We extract product listings, promotional pricing, Star Rewards tiers, inventory depth, and customer reviews from Macy's. Delivered as clean JSON, CSV, or Parquet to S3 or Snowflake.
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 Macy's. All fields typed and schema-versioned.
"product_id": "1294812", "title": "Men's Classic Fit Dress Shirt", "brand": "Ralph Lauren", "category": "Men > Shirts > Dress Shirts", "price": 89.5, "colour_options": "['White', 'Blue', 'Pink']", "size_options": "['15 32/33', '15.5 34/35', '16 34/35']", "material": "100% Cotton"
| # | product_id | title | brand | category | price | sale_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promos objects from Macy's. All fields typed and schema-versioned.
"product_id": "1294812", "regular_price": 89.5, "sale_price": 59.99, "promo_code": "VIP", "discount_pct": 33, "promo_end_date": "2026-10-15T23:59:59Z", "lowest_price_guarantee": true
| # | product_id | regular_price | sale_price | promo_code | star_rewards_price | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Inventory & Fulfillment objects from Macy's. All fields typed and schema-versioned.
"product_id": "1294812", "sku": "RL-WHT-155", "size": "15.5 34/35", "colour": "White", "online_stock": true, "store_pickup_eligible": true, "expected_delivery": "2026-10-12"
| # | product_id | sku | size | colour | online_stock | store_pickup_eligible |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from Macy's. All fields typed and schema-versioned.
"review_id": "REV-98213", "product_id": "1294812", "rating": 4.5, "review_text": "Great fit and quality material.", "verified_buyer": true, "helpful_votes": 12, "submission_date": "2026-09-28"
| # | review_id | product_id | rating | review_text | reviewer_nickname | verified_buyer |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category Navigation objects from Macy's. All fields typed and schema-versioned.
"category_id": "CAT-481", "category_name": "Men's Dress Shirts", "product_count": 1420, "top_brands": "['Ralph Lauren', 'Tommy Hilfiger', 'Calvin Klein']", "featured_promos": "['Extra 30% off with code VIP']", "scraped_timestamp": "2026-10-10T08:15:00Z"
| # | category_id | category_name | breadcrumbs | product_count | top_brands | featured_promos |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the complexities of the Macy's platform: variant matrices, promotional pricing logic, and inventory availability across physical and digital channels.
Extract titles, descriptions, materials, care instructions, and brand metadata across all departments.
Track complex matrices of colours, sizes, and widths mapped to individual SKUs and stock levels.
Capture sale prices, promo codes, limited-time offers, and baseline retail prices simultaneously.
Scrape customer feedback, star ratings, fit metrics, and verified purchase flags for product research.
Check click-and-collect availability across Macy's retail locations using specific zip codes.
Track assortment size, pricing, and promotional inclusion for specific designers or private labels.
Map category hierarchies, shelf-share metrics, and search ranking positions for key terms.
Download high-resolution product imagery, colour swatches, and lifestyle photos.
Run pipelines at daily or hourly frequencies to catch flash sales and inventory restocks.
Brief in. Clean data out.
Provide category URLs, brand names, or search terms. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for macys.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Macy's employs strict perimeter defenses and complex frontend rendering. We handle the infrastructure so you receive clean data.
Bypass Akamai and perimeter defenses using residential ISP proxies with realistic browser fingerprints and automated session management.
Execute React components to hydrate pricing, inventory availability, and promotional badges that static parsers miss.
Flatten multi-dimensional colour and size matrices into relational records, ensuring every SKU is tracked accurately.
Compare current state against historical hashes to emit only pricing and inventory diffs, reducing processing overhead.
Alert on schema drift or missing promotional fields automatically, maintaining data integrity across site updates.
Monitor promotional cadences, discount depths, and baseline pricing across the department store sector.
Analyse brand coverage, category depth, and size availability to inform retail buying decisions.
Audit MAP adherence, promotional exclusion lists, and brand representation on the Macy's storefront.
Track new arrivals, out-of-stock rates, and review velocity to identify emerging fashion trends.
Feed structured apparel descriptions, material compositions, and images to machine learning models.
Compare Macy's pricing and inventory availability against other major department stores and direct-to-consumer brands.
"Macy's digital storefront contains critical signals for apparel pricing and brand assortment, requiring resilient pipelines to extract reliably."
Extracting retail data at scale requires navigating complex variant matrices, dynamic promotional pricing, and aggressive anti-bot perimeters. DataFlirt manages this infrastructure entirely, ensuring your data warehouse receives clean, normalised records without the operational overhead.
Everything supported by our Macy's 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 executes JavaScript to expose dynamic pricing and inventory data.
US-based residential ISP proxies rotate per request to bypass perimeter defenses and maintain high success rates.
Pipelines execute on AWS infrastructure with Airflow managing scheduling, dependencies, and delivery SLAs.
Data delivered to where your team already works — no new tooling required.
About Macy's scraping, legality, and pipeline operations.
Ask us directly →Yes. Our pipeline iterates through the product variant matrix to capture specific prices, promotional eligibility, and inventory status for every unique SKU.
We extract publicly advertised promo codes from banners and product pages, applying the discount logic to calculate the final consumer price alongside the baseline retail price.
Yes. By providing a list of target zip codes, we can query local store inventory systems to determine click-and-collect availability for specific products.
We support daily, hourly, or custom schedules. High-priority categories can be monitored continuously for flash sales or stock changes.
Yes. We paginate through the entire review corpus, extracting ratings, text, helpful votes, and verified buyer status.
Data is normalised into consistent schemas. Complex variant matrices can be delivered as nested JSON arrays or flattened into individual rows for CSV and Parquet formats.
20-minute scoping call. Pilot dataset within the week. Production within two. From targeted category tracking to full catalogue extraction, we build and operate the infrastructure. Define your requirements today.
