustainability tags, material composition, and detailed care instructions for every garment.
Scrape granular customer feedback including fit, length, and quality sliding-scale ratings.
gap.com, gap.co.uk, gapcanada.ca, and localized sub-brands including GapKids and babyGap.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide category URLs, keyword sets, or specific product IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for gap.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.
Apparel sites rely on complex JavaScript state for variant switching and inventory rendering. We extract the underlying JSON state rather than parsing fragile DOM elements.
Gap products feature deep variant trees. Rather than simulating clicks on every colour and size swatch, our pipeline intercepts the Next.js/React hydration state, extracting the entire pricing and inventory matrix in a single request.
Gap's bot detection operates on TLS fingerprints and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Pricing and availability change based on the user's region. We route requests through specific US, UK, or CA proxy pools to capture accurate localized data without triggering geo-blocks.
For large apparel catalogues, we maintain a hash index of last-seen values per SKU. Subsequent runs only push diffs — reducing compute cost and downstream processing load. You get a clean changelog of stock drops and markdowns.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, schema drift during site redesigns, and coverage drops — and respond before you notice.
Apparel brands track markdowns, promotional cadences, and GapCash events to optimise their own pricing strategies.
Retail analysts evaluate colour availability, fabric trends, and category density to identify seasonal shifts.
Supply chain teams monitor stockout rates and replenishment cycles at the size level across key categories.
ESG analysts audit the prevalence of Washwell and organic cotton tags across the catalogue to measure sustainability goals.
Product teams mine review text and fit-ratings to identify manufacturing defects or sizing inconsistencies.
Resellers identify high-discount, clearance, and promo-stacking opportunities to source inventory at scale.
"Apparel data is uniquely multi-dimensional. A single Gap product might have 60 distinct SKUs across colour and size matrices—each with its own stock state and price."
Extracting fast-fashion data requires handling deep variant matrices and dynamic promotional states. DataFlirt manages the residential proxies, JavaScript rendering, and schema normalisation so your data engineering team receives clean, warehouse-ready product records.
Everything supported by our gap.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 US/UK/CA 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 gap.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Gap is generally permissible under applicable law — reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for block rate spikes in real time and trigger pool rotation automatically.
Yes. We extract the full variant matrix for every product, meaning you receive distinct records and stock statuses for every colour and size combination.
Yes. We extract promotional text, GapCash eligibility flags, and calculate final prices based on publicly visible discount logic.
We support gap.com (US), gap.co.uk (UK), gapcanada.ca (CA), and other regional variants by routing requests through geo-targeted residential proxies.
Real-time streaming pipelines achieve sub-60-minute latency for price and stock signals on a defined SKU set. Full catalogue refreshes complete within a 6-12 hour window depending on scale.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or continuous price and stock monitoring across 100K SKUs — we scope, build, and operate the pipeline. Tell us what you need.
