Pilot dataset — 41,619 stores indexed, growing weekly

Every ecommerce store, one open database.

OpenData is a global database of ecommerce stores for teams selling into online retail. Filter stores by platform, installed apps, payment gateways, market and public business contact availability — with especially deep coverage across Southeast Asia.

Global storefrontsShopify, WooCommerce, Magento, Wix and BigCommerce
SEA payment depthGCash, OVO, DANA, PromptPay, QRIS, Xendit and Midtrans
Exports includedCSV export from the $29 plan — not locked behind a $250 tier

Free store checker

Paste a storefront URL to preview the kind of signals OpenData records.

DEMO

Demo mode: known demo domains return labelled sample detections; any other valid domain returns a generic demo result. No live scan is performed on this static page.

Demo result

SAMPLE
Platform—
Frontend / stack—
Payments—
Pilot index41,619Stores indexed so far — and growing weekly. We publish the real count, not a projection.
Detection library283 signalsStorefront, commerce, marketing, analytics and payment fingerprints.
Launch platforms5 core platformsShopify, WooCommerce, Magento, Wix and BigCommerce.
Refresh rhythmWeekly targetRechecks prioritise active stores and detected technology changes.

Build a list that matches your sales motion.

Do not buy a generic dump of websites. Start with the stores that can actually use, integrate with or resell your product.

Platform: Shopify or WooCommerce Market: Singapore · Malaysia · Indonesia · Thailand · Philippines Payments: GCash · QRIS · PromptPay · Xendit Installed app: Reviews / loyalty / subscriptions Contact: Generic business email available
⌕

Composable store filters

Combine platform, country, language, currency, payment gateway, technology and installed-app filters instead of cleaning a spreadsheet by hand.

▦

Installed-app intelligence

See signals for reviews, loyalty, subscriptions, chat, search, upsells and other storefront apps so your outreach can reference the store's real setup.

◉

Change alerts

Watch target segments for platform migrations, newly detected payment methods, app installs and storefront technology changes.

↻

Weekly refresh

Active stores are rechecked on a weekly target cycle. Every record keeps a source URL and observation date so your team can audit where a signal came from.

@

Business contacts, responsibly

Paid exports can include publicly listed generic business mailboxes such as sales, support or contact addresses. Sample files keep contact details hidden.

⬇

Clean CSV exports

Download deduplicated store records with the fields your CRM needs — no oversized, messy technology dump to repair before outreach.

How detection works — and what it cannot see. OpenData reads public storefront pages and records only the signals those pages actually expose: platform markers, app code, payment buttons, analytics and CDN fingerprints. Apps that run only inside a store's admin, checkout-only extensions and email tools leave no storefront trace — no outside tool can see them, and we never guess. Every detection keeps its evidence and observation date.

Built for teams that sell to stores.

Four teams use store intelligence the same way: find the right stores, skip the rest.

▣

App developers

Find stores on your platform that have not installed your app yet — or that just installed a competitor's.

✦

Agencies

Research a niche before pitching: which stores run which stack, in which market, at what scale of tooling.

⬢

Payment & logistics teams

Spot stores missing your gateway or shipping option — especially across Southeast Asia's local payment rails.

⌁

Market researchers

Track platform and app adoption by country and category with dated, auditable records instead of anecdotes.

Sample store records

These are illustrative sample rows, not a live extract. Business email values are fully hidden in every public sample.

Sample storeMarketPlatformPayments detectedInstalled-app signalsBusiness email
Sample Beauty Store 01Health & beauty storefrontSingaporeShopifyStripe · PayPalReviews · Loyalty🔒 Available
Sample Fashion Store 02Apparel storefrontMalaysiaWooCommerceXendit · CardsSubscriptions · Search🔒 Available
Sample Electronics Store 03Consumer electronicsIndonesiaMagentoMidtrans · QRIS · OVO · DANALive chat · Upsells🔒 Available
Sample Home Store 04Home & livingThailandShopifyPromptPay · CardsReviews · Bundles🔒 Available
Sample Grocery Store 05Specialty foodPhilippinesWooCommerceGCash · Maya · CardsLoyalty · Delivery slots🔒 Available
Sample Sports Store 06Sporting goodsUnited StatesBigCommerceStripe · KlarnaProduct recommendations🔒 Available
Sample Pet Store 07Pet suppliesAustraliaWixPayPal · AfterpayBookings · Subscriptions🔒 Available

Get the sample CSV

Enter a valid work email to unlock the sample. Free webmail addresses are not accepted for this B2B sample. The request is saved in this browser with a timestamp.

Sample request history on this device

    No sample requests recorded yet.

    What the full record adds

    Paid records are designed to include the store domain, platform, market signals, detected technologies and apps, payment gateways, public generic business contact where available, source URL and last-observed date.

    Records are not copied from another vendor's database. OpenData collects public storefront signals itself and keeps provenance for audit and removal.

    Compare plans
    Check stores while you browse. The free OpenData browser extension reads the storefront signals on any store you visit — platform, apps and payment clues — using the same on-device detection as this page. No account needed for a quick look.

    Simple pricing for focused prospecting.

    Lower overhead, a narrower dataset and self-serve exports — built for independent app teams, agencies and regional expansion teams. Every plan includes CSV exports; no plan hides them behind an enterprise tier.

    Starter

    $29/month

    For validating a niche and building your first targeted store lists.

    • Core global store search
    • Platform, country and payment filters
    • Sample and CSV exports included
    • Weekly refresh target
    • Public business contact availability flags
    Start with the sample

    Public business data only. Removal is permanent.

    OpenData is designed around public storefront facts, self-collected records and fast suppression. If your business appears in the dataset, you can request removal.

    Request data removal

    Use a business email and the store domain to remove. This demo form stores the request locally in your browser; production requests are reviewed against the suppression list.

    Removal requests on this device

      No removal requests recorded yet.

      Frequently asked questions

      Straight answers about what OpenData contains, where records come from and how removal works.

      What data does a store record contain?

      A record is designed to include the store domain, platform, market signals, detected technologies, installed-app signals, payment gateways, public generic business contact availability, source URL and last-observed date.

      Where does the data come from?

      OpenData discovers candidate stores from public web indexes and scans public storefront pages itself. It does not purchase or copy another vendor's proprietary database.

      How fresh is the data?

      The operating target is a weekly refresh for active stores, with more valuable segments prioritised. Each record should carry the date it was last observed so users can judge freshness for themselves.

      Why are emails hidden in the sample?

      Public samples are deliberately redacted. An “Available” marker shows that a generic business contact is present in the full record without exposing the address in a downloadable demo file.

      How do I remove my business?

      Submit the removal form with the store domain. Valid requests are targeted for completion within 48 hours and the domain is added to permanent suppression so it is not intentionally re-added.

      Why is OpenData cheaper than BuiltWith or Store Leads?

      It launches with a narrower self-serve product, lower overhead and a focused store dataset rather than decades of web-wide history and enterprise features. The trade-off is explicit: less historical depth, but a lower price and stronger focus on ecommerce stores and Southeast Asian payment signals.