Ecommerce Platform Profiler - Shopify, Woo, Magento

🔎 What can Ecommerce Platform Profiler do?

Give it a company domain. It reads the storefront and returns which ecommerce platform it runs on, which payment providers it loads, whether it sells subscriptions, roughly how many products it lists, and which currencies it takes. One flat row per company.

Static reads only: the homepage, the sitemap, and optionally the public cart page. No browser, no checkout, nothing submitted.

📦 What you get	⚙️ Features and integrations
🛒 Ecommerce platform the storefront runs on 💳 Payment providers, subscription and marketplace apps 📦 Catalogue size estimate, currencies and shipping destinations 🧾 22 flat fields, snake_case, one row per company	⚡ Static homepage and sitemap reads only, no browser 🎯 Confidence and evidence per detection, not a bare label 📊 Coverage per row, so a thin read is visible ⬇️ Export to JSON, CSV, Excel, HTML or XML

Bought by ecommerce app and agency sellers, payments and subscription vendors, and anyone whose ICP is defined by the platform a storefront runs on.

🚫 This is not a product or price scraper. It profiles the storefront's platform and apps, once per company. It does not extract catalogues, product pages, prices or inventory.

💡 Why use Ecommerce Platform Profiler?

It answers the question instead of handing you a list. Generic technology detectors return every script on the page and leave you to work out which entry is the ecommerce platform. This returns shopify, with the evidence type and a confidence that follows that evidence.

It refuses to guess. A storefront that only reveals its platform after JavaScript runs reports not_extractable. It never returns the nearest plausible label, and a platform column full of confident wrong answers is worse than one with honest gaps.

Catalogue size is marked as an estimate and its source is on the row. A real read of the products endpoint and a count of sitemap URLs are not the same measurement and are never presented as if they were.

It joins the rest of the fleet on company_domain, including the Pinterest brand presence mapper, so a consumer brand list can carry social reach and commerce stack in one table.

🧭 One read, several fingerprints

1. Read the storefront homepage with its response headers, which is where the strongest evidence lives: powered-by: Shopify, a dwac_ cookie for Salesforce Commerce, an x-magento- header.
2. Match the fingerprint tables for platform, payment providers, subscription apps and marketplace marks. Confidence comes from the kind of evidence, not from the vendor.
3. Estimate the catalogue, from the Shopify products endpoint where the store is Shopify and from product URLs in the sitemap otherwise.
4. Optionally read the public cart page, because several buy now pay later providers load there and not on the homepage.

A storefront that answers 403 is retried once from a residential exit, and the row says whether that was needed.

📋 What data can Ecommerce Platform Profiler extract?

Every row carries 22 flat fields. These are the ones a buyer actually filters and sorts on.

