WooCommerce store database: the full guide

What a WooCommerce store database actually is

A WooCommerce store database is a structured list of stores that run WooCommerce, with the facts about each store — domain, country, technologies, contact channels — in one searchable file. WooCommerce itself is the ecommerce plugin that turns a WordPress site into a store, so a WooCommerce database is, in practice, a filtered view of WordPress-based stores that sell online. The value is not the domain names by themselves. It is the verification and enrichment around each row: proof that the store is live, proof that it runs WooCommerce, and the signals that let you filter a very large list down to the stores that match your market.

Buyers usually search a store database for one of three reasons: to find prospects to sell a service, plugin or app to, to research a niche or a competitor set, or to build an outreach list. The same filters — platform, country, technology, contact availability — power all three. If a database cannot tell you how each store was verified and when it was last seen, treat its counts as marketing, not data. A useful WooCommerce list therefore starts with method, not with a headline total.

What each record contains

In OpenData, every store record carries the domain, detected platform, country, the technologies and apps found on the storefront, and the date the store was last observed. Each record also keeps a per-record source URL, so any row can be traced back to the page it came from. Where a store publishes them itself, the record can include a public business email or a store-published business phone. That traceability is what makes a record usable: you can check a row against its source instead of taking it on trust.

Two limits are worth stating plainly. First, contact data is public business facts only: business emails such as info@, sales@ or support@ that a store publishes for customers — never private addresses, and never bought or copied third-party data. Second, contact coverage is partial by nature: 205,297 verified stores have a public business email and 111,859 have a store-published business phone. A database claiming a contact for every row is inventing data. If a store asks to be removed, OpenData honours removal within 48 hours and suppresses the record permanently.

• Domain and country for every store
• Detected platform and storefront technologies
• Per-record source URL and last-observed date
• Public business email where the store publishes one (205,297 stores database-wide)
• Store-published business phone where available (111,859 stores database-wide)

How stores are detected and verified

Verification separates a database from a scraped list of domains. OpenData counts a store as verified only when its storefront has been fetched and at least one ecommerce technology detected on it. That rule removes parked domains, dead sites, and pages that merely mention shopping. One store counts as exactly one record, never several rows for the same shop, and stores are re-checked before packaging so a list does not ship with rows that have already gone stale.

The scale behind the numbers: OpenData tracks 1,554,041 domains in total, and 1,504,744 of them pass the verified bar in the 15 Nov 2026 snapshot. For WooCommerce, OpenData does not quote a fixed total in this guide, because the slice changes as stores are re-checked; the current WooCommerce count is shown in the live catalog — check there for the figure on the day you buy. The same live catalog is the place to confirm any slice before you rely on its size.

Useful slices: by country and by technology

Almost nobody needs every WooCommerce store — the useful product is the slice matching a territory or a tech stack. By country, the United States is the largest market by far: the US country list holds 139,254 verified stores across platforms, followed by the United Kingdom at 5,957, Brazil at 5,675 and Germany at 3,332. If you sell into one market, start from the United States store list or browse the stores by country index and narrow to WooCommerce there.

By technology, slices answer questions like "which WooCommerce stores run this payment or analytics tool?" WordPress — the platform WooCommerce runs on — appears as a 15,382-store technology slice, while PayPal appears in 11,371 stores and Apple Pay in 11,065, all database-wide figures that the platform filter narrows to WooCommerce. Larger technology slices in the same catalog include Cloudflare at 141,204 stores and React at 81,205. Explore them at stores by technology before deciding which cut to buy.

What a WooCommerce list costs

OpenData sells its records per row — there are no subscriptions and no fixed packages. A WooCommerce slice is priced like every other filter: full records $4.00 per 1,000 rows, platform-only records $1.00 per 1,000 rows. Checkout is by PayPal, and the export starts right after payment. The index is refreshed monthly, and every paid pull is fingerprinted per buyer under a no-redistribution licence. Full details are on the pricing page.

Vendor prices put that in context. The figures here are vendor-reported, checked 2026-11-15: Store Leads charges $75/mo for search-only access, with export from $250/mo, and reports ~13.8M stores; BuiltWith Basic is $295/mo and Wappalyzer Pro is $250/mo. Those are recurring tools, priced per month; OpenData charges per row instead. Our comparison page sets out the differences, and developers who prefer an API can start from the developer pages, including RapidAPI Basic at 1,000 free requests a month, capped at 50 rows per request.

• Pay per row for WooCommerce records — no subscription
• PayPal checkout with download immediately after payment
• Index refreshed monthly; every paid pull exports CSV plus a formatted Excel file
• One free sample file per industry on the sample page

How buyers actually use it

Agencies use a WooCommerce store database as a prospecting base: filter by country and technology, and the result is a list of stores that plausibly need design, marketing, development or plugin work. Plugin and app developers size the installed base of a competing or complementary tool, then target stores whose stack matches their integration. Lead generators and freelancers work the contact-bearing rows: stores with a public business email or phone are the ones a small team can realistically handle by hand.

The common thread is filtering before outreach. A very large list is a research asset; a filtered cut of a few thousand stores in one country running one technology is a work plan. Buyers who skip filtering and blast the whole file get poor results from any database, ours included — relevance, not volume, is what converts. A sensible sequence is to check a handful of stores you know in the free store checker, read the sample file on the sample page, then buy the smallest matching slice. If the spot-checks are accurate, the database has earned the purchase; if not, you have spent nothing finding out. The Shopify store database guide covers the same method for the largest platform slice, at 269,688 verified Shopify stores.

Questions, answered straight

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