Ecommerce market research with real store data

Why count stores at all

Every market-entry decision rests on two questions: how much activity is already there, and how crowded is it? Surveys and analyst reports answer with modelled estimates that a solo seller or freelancer cannot audit. A store count answers with evidence. Each unit is a real storefront that was fetched and checked, and the reports page publishes the underlying warehouse counts so the arithmetic is visible. Counts will not tell you everything — the limits section below is blunt about that — but they give market research a floor of fact: this many stores demonstrably exist, running this technology, in this country, as of a stated date.

Verified vs tracked: read the headline numbers honestly

OpenData publishes two headline numbers, and confusing them inflates every conclusion downstream. Tracked — 1,554,041 domains — is everything in the database, including subdomains, redirects and domains that have not been confirmed as stores. Verified — 1,504,744 stores — is the stricter count: the storefront was fetched and at least one ecommerce technology was detected on it, and each store counts once. Use verified for sizing, always. A market sized on tracked domains would quietly include parked pages and duplicate hosts, and the error compounds when you compare two countries whose tracked-to-verified ratios differ.

Sizing a market by country

Country is the first cut most researchers make, and the country slices show how uneven the ecommerce map is. The stores by country catalogue runs from 139,254 verified stores in the United States down to 723 in Thailand. Read a country count as the supply side of that market: how many sellers you would compete with, sell to or supply. The United States is roughly 42 times the size of Germany by this measure, which says nothing about which is the better opportunity — a large count proves demand exists and that you will not be alone; a small count can mean whitespace or a market where online selling barely registers. The count frames the question. Your niche, language and shipping reality answer it.

• United States — 139,254 verified stores
• United Kingdom — 5,957
• Brazil — 5,675
• Germany — 3,332
• Indonesia — 2,868
• France — 2,612
• Spain — 2,241
• Canada — 2,111
• South Korea — 2,060
• Australia — 1,763
• Thailand — 723

Sizing by platform

Platform counts describe how a market is built, not just how big it is. Shopify is the largest single platform slice in OpenData, at 269,688 verified stores, and the snapshot breaks the rest of the database down across Wix, WooCommerce, Squarespace and more. For an app developer or agency, platform share is the market: it tells you which ecosystems have enough stores to support a product, which integrations to build first, and where a platform's growth would show up in your prospect list. Platform cuts also stay comparable over time, because the verification rule — fetched storefront, detected ecommerce technology — does not change between snapshots.

Sizing by technology and app

The third cut is the one most market research skips: what the stores run. Technology adoption is a demand signal with a denominator. OpenData's Cloudflare slice covers 141,204 stores and its React slice 81,205, and the stores by technology catalogue breaks counts down by individual apps and tools. If you sell a checkout add-on, the addressable market is not 'all Shopify stores' — it is the stores running a complementary app, in the countries you serve, minus the ones already using your direct competitor. Counting at the technology level is how a vague total-addressable-market claim becomes a number you can work a list against.

Worked example: entering Germany

Say you sell a service to online stores and are weighing Germany against staying US-only. The Germany country page gives you the starting fact — 3,332 verified stores — and the workflow below turns it into a decision. The point of the example is the order of operations: count first, segment second, inspect records third, spend last. Most failed market entries do it backwards.

• Start with the verified count: 3,332 stores is the realistic prospect universe, not a modelled estimate.
• Split it by platform to see which ecosystems dominate German stores before choosing what to build or pitch.
• Pull the free sample and spend free checker unlocks (30 per month) on individual records — check contact coverage, currencies and last-observed dates.
• Compare against the United States list (139,254 stores): if Germany's smaller count still covers your niche many times over, competition density, not size, is your real constraint.
• Decide a test budget only after the sample records survive inspection.

The limits: a store count is not revenue

Be precise about what these numbers cannot say. A store count measures supply, not money: it contains no sales figures, no traffic and no order volumes, and a verified store can be thriving or dormant — verification proves it exists and runs ecommerce technology, checked against its last-observed date. Counts also age; the figures here are the 15 Nov 2026 snapshot, and the index is rebuilt monthly because stores open and close constantly. Used inside those limits, though, store counts are the most honest starting point available to an individual researcher: every unit is a real store you can visit, and every claim built on them can be re-checked record by record.

Questions, answered straight

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