Field	Type	Meaning
degraded	boolean	True when this row could not be produced normally, for example the company site was unreachable and no discovery could run. A degraded row is never charged.
degradation_reason	string | null	Why the row is degraded, in plain words. Null on a normal row.
company_domain	string | null	The company domain this row is about, normalized. Null when only a handle or a name was supplied. This is the join key across the whole Mamba Labs fleet.
company_name	string | null	The company name as supplied or derived. Improves search accuracy and is what the identity gate matches against.
ecommerce_platform	string | null	The detected platform: shopify, woocommerce, magento, bigcommerce, salesforce_commerce, squarespace_commerce, wix_stores, prestashop or commercetools. Null when nothing was detected, which on a site rendered entirely in JavaScript is a fact about the read rather than about the store. Check fetch_status before reading a null here.
platform_confidence	string | null	high, medium or low, derived from the KIND of evidence rather than asserted per platform. A vendor response header or a platform cookie is high, a script host is medium, a substring in the page HTML is low.
platform_evidence	string | null	What actually matched, for example "header" or "script_src". A detection you cannot inspect is a detection you have to take on trust.
platforms_all	string | null	Every platform whose marks appear, comma separated, when more than one does. Two platforms on one page usually means a migration in progress or a widget from another vendor, and collapsing that to one winner would throw away the evidence that tells them apart.
payment_providers	string | null	Payment and buy now pay later providers detected on the pages read, comma separated. Providers that load only inside a real checkout are invisible unless you switched checkCheckout on, so an absence here is weaker evidence than a presence.
has_subscriptions	boolean | null	True when a subscription app such as Recharge, Skio, Bold or Shopify Subscriptions was detected. FALSE means the pages were read and no subscription app was found, which is a real finding. NULL means the storefront could not be read at all.
subscription_apps	string | null	Which subscription apps were detected, comma separated.
has_marketplace	boolean | null	True when third party seller marks or a marketplace platform such as Mirakl was detected. FALSE means checked and absent. NULL means the storefront could not be read.
product_count_estimate	integer | null	An ESTIMATE of catalogue size, and the field name says so. From the Shopify products endpoint where available, which is a real catalogue read, and from product URLs in the sitemap otherwise, which counts variants, retired products and localized duplicates and cannot separate them.
product_count_source	string | null	products_json means a real catalogue read. sitemap means a URL count, which is a much rougher number. Never compare a sitemap count against a products_json count as if they measured the same thing.
product_count_exact	boolean | null	True only when the catalogue was read in full. FALSE means the count is a FLOOR: the products endpoint caps at 250 per page, so a store returning a full page has at least that many and probably more.
currencies	string | null	Currency codes offered, comma separated, read from a currency selector or from JSON-LD offers. A single currency is common and is not a failure.
ships_to	string | null	Country codes named in a shipping or country selector, comma separated. Coarse by nature: a selector lists where the store will take an order, not where it actually ships well.
pages_read	integer | null	How many pages were fetched for this company. Useful for reconciling a thin row against what it cost.
escalated	boolean | null	True when the first read was refused and a residential retry was needed. A row that needed escalation is a storefront defending itself, which is worth knowing before you plan a large batch against it.
coverage	number | null	How much of what this actor can return actually came back on this row, from 0 to 1. Computed over this actor value fields only, never over the identity or status columns. Null on a degraded row, where nothing was attempted. This is a reporting field: nothing is dropped for low coverage and no event fires on it.
fetch_status	string	ok, not_found, not_extractable, blocked, identity_mismatch, auth_failed or skipped. Read this before reading any value on the row. not_found means we looked and there is nothing there; blocked and not_extractable mean we could not look, and they must never be read as an absence.
run_date	string	ISO 8601 timestamp of this run. Social counts move, so a row without a date is a number with no shelf life.

⚠️ How to read these values. product_count_exact: false means the number is a floor, not a total. The Shopify products endpoint caps at 250 per page, so a store returning a full page has at least that many.

🛠️ How to find out what platform an online store uses

1. Put a company domain in company_domain. That is the whole setup.
2. Leave includeProductCount on unless you are running a very large batch and only need the platform.
3. Turn checkCheckout on when you specifically care about buy now pay later providers, which often load only on the cart page.
4. For a list, pass an array of objects with the same fields.

🧪 Using it in Clay

Add an Enrichment > Apify column, pick this actor, and map company_domain to your domain column.

The highest value pattern here is segmentation: filter your list on ecommerce_platform to find every Shopify merchant, then on has_subscriptions to find the ones already selling recurring, then on product_count_estimate to separate a 40 product brand from a 40,000 product retailer. Those three columns split a flat ecommerce list into genuinely different buyers.

💵 How much does it cost?

Pay per event. You are charged for output, never for input.

Event	Fires when	Price
company-checked	Once per company for which the storefront read completed and a non degraded row was produced, whether or not anything was found. A not_found row fires this event, because looking and finding nothing is a real answer and it is the work you asked for. A degraded row, where the lookup could not run at all, fires nothing.	$0.0035
platform-detected	Once per company where an ecommerce platform was identified from the evidence. Does not fire when the storefront was read and no platform marks were found, and does not fire when the storefront could not be read at all, because in neither case was a platform detected.	$0.0030
product-count-estimated	Once per company where a catalogue size was actually produced, from the products endpoint or from the sitemap. Does not fire when includeProductCount is off and does not fire when neither route yielded a number.	$0.0025

💳 What you are billed for. platform-detected fires only when a platform was actually identified. A storefront read with no platform marks, and a storefront that could not be read at all, both charge the check event and nothing more.

product-count-estimated fires only when a number was produced.

