E-Commerce Migration Risk Auditor

E-Commerce Migration Risk Auditor reviews a public online store and turns observable storefront signals into a migration complexity report. Give it one or more store URLs plus a target platform such as Shopify, BigCommerce, WooCommerce, Magento / Adobe Commerce, or Salesforce Commerce Cloud. The actor returns migrationComplexityScore, sourcePlatformDetected, detectedIntegrations, commerceSignals, migrationRisks, recommendedWorkstreams, and manualDiscoveryQuestions.

Use it before quoting, scoping, or planning an e-commerce platform migration. It helps agencies, consultants, and commerce teams run a fast public assessment before they receive admin access, app exports, analytics access, or catalog files.

This is a public-signal migration auditor. It does not log in, read private app lists, access order/customer data, or guarantee that every plugin or custom integration is visible from the storefront.

Why use this actor

Platform migrations are often underestimated because hidden work lives in apps, checkout rules, analytics tags, product data, redirects, policies, and custom storefront behavior. A simple technology lookup is not enough to quote or prioritize a migration.

Use this actor to answer how complex a migration looks, which platform is likely in use, which visible tools need replacement, and what discovery questions should be asked before a fixed quote.

What it produces

Each store produces one dataset row with platform confidence, migrationComplexityScore, complexityLevel, readinessLevel, visible integrations, integration categories, commerce signals, migration risks, recommended workstreams, discovery questions, component risk fields, and compact observable evidence.

Use cases

Commerce agencies can pre-qualify prospects and avoid under-scoping migrations that include subscriptions, review apps, complex tracking, checkout replacement, or large URL inventories.

Platform consultants can create a repeatable discovery checklist before asking a client for admin access.

Merchants and e-commerce teams can compare stores in a portfolio and decide which migrations need deeper discovery first.

SEO and analytics teams can flag redirect, structured data, product URL, and tracking risks before launch planning starts.

How to use

1. Add one or more storefront URLs in storeUrls.
2. Choose the likely targetPlatform.
3. Leave knownSourcePlatform on auto unless you already know the current platform.
4. Run the actor and review the score, risk fields, workstreams, and discovery questions.

Input

{
  "storeUrls": [
    { "url": "https://webscraper.io/test-sites/e-commerce/static" }
  ],
  "targetPlatform": "shopify",
  "knownSourcePlatform": "auto"
}

Field	Required	Description
storeUrls	Yes	Public e-commerce store homepages or major storefront entry points. Each store produces one output row.
targetPlatform	No	Target migration platform. Defaults to shopify.
knownSourcePlatform	No	Optional current platform if you already know it. Use auto for public detection.
proxyConfiguration	No	Optional Apify Proxy settings for storefronts that block datacenter traffic or show regional pages.
datasetId	No	Optional existing Apify dataset ID. Results are appended there as well as to the default dataset.
runId	No	Optional workflow, client, or CRM ID copied into output rows.

Output example

{
  "storeUrl": "https://example-store.com/",
  "finalUrl": "https://example-store.com/",
  "domain": "example-store.com",
  "sourcePlatformDetected": "WooCommerce",
  "sourcePlatformConfidence": "high",
  "targetPlatform": "shopify",
  "migrationComplexityScore": 74,
  "complexityLevel": "high",
  "readinessLevel": "scope_before_quote",
  "estimatedDiscoveryEffort": "multi-workstream discovery before fixed scope",
  "detectedIntegrations": ["Klaviyo", "Stripe", "Google Tag Manager", "Meta Pixel", "Yotpo"],
  "integrationCategories": ["email_crm", "payments", "analytics_ads", "reviews_loyalty"],
  "commerceSignals": [
    "product structured data visible",
    "product URLs visible",
    "category or collection URLs visible",
    "cart or checkout affordance visible",
    "policy/support pages visible",
    "sitemap reachable"
  ],
  "migrationRisks": [
    "Public evidence points to WooCommerce; migration to Shopify should include platform-specific data mapping.",
    "Several third-party tools are visible and should be mapped before migration.",
    "Checkout and payment behavior needs replacement testing on the target platform.",
    "Analytics and advertising tags must be remapped to preserve campaign measurement."
  ],
  "recommendedWorkstreams": ["Platform data model and URL redirect mapping", "Catalog, variants, pricing, categories, images, and product schema migration", "Checkout, payments, tax, shipping, and transactional email replacement"],
  "manualDiscoveryQuestions": ["Confirm total SKUs, variant count, bundles, gift cards, subscriptions, and custom product options.", "Export the full app/plugin list and classify each item as replace, rebuild, retire, or native target-platform feature."],
  "seoRedirectRisk": "high",
  "checkoutReplacementRisk": "high",
  "catalogMigrationRisk": "high",
  "analyticsTrackingRisk": "high",
  "policyContentRisk": "low",
  "auditedAt": "2026-08-10T12:00:00.000Z"
}

API usage

curl -X POST "https://api.apify.com/v2/acts/trovevault~ecommerce-migration-risk-auditor/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "storeUrls": [
      { "url": "https://webscraper.io/test-sites/e-commerce/static" }
    ],
    "targetPlatform": "shopify",
    "knownSourcePlatform": "auto"
  }'

Fetch dataset rows:

curl "https://api.apify.com/v2/datasets/DATASET_ID/items?clean=true" \
  -H "Authorization: Bearer $APIFY_TOKEN"

How scoring works

The actor uses public observable evidence: platform fingerprints, third-party scripts, product/category URLs, prices, checkout affordances, policy links, structured data, default robots.txt, and default sitemap.xml. The score is heuristic and designed for migration triage.

Limitations

• The actor checks public storefront evidence only.
• It does not log in, access admin panels, export app lists, read order/customer data, complete checkouts, or bypass access controls.
• It cannot guarantee a complete list of plugins, private apps, server-side integrations, ERPs, PIMs, tax tools, shipping rules, or custom middleware.
• Some sites hide scripts behind consent banners, personalization, geo-routing, bot protection, or client-side rendering.
• Results are for planning and triage, not legal, financial, or implementation certainty.

Troubleshooting

Problem	What to try
Platform is Custom or unknown	Provide knownSourcePlatform if you already know it, or rerun with proxy if the storefront blocked the request.
Few integrations are detected	Public scripts may be hidden by consent, tag managers, regional rendering, or server-side integrations. Ask for an app/plugin export.
Score seems too low	Confirm private apps, checkout rules, subscriptions, customer groups, and custom product options with the merchant.
Store blocks requests	Try Apify Proxy and use the public storefront homepage rather than an admin or checkout-only URL.

FAQ

Is this a complete migration estimate?

No. It is a first-pass public assessment. Use it to decide what to verify next, not to replace admin access, catalog exports, analytics review, or stakeholder discovery.

Can I schedule this?

Yes. Use Apify schedules and optionally provide datasetId to append repeated assessments into one dataset.

Is scraping these stores legal?

The actor visits public pages and reports observable technical and content signals. You are responsible for ensuring your use complies with applicable law, website terms, and internal policies.

Related actors

This pairs well with product scrapers, SEO metadata scrapers, AI commerce readiness auditors, and GDPR website compliance auditors.

Changelog

• 0.1.0: Initial public-signal migration risk auditor with platform detection, integration categories, component risk fields, workstreams, discovery questions, datasetId, and runId support.

Support

Open an issue on the actor page with the storefront URL, target platform, expected source platform, run ID, and the dataset row that looked wrong.