Nordstrom Scraper
Scrape Prices and Availability from Nordstrom
Extract product pricing, markdowns, size and color variants, and stock status from one of the largest US upscale department stores. Nordstrom sits behind Kasada, which serves a JavaScript challenge and blocks datacenter proxies. Scrape.do handles it automatically.
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31M Monthly Visits. Every Brand. One API.
Nordstrom is a major US upscale department-store retailer, drawing over 31 million monthly visits across designer, contemporary, and off-price Nordstrom Rack assortment in fashion, shoes, beauty, and accessories. Its mix of full-price and steep markdown pricing across premium brands carries the sale cadence, variant availability, and ratings that fashion price-intelligence scrapers track.
With Scrape.do you can track upscale fashion pricing and markdowns, compare against Saks, Macy's, and Bloomingdale's, monitor brand and assortment coverage, and capture size, color, and stock availability. All through a single API call.
Kasada. JavaScript Challenge. Handled.
Nordstrom sits behind Kasada, fronted by Fastly, which answers requests from Python requests, cURL, and datacenter proxies with a blank JavaScript challenge page instead of the real content. The challenge uses heavily obfuscated inline JavaScript with rotating cookie and script names, so a raw fetch returns a 200 with no products, prices, or markdowns, and signature-based scrapers never see the page.
Scrape.do rotates high-quality residential IPs with full browser fingerprints, executes the Kasada challenge in a real browser, and renders the JavaScript so you receive fully populated product and category HTML. You get clean pricing, variant, and availability data without maintaining proxy pools or headless browsers.
How to Scrape Nordstrom
Select a Target
Send API Request
import requests
import urllib.parse
token = "<SDO-token>"
targetUrl = "https://www.nordstrom.com/s/maeve-midi-dress/7737947"
render = "true" # set to "false" to disable JavaScript rendering
super = "true" # set to "false" to disable residential proxies
geoCode = "us"
encodedUrl = urllib.parse.quote(targetUrl)
url = f"https://api.scrape.do/?token={token}&url={encodedUrl}&render={render}&super={super}&geoCode={geoCode}"
response = requests.get(url)
print(response.text)Get HTML
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>ASTR the Label Maeve Midi Dress (Women) | Nordstrom</title>
</head>
<body>
<nav class="breadcrumb">Home / Women / Clothing / Dresses / Floral</nav>
<h1 class="product-title">Maeve Midi Dress</h1>
<a class="product-brand" href="/brands/astr-the-label">ASTR the Label</a>
<div class="price">
<span class="current-price">$51.20 – $128.00</span>
<span class="original-price">$128.00</span>
<span class="promo">Up to 60% off select items</span>
</div>
<div class="rating"><span>4.2</span><span class="count">(200)</span></div>
<div class="color-selector">Color: Blue Multi</div>
<div class="size-selector">
<button>XXS</button><button>XS</button><button>S</button><button>M</button><button>L</button><button>XL</button>
</div>
<div class="availability">In Stock</div>
<button class="add-to-bag">Add to Bag</button>
<!-- ... remaining page content ... -->
</body>
</html>
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Sounds great, but I have a few questions..
Yes. nordstrom.com sits behind Kasada, which returns a blank JavaScript challenge page to Python requests, cURL, and datacenter proxies instead of the real content. Scrape.do rotates real residential IPs with full browser fingerprints, executes the Kasada challenge, and renders JavaScript to return fully populated product and category HTML. Success rates exceed 95% on product and category pages.
You can extract product names and brands, current and original prices, markdown and sale badges, size and color variants, stock and availability status, customer ratings and review counts, and full category listings with brand, size, price, and color filters across women's, men's, beauty, shoes, and Nordstrom Rack off-price assortment.
Yes. Nordstrom serves a Kasada challenge and renders product and category details client-side, so a plain request returns a blank page with no prices. Use super=true and render=true so Scrape.do solves the challenge and executes the page JavaScript in a real browser, and set geoCode=us for US pricing and availability.
