Scraping general online stores in the United States — price & assortment monitoring
Department and multi-category stores in the United States: catalogs, prices and stock across all departments.
Multi-category retail in the United States is a convenient analytics entry point: one collection covers several product verticals. Scraping lays the assortment out along the category tree with prices, discounts and stock.
There are 25 platforms here, led by Walmart, Target, Costco by domain authority. Site size is not a constraint: catalogs with hundreds of thousands of SKUs and small stores are normalized to the same field schema, making sellers directly comparable.
Shelves in this list carry Nike, Levi's, Dyson, Samsung, KitchenAid, Ralph Lauren and other brands — every product is linked to its brand in the feed, so you can track brand presence and pricing across sellers.
Delivery is tailored to the task: from a one-off Excel/CSV file to a stream of updates via API or into your DBMS. We start with a free data sample — you verify structure and quality before any payment.
Fields we collect: General / Department
The baseline set for this category — extended to fit your task.
title, brand, category with tree path, URL
current and old price, discount, promo
sizes, colours, versions — where applicable
status, stock, delivery times
card attributes according to product type
rating and review count
Jobs this scraping gets done
Competitor prices across several departments at once.
The category tree and each department’s saturation.
Discount campaigns and their depth by department.
New categories and products as they appear.
Stores in this category in the United States
Ranked by domain authority — price scraping and scheduled price monitoring are available for any platform below.
| # | Store | DR |
|---|---|---|
| 1 | Walmart |
92 |
| 2 | Target |
91 |
| 3 | Costco |
86 |
| 4 | Nordstrom |
86 |
| 5 | Macy's |
85 |
| 6 | Kohl's |
82 |
| 7 | Sam's Club |
82 |
| 8 | Staples |
82 |
| 9 | Bloomingdale's |
81 |
| 10 | Office Depot |
81 |
| 11 | Neiman Marcus |
80 |
| 12 | Saks Fifth Avenue |
80 |
| 13 | JCPenney |
78 |
| 14 | Meijer |
78 |
| 15 | QVC |
78 |
| 16 | Dollar Tree |
77 |
| 17 | Woot |
77 |
| 18 | BJ's Wholesale Club |
76 |
| 19 | Dillard's |
76 |
| 20 | HSN |
75 |
| 21 | Belk |
74 |
| 22 | Five Below |
72 |
| 23 | Marshalls |
72 |
| 24 | Big Lots |
71 |
| 25 | T.J.Maxx |
60 |
DR (Domain Rating) — domain authority on a 0–100 scale; it reflects link-profile strength, not sales.
Top platforms: what gets scraped
Quick notes on the leaders of this list — any of them can be plugged into the same field structure.
For Walmart we set up recurring collection: product, prices, variants. Cadence ranges from a one-off export to several refreshes a day.
From Target we usually extract prices, variants, availability. The export arrives in the same structure as the rest of this list, so the data compares directly.
On Costco we track the catalog and prices — variants, availability — one-off or on a schedule. Delivered as a file, via API or straight into your database.
For Nordstrom we set up recurring collection: availability, attributes, reviews. Cadence ranges from a one-off export to several refreshes a day.
On Macy's we track the catalog and prices — attributes, reviews — one-off or on a schedule. Delivered as a file, via API or straight into your database.
From request to first delivery
Scope the task
We fix the stores, fields, catalog depth and refresh frequency.
Free sample
A data fragment in the agreed structure — before any payment.
Collect & validate
Full collection with completeness and consistency checks.
Deliver & refresh
File, API or database — refreshed on your schedule.
Frequently asked questions
Can we collect only part of the catalog?
How do you handle heterogeneous department attributes?
Is the feed comparable with niche stores?
Other categories: United States
Store scraping for other categories in the same geography.