We extract product specifications, Co-op member pricing, colour and size matrices, and local store inventory from REI. 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 rei.com. All fields typed and schema-versioned.
"sku": "102059", "title": "Half Dome Helmet", "brand": "Black Diamond", "base_price": 59.95, "currency": "USD", "category": "Climbing", "rating": 4.6, "review_count": 342, "weight": "12 oz", "best_use": "Rock Climbing"
| # | sku | title | brand | category | sub_category | base_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Inventory objects from rei.com. All fields typed and schema-versioned.
"sku": "102059", "variant_id": "102059-BLU-M", "base_price": 59.95, "coop_member_price": 47.89, "discount_pct": 20, "online_stock_status": "In Stock", "local_store_stock": "Limited Stock", "store_zip_code": "98109", "price_timestamp": "2026-05-12T09:14:00Z"
| # | sku | variant_id | base_price | coop_member_price | clearance_price | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from rei.com. All fields typed and schema-versioned.
"review_id": "REV-938475", "sku": "102059", "star_rating": 5, "verified_buyer": true, "review_title": "Durable and comfortable", "recommended": true, "helpful_votes": 14, "usage_frequency": "Weekly"
| # | review_id | sku | reviewer_name | verified_buyer | star_rating | review_title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Re/Supply Used Gear objects from rei.com. All fields typed and schema-versioned.
"used_sku": "U-102059-A", "original_sku": "102059", "condition": "Excellent", "defects_description": "Minor scuffs on outer shell.", "used_price": 35.0, "new_price": 59.95, "savings_pct": 41, "store_location": "Seattle Flagship"
| # | used_sku | original_sku | title | condition | defects_description | used_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from rei.com. All fields typed and schema-versioned.
"keyword": "climbing helmet", "position": 1, "sku": "102059", "brand": "Black Diamond", "price": 59.95, "coop_exclusive": false, "new_arrival": false, "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | position | sku | title | brand | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our REI scraper captures the complexities of outdoor retail data: nested colour and size matrices, Co-op member discounts, local store inventory APIs, and detailed technical specifications.
Extract technical details including weight, dimensions, materials, temperature ratings, and best-use categories for gear and apparel.
Capture regular retail prices alongside REI Co-op member exclusive discounts, sale prices, and clearance markdowns.
Track used gear inventory, including condition ratings, specific defect descriptions, and price savings compared to new items.
Query inventory availability across physical REI locations using zip code parameters to track regional stock depth.
Extract all available variant combinations, mapping specific prices and stock statuses to exact colour and size pairings.
Identify products with bluesign materials, Fair Trade certifications, and climate neutral designations.
Extract customer sentiment, verified purchase flags, usage frequency metrics, and product recommendations from the review corpus.
Track brand visibility and product positioning across REI category pages and specific keyword search results.
Run pipelines at daily or hourly cadences, delivering only the records that have changed since the last extraction.
Brief in. Clean data out.
Provide REI categories, brand names, or specific SKU lists. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for rei.com.
Schema validation, null-rate checks, and variant mapping verification before full launch.
JSON, CSV, or Parquet pushed to your AWS S3 bucket, BigQuery dataset, or webhook endpoint.
Extracting accurate variant pricing and local inventory requires bypassing modern bot protection and hydrating complex JavaScript interfaces.
REI uses strict bot mitigation to block automated scrapers. Our crawlers utilise US-based residential ISP proxies with realistic browser fingerprints and full cookie session management to maintain access.
Colour and size selections on REI product pages rely heavily on JavaScript. We run full Playwright browser sessions to trigger variant changes and capture the exact price and stock status for every combination.
Instead of purely scraping the DOM for in-store availability, our pipeline intercepts the backend API calls triggered by zip code searches, ensuring faster and more reliable local inventory extraction.
Product specification tables vary wildly between a tent and a pair of boots. Our schema normalises these diverse attributes using fallback chains and text-pattern matching to ensure consistent data delivery.
We monitor extraction runs for sudden drops in inventory counts or null-rate spikes in pricing fields, alerting our infrastructure team before bad data reaches your warehouse.
Outdoor brands and competing retailers monitor REI pricing, Co-op discounts, and clearance events to adjust their own pricing strategies.
Manufacturers track their product placement, review sentiment, and search visibility within the REI ecosystem compared to rival brands.
Analysts extract bluesign and Fair Trade certifications to track the adoption rate of sustainable materials in the outdoor apparel market.
Retail strategists analyse the Re/Supply catalogue to understand depreciation curves and secondary market value for outdoor equipment.
Supply chain teams monitor regional stockouts and inventory depth across REI physical locations to optimise their own distribution.
Machine learning teams use REI technical specifications and best-use categorisations to train outdoor gear recommendation engines.
"REI holds the definitive catalogue for outdoor gear specifications and sustainability metrics, but extracting size-level inventory requires bypassing strict bot protection."
Most teams underestimate the investment required: reliable REI scraping requires residential proxies, full JavaScript rendering for size matrices, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our rei.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 and retry logic. Playwright handles JavaScript rendering for complex variant matrices and local inventory API triggers.
We maintain pools of US-based residential ISP proxies. Rotation happens per-request with sticky sessions to bypass bot mitigation without triggering blocks.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management, ensuring data is delivered exactly when expected.
Data delivered to where your team already works — no new tooling required.
About rei.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product, pricing, and inventory information from REI is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls to access private member dividend information.
We utilise US-based residential ISP proxies and full Playwright browser sessions with realistic device fingerprinting. This allows us to navigate the site and extract data without triggering automated blocking mechanisms.
Yes. We can configure the pipeline to query inventory availability across specific REI physical locations using targeted zip codes, capturing stock depth for regional analysis.
Yes. We extract data from the Re/Supply catalogue, including original SKUs, used condition ratings, specific defect notes, and the price delta between new and used items.
We support daily catalogue refreshes and can configure higher-frequency pipelines (e.g., hourly) for specific high-value categories or clearance monitoring.
Yes. We provide a sample run of up to 500 products as part of the pre-engagement scoping process to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily extract of Co-op pricing or a comprehensive map of technical specifications across the catalogue, we build and operate the pipeline. Tell us your requirements.