What the same coverage costs bought a la carte: The Store carries general technology detectors that return long unranked lists of every script on a page, and the buyer does the work of deciding which entry is the ecommerce platform. This actor answers the one question directly, with the evidence type and a confidence that follows the evidence, and it adds catalogue size, payment providers and subscription detection that a generic detector does not attempt. It also refuses to guess: a JavaScript rendered storefront reports not_extractable rather than the nearest label.

⌨️ Input

Field	Type	Required	Meaning
company_domain	string	no	Bare company domain, for example allbirds.com. This is the storefront that gets read, and it is the join key against every other actor in the fleet including the Pinterest brand presence mapper.
company_name	string	no	Optional but strongly recommended. It is what the identity gate checks a discovered record against, so supplying it is the single cheapest way to reduce wrong matches.
includeProductCount	string	no	When "true" (default) the catalogue size is estimated, from the Shopify products endpoint where the store is Shopify and from the sitemap otherwise. It costs one or two extra requests. Sent as a string for Clay compatibility.
includePaymentProviders	string	no	When "true" (default) the payment provider scripts loaded on the storefront are detected. Providers that load only inside a real checkout are invisible from the homepage, which is why checkCheckout exists. Sent as a string for Clay compatibility.
checkCheckout	string	no	When "true" the public cart page is also read, because several payment and buy now pay later providers load there and not on the homepage. This never adds an item, never starts a checkout and never submits anything: it is a plain read of a public URL. Costs one extra request. Sent as a string for Clay compatibility.
escalateOnBlock	string	no	When "true" (default) a storefront that answers 403 or 429 is retried once from a residential exit, because a bot challenge on a first read is common and one retry clears a fair share of them. Set "false" to fail fast and cheap. Sent as a string for Clay compatibility.
skipCache	string	no	When "false" (default) a successful lookup is cached for seven days and reused, which costs you nothing on a repeated run. Set "true" to force a fresh fetch. Sent as a string for Clay compatibility.

{
  "company_domain": "allbirds.com",
  "company_name": "Allbirds",
  "includeProductCount": "true",
  "includePaymentProviders": "true"
}

📤 Output

Exports to JSON, CSV, Excel, HTML or XML. One flat, snake_case row per company. No nested objects, so it drops straight into Clay, a spreadsheet or a warehouse table without a flattening step.

{
  "degraded": false,
  "degradation_reason": null,
  "company_domain": "allbirds.com",
  "company_name": "Allbirds",
  "ecommerce_platform": "shopify",
  "platform_confidence": "high",
  "platform_evidence": "header",
  "platforms_all": "shopify",
  "payment_providers": "apple_pay",
  "has_subscriptions": false,
  "subscription_apps": null,
  "has_marketplace": false,
  "product_count_estimate": 250,
  "product_count_source": "products_json",
  "product_count_exact": false,
  "currencies": null,
  "ships_to": null,
  "pages_read": 2,
  "escalated": false,
  "coverage": 0.71,
  "fetch_status": "ok",
  "run_date": "2026-08-22T19:23:53.897Z"
}

false versus null, and why the difference matters

false means we looked and the answer is no. null means we could not look, or the platform withheld it. They are never interchangeable in this output. If you filter for companies with no presence on this platform, filter on false, because null rows are unknown rather than absent and including them will overstate your list.

💡 Tips

• Filter on platform_confidence: high for anything that matters. High means a vendor header or a platform cookie, which is proof rather than a hint.
• has_subscriptions: false is a real finding and a good prospecting signal for anyone selling subscription tooling. Null is the missing one.
• Turn checkCheckout on for buy now pay later research. Klarna and Afterpay frequently load only on the cart page.
• Do not compare a sitemap product count against a products_json count. Check product_count_source first.
• A salesforce_commerce or commercetools result means enterprise. Those two are a size signal in themselves.

