JD.com Product Scraper
Scrape JD.com (Jingdong) Product Listings to a Spreadsheet
Extract product titles, prices, review counts, shop names, and ratings from any JD.com (京东) search or category page. No code, no API — just open the page and export.
Each example shows how a live website can become a reviewable dataset inside the DataLens AI scraping workbench.
What data gets extracted
DataLens automatically detects and extracts these fields from JD.com — no selectors, no code, no maintenance.
Decision-ready dataset
What teams can decide with JD.com data
Use JD.com as a live source for an AI scraping workbench: collect the fields, clean the noisy rows, and turn the result into market, lead, content, or operations evidence.
Spot patterns
Compare listings, reviews, creators, products, or posts across the fields that matter.
Prioritize action
Move from raw rows to ranked opportunities, risks, accounts, or content ideas.
Share proof
Keep the exported file and source context ready for teammates, clients, or follow-up analysis.
How it works
- 1
Open a JD.com search results or category page in Chrome.
- 2
Launch DataLens and detect the product card structure automatically.
- 3
Export the product rows to CSV or Excel.
Frequently asked questions
Use these questions to decide how a live website becomes an AI scraping workflow.
What JD.com data can DataLens extract?
DataLens extracts product titles, current prices, review counts, shop names, and star ratings from JD.com search and category pages.
Does it work on JD.com product listing pages?
Yes. DataLens captures all visible product cards on JD.com search and category pages.
Can I scrape JD.com product reviews?
Yes. Open a JD.com product review page and DataLens will extract reviewer names, ratings, verified purchase status, and review text.
Can I export to Excel?
Yes. Export JD.com data to CSV, Excel (XLSX), or JSON for pricing analysis or market research.
Related workbench workflows
Compare adjacent collection paths by source, export format, and team job.
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