Filter 23.98M stores down to your exact ICP

The six filters that define a store ICP

Most store databases give you a search box and a credit counter. OpenData works the other way round: the signals are the product. A store record carries its platform, its detected technologies and apps, the payment gateways it takes money through, its country and currency, and whether it publishes a business email. Each of those is a filter you can apply — on the country catalog, in the technology catalog, through the API, or inside the file you buy.

That matters because ICP definitions are usually combinations, not single traits: Shopify stores, in the United States, running a specific app, with a published email. A single-trait list is a phone book; a three-filter segment is a campaign.

• Platform — Shopify, WooCommerce, Wix, Squarespace and more
• Technology — e.g. Cloudflare: 141,204 stores · React: 81,205 stores
• Installed app — the apps a store runs are detected from its storefront
• Payment gateway — including Southeast Asian gateways like GCash, QRIS and PromptPay
• Country — e.g. United States: 139,254 stores · Germany: 3,332 stores
• Has email — 205,297 stores publish a business email

Way 1: the pre-built catalog (counts before money)

The fastest ICP check costs nothing. The catalog publishes 155 pre-built segment pages — country pages, platform-by-country pages and technology-by-platform pages — each with its verified store count and a 25-row sample (first 10 domains in full, the rest masked). If your segment is already a catalog page, you can see exactly how many stores match before spending anything.

Start at the country hub or the technology hub, open your segment, and read the count. Small is not bad — a 700-store segment that matches your ICP exactly will outsell a 100,000-store generic list for almost any offer.

Way 2: filtered slices, billed per row

When a segment fits, you pull the matching slice per row — app, technology and country cuts are billed per row (full records $4 per 1,000 rows, platform records $1 per 1,000 rows), platform slices use the same rates, all with no subscription. You pull through the pricing page and export immediately as CSV plus a formatted Excel copy.

Every file carries the full 12-field record described in the column spec, including the source URL and last-observed date for each store — so you can audit any row back to the storefront it came from.

Way 3: API filters for tools and agents

If the ICP lives inside a workflow — a CRM, a scraper, an AI agent — the same filters are exposed as API parameters: platform, tech, app, gateway, country and has_email on GET /v1/stores. The API access page covers the RapidAPI and Apify routes and their free tiers.

The rule of thumb: a file when the ICP is stable and the campaign is now; the API when the ICP changes often or something non-human is doing the filtering.

Validate the segment before you buy it

Two free checks exist precisely for this. The store checker looks up any individual store (30 full-record unlocks a month on a free account), and every industry has a free sample file in the exact format of the paid lists. Run your ICP against both: if the sample rows look like your customers, the segment will too.

And if a segment turns out too broad, narrow it before buying — add the has-email filter, or intersect technology with country. The counts on the catalog pages update with each snapshot (current: 15 Nov 2026), so the number you plan against is the number that ships.

Questions, answered straight

Next steps