Kmart.com is more than a discount retailer — it’s a hybrid of an online store and a marketplace where thousands of third-party sellers list their products alongside Kmart’s own catalog. The platform still serves millions of U.S. shoppers despite Kmart’s reduced physical presence. With our Kmart scraper, you can access structured data on active listings across dozens of categories.
Our Kmart web scraper handles the entire extraction process so you don’t have to deal with tools, APIs, or dashboards. We collect exactly the information you need — from product listings to pricing and availability — directly from Kmart’s online catalog.
Whether you want full product catalogs or targeted datasets, we deliver clean, structured data in your preferred format: CSV, Excel, JSON, or any other. Fast, accurate, and ready to use — so you can focus on insights while we handle the technical side.
Here's what you can expect:
Beyond core listing details, our Kmart scraper also captures additional insights that enhance competitive understanding:
Kmart is a U.S.-based discount retail brand with a history dating back to 1962. Once one of America’s largest department store chains, Kmart has shifted its focus primarily to online retail through kmart.com.
The platform offers a wide range of products — from clothing, home goods, and toys to appliances and electronics — and combines Kmart’s own catalog with third-party sellers through the Kmart Marketplace. This hybrid model expands the assortment and provides competitive pricing across thousands of listings.
While most physical Kmart stores in the U.S. have closed, kmart.com remains active nationwide, supporting U.S. shipping and store pickup where available. Prices are displayed in U.S. dollars, the interface is in English, and the marketplace structure makes the platform relevant for monitoring both Kmart’s stock and independent seller strategies.
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Developers
Customers
Pages extracted
Hours saved for our clients
Customized scraping setup for Kmart — faster and cheaper than building a solution from scratch.
Data limits (rows): up to 10%
Iterations: up to 3
Custom requirements: Yes
Data lifetime: up-to-date
Data quality checks: Yes
Delivery deadline: 1-2 working days
Output formats: CSV, JSON, XLSX
Delivery options: e-mail
A Kmart data scraper helps you track pricing, promotions, and product availability across Kmart’s online catalog and marketplace. The same product can have different prices, discounts, or delivery options depending on the seller — insights you can’t get without structured data.
By scraping Kmart, you can monitor stock levels, analyse third-party seller strategies, compare marketplace vs. Kmart listings, and track seasonal promotions. It’s the fastest way to understand how products are positioned and priced in the U.S. discount retail space.
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ScrapeIt is a data extraction company that provides tailored services for collecting structured e-commerce information. When you need to scrape Kmart, we handle the entire process — from parsing product listings to cleaning and organizing the data.
We work with marketplaces, retail platforms, and online catalogs, delivering ready-to-use datasets in the format you prefer. You choose the scope; we take care of the rest.
Yes, we can schedule automated exports daily, weekly, or by custom intervals.
Our extractor organizes marketplace data into a structured format, so it’s easy to read, analyse, and compare.
Absolutely. We provide clean, organized product data that’s ready for immediate analysis or integration.
We collect live data directly from product pages, ensuring the information is always current and reliable.
Yes, you can target marketplace sellers separately from Kmart’s own listings.
1. Make a request
You tell us which website(s) to scrape, what data to capture, how often to repeat etc.
2. Analysis
An expert analyzes the specs and proposes a lowest cost solution that fits your budget.
3. Work in progress
We configure, deploy and maintain jobs in our cloud to extract data with highest quality. Then we sample the data and send it to you for review.
4. You check the sample
If you are satisfied with the quality of the dataset sample, we finish the data collection and send you the final result.
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