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Pay per event
361sport Running Product Catalog Scraper
Scrape 361ยฐ's complete running shoe and apparel catalog from 361sport.com โ the global Shopify storefront of the Asian Games-endorsed sportswear brand. Extracts product names, prices, sizes, colors, technologies, variants, and stock status for running shoes and run-apparel SKUs.
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Pay per event
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19 days ago
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Scrape 361ยฐ's complete running shoe and apparel catalog from 361sport.com โ the global Shopify storefront of the Asian Games-endorsed sportswear brand. Extracts full product data including prices, sizes, colors, technologies, variants, and stock status for every running shoe and apparel SKU.
What it does
The actor calls Shopify's public /products.json API to paginate the entire 361sport.com catalog (~363 SKUs across all categories). For each product it extracts:
- Product ID, handle, name, and canonical URL
- Category (running-shoes, apparel, basketball-shoes, accessories, slides) and Shopify
product_type - 361ยฐ model line name (Spire, Meraki, Flame, BIOSPEED, etc.)
- Current price and original MSRP in USD, plus an
on_saleflag - Available sizes and colors
- Full SKU variant list (id, sku, price, availability, options)
- All product image URLs
- Full
body_htmldescription and a parsedfeaturessentence array - Extracted 361ยฐ technologies (QU!KFOAM, PEBA, CQT, carbon plate, etc.)
- Heel-to-toe drop and stack height in mm (regex-parsed from description when stated)
- Weight in grams from Shopify variant data
- Inferred
shoe_type(road, trail, training, racing) from product type and tags - Launch year from
published_at - All Shopify product tags
Use cases
- Price monitoring and competitive analysis against Saucony/Brooks/ASICS at the same tier
- Product catalog snapshots for inventory research
- Running shoe feature comparison (drop, stack, technology)
- Market research for the growing US/EU 361ยฐ customer segment (Believe in the Run / Doctors of Running audience)
Input
| Field | Type | Description |
|---|---|---|
maxItems | integer | Maximum number of records to scrape (required; use 0 or omit for all ~363 products) |
productTypes | array | Optional filter โ e.g. ["running shoes"] to return only running shoes. Default: all product types. |
Example โ scrape all running shoes:
Example โ full catalog snapshot:
Output
Each record in the dataset represents one product. Array fields (sizes, colors, sku_variants, images, features, technologies, tags) are JSON-encoded strings.
| Field | Type | Description |
|---|---|---|
product_id | string | Shopify product ID |
product_handle | string | Shopify URL handle |
product_name | string | Full product title |
product_url | url | Canonical product page URL |
category | string | Top-level category: running-shoes, apparel, basketball-shoes, accessories, slides, other |
subcategory | string | Shopify product_type value |
shoe_model_line | string | 361ยฐ model-line name (Spire, Meraki, Flame, BIOSPEED, etc.) |
price_usd | number | Current listing price in USD |
price_original | number | Compare-at (MSRP) price in USD |
currency | string | Always USD for 361sport.com |
on_sale | boolean | True when price_usd is below price_original |
sizes | string | JSON array of available size values |
colors | string | JSON array of available color values |
sku_variants | string | JSON array of variant objects |
in_stock | boolean | True if any variant is available |
images | string | JSON array of product image URLs |
description_html | string | Full product description HTML |
features | string | JSON array of parsed feature sentences |
technologies | string | JSON array of 361ยฐ technology names |
shoe_drop_mm | number | Heel-to-toe drop in mm (null if not stated) |
shoe_stack_mm | number | Stack height in mm (null if not stated) |
weight_g | number | Weight in grams from Shopify variant data |
shoe_type | string | Inferred usage type: road / trail / training / racing |
launch_year | integer | Year of first publication |
tags | string | JSON array of Shopify product tags |
Performance
- No proxy required โ plain Shopify JSON API
- Full catalog (~363 products) completes in under 60 seconds
- Memory: 256 MB