⚠️ Known limits

• JavaScript rendered storefronts are invisible to a static read. Measured on underarmour.com: a Next.js front end on Vercel with nothing about the commerce platform in the served HTML or headers. Those rows report not_extractable, which is a fact about the read and not about the store.
• Payment providers that load only inside a real checkout cannot be seen. This actor never starts a checkout. checkCheckout reads the public cart page and that is as far as it goes.
• Product counts are estimates. A sitemap carries variants, retired products and localized duplicates, and no static read separates them.
• ships_to is coarse. A country selector lists where a store will take an order, not where it ships well or quickly.
• Some storefronts refuse us. Measured on lush.com: an HTTP 403 Cloudflare challenge. The row reports blocked, which is never the same as having no platform.

❓ FAQ

Why is the platform null on a store I know is Shopify? Read fetch_status first. not_extractable means the page was read and carried no platform marks, which happens on JavaScript rendered front ends. blocked means the storefront refused us.

Does this add anything to a cart or start a checkout? No. Every request is a plain read of a public URL. checkCheckout reads the cart page; it does not use it.

Why does the product count sometimes look too high? Because it came from the sitemap, which counts variants and retired products. product_count_source tells you which route produced the number.

Can it detect two platforms at once? Yes, and platforms_all reports both. That usually means a migration in progress or a widget from another vendor, and it is information rather than an error.

Does it need a proxy or an API key? Neither by default. A storefront that refuses the first read is retried once from a residential exit automatically.

🧩 Want other GTM data?

Mamba Labs builds a fleet of GTM enrichment actors that share one flat, Clay-ready output convention, so their rows join on company_domain with no cleaning step:

🕵️ Agent Accessibility Auditor	🤖 AI Tooling Detector
📡 B2B Buying Signals Aggregator	🚀 Prospect Engine
📝 Publishing Frequency Tracker	⏩ Sequencer Lead Push
🔄 Company Change-Event Feed	🧭 Company Discovery List Builder
🏢 Company Firmographic Enricher	🪪 Company Identity Resolver
🌐 Company Social Presence Mapper	🏷️ Contact Classifier
📬 Domain Deliverability Checker	🔗 Domain to LinkedIn URL Resolver
✉️ Work Email Waterfall Finder	🎪 Event Presence Index
💰 Funding and Press Signal Scanner	🧑‍💼 GTM Hiring Signal Scraper
📋 Job Posting Monitor	🧱 Tech Stack Detector
🎯 ICP Fit Scorer	🔑 Job Board Keyword Scanner
⚖️ Legal Entity Resolver	💼 LinkedIn Company Page Mapper
💬 LinkedIn Post Tracker and Comment Capture	📸 Instagram and Facebook Brand Mapper
📮 Outbound Stack Detector	📄 Page Finder and Extractor
👤 People Finder and Email Verifier	📌 Pinterest Brand Presence Mapper
🏛️ Government Contract Award Monitor	📅 Public Company Reporting Window Finder
👥 Team Page People Extractor	🎵 TikTok Brand Presence Mapper
🏅 Workplace Program Detector	▶️ YouTube Channel Stats Extractor

Every actor in the suite takes a domain or a company and returns one flat row, so they stack in the same Clay table without reshaping anything.

🛠️ Need something custom built for you or your team? Tell us what you are trying to find and we will build it. Talk to Mamba Labs.

🆘 Support

Issues, field requests and bug reports: open an issue on the actor's Issues tab. Mamba Labs reads every one.

ℹ️ Sourcing and legal. Every field is read from the storefront's own public homepage and sitemap, with robots.txt honored. product_count_estimate is an estimate and product_count_exact tells you when it is not exact. You are responsible for how you use the output.

Built by Mamba Labs.