Website Tech Stack Enricher — Technographics for B2B Targeting

🎥 Video walkthrough

Give this Actor a list of domains and it tells you what each website is built with: its CMS, JavaScript framework, analytics, advertising pixels, payment processors, chat/support widget, marketing-automation platform, and CDN/hosting — plus derived signals like whether the site runs ecommerce, buys paid ads, and how sophisticated its stack is. It's a keyless, pay-per-result alternative to BuiltWith and Wappalyzer that runs in bulk and drops clean JSON/CSV/Excel straight into your workflow.

Under the hood it fetches each site's homepage (and one relevant internal page) through a US residential proxy, then fingerprints technologies from the HTML, inline and external <script> sources, <link> tags, <meta> generators, cookies, and response headers. Detection is evidence-based and conservative — a technology is only reported when there's a clear signal, so you get a low-false-positive stack rather than a wall of guesses.

Why tech-stack targeting matters for B2B sales

Technographics let you build a lead list around the exact question a good sales or partnerships team actually asks: "who uses the tools we integrate with, compete with, or complement?" A few concrete plays:

• Sell an app or agency service to a specific platform. Filter for cms = "Shopify" to find every Shopify store in a list, or hasEcommerce = true to find online retailers worth pitching a CRO/ads/fulfilment service to.
• Displacement selling. Looking for companies on a competitor's tool? Filter technologies for Intercom, Zendesk, Mailchimp, Marketo, etc. and pitch your alternative to accounts that already pay for that category.
• Qualify by spend & maturity. hasPaidAds = true (a Google/Meta/TikTok/LinkedIn pixel is present) means the company already spends on acquisition — a warm signal for ad, analytics, and landing-page tools. sophisticationTier ("basic" / "growing" / "advanced") lets you route enterprise-y stacks to sales and thin stacks to self-serve.
• Integration & partnership discovery. Find accounts running Stripe, HubSpot, Segment, or Klaviyo when your product plugs into those.
• Enrich an existing CRM. Push a column of account domains through this and append a technographic profile to every row.

Categories detected

Category	Example technologies
CMS / site builders	WordPress, Shopify, Wix, Webflow, Squarespace, Drupal, Joomla, Ghost, HubSpot CMS, Contentful, Sanity
Frameworks / frontend	React, Vue, Angular, Next.js, Nuxt, Svelte, Gatsby, Ember
Analytics	Google Analytics (GA4 & UA), Google Tag Manager, Segment, Mixpanel, Amplitude, Hotjar, Plausible, Fathom, Matomo, Heap, PostHog
Advertising / pixels	Google Ads, Meta Pixel, LinkedIn Insight, TikTok Pixel, Twitter/X Pixel, Pinterest, Snap, Bing/UET, Reddit, DoubleClick
Payments	Stripe, PayPal, Braintree, Square, Shopify Payments, Adyen, Klarna, Razorpay
Chat / support	Intercom, Drift, Zendesk, Crisp, Tawk.to, LiveChat, Freshchat, Olark, Gorgias
Email / marketing	Klaviyo, Mailchimp, HubSpot, Marketo, ActiveCampaign, ConvertKit, Pardot, Drip, Braze, Omnisend
Ecommerce platforms	WooCommerce, Magento, BigCommerce, PrestaShop, Salesforce Commerce
CDN / hosting / infra	Cloudflare, Fastly, CloudFront, Akamai, Vercel, Netlify, AWS, Nginx, Apache, IIS, LiteSpeed, WP Engine, Kinsta

Input

{
  "domains": ["stripe.com", "shopify.com", "notion.so"],
  "maxConcurrency": 5,
  "fetchExtraPage": true
}

• domains (required) — list of domains or URLs. Scheme, www., and paths are normalized away.
• maxConcurrency — how many domains to analyse in parallel (default 5, max 20).
• fetchExtraPage — also fetch one internal page (/pricing, /products, /checkout, /contact…) to catch payment/chat/marketing scripts that only load off the homepage. Default true; set false for a faster homepage-only pass.

Output

One record per domain:

{
  "domain": "shopify.com",
  "url": "https://www.shopify.com/",
  "technologies": [
    { "name": "Cloudflare", "category": "cdnHosting" },
    { "name": "Google Analytics (GA4)", "category": "analytics" },
    { "name": "Google Tag Manager", "category": "analytics" },
    { "name": "React", "category": "frameworks" },
    { "name": "Shopify", "category": "cms" }
  ],
  "categoriesSummary": {
    "cms": "Shopify",
    "frameworks": ["React"],
    "analytics": ["Google Analytics (GA4)", "Google Tag Manager"],
    "advertising": [],
    "payments": [],
    "chat": [],
    "marketing": [],
    "cdnHosting": ["Cloudflare"]
  },
  "techCount": 5,
  "hasEcommerce": true,
  "hasPaidAds": false,
  "sophisticationTier": "growing",
  "scrapedAt": "2026-07-03T00:00:00.000Z"
}

Field reference

Field	Meaning
domain	Normalized domain analysed.
url	The final URL fetched (after redirects).
technologies	Flat, deduped list of { name, category } for every detected technology.
categoriesSummary	The stack grouped for easy filtering: single best cms, plus arrays for the other categories.
techCount	Number of distinct technologies detected.
hasEcommerce	true when a store platform (Shopify/WooCommerce/Magento/BigCommerce/…) is present.
hasPaidAds	true when at least one advertising pixel/tag is present — the site runs paid acquisition.
sophisticationTier	basic / growing / advanced, from tech breadth plus presence of paid-ads and marketing-automation tooling.
scrapedAt	ISO timestamp of the scan.

A ready-made table view ships with the Actor (domain, tier, tech count, ecommerce, paid-ads, CMS, technologies) so the dataset is readable at a glance and trivially consumable by an LLM agent.

The find → enrich workflow

This Actor is the technographic layer of a lead pipeline. Combine it with its siblings to go from "a domain" to "a qualified, contactable account":

1. Find domains — start from any list of company domains (a scrape, a CRM export, an ICP list).
2. Profile the stack (this Actor) — attach the technologies, ecommerce/paid-ads flags, and sophistication tier so you can segment and prioritise.
3. Enrich the company — run Company Enrichment to add industry, size signals, description, and decision-maker names for the accounts that pass your tech filter.
4. Find the contact — run Website Contact Finder to pull emails, phones, and social profiles for outreach.

Filter at step 2, then only spend enrichment/contact credits on the accounts that match your technographic ICP.

Honest note on detection

Detection is signal-based and best-effort, exactly like every client-side technographics tool (BuiltWith and Wappalyzer included). It reads what a website exposes to a browser: markup, script/link URLs, meta tags, cookies, and headers.

• Some technologies are deliberately invisible from the outside (server-side-only tools, tag-managed scripts that fire after consent, self-hosted/proxied assets, first-party-domained bundles) and won't be detected.
• We favour precision over recall — when in doubt we don't flag a tech, to keep false positives low. That means the stack we return is trustworthy but not necessarily exhaustive.
• Enabling fetchExtraPage meaningfully improves recall for payments and chat, which frequently only load on inner pages.

Treat the output as a strong, structured signal for segmentation — not a legal audit of a company's infrastructure.

FAQ

Do I need a BuiltWith or Wappalyzer API key? No. This is fully self-contained and keyless — it inspects each site directly. You only need an Apify account to run it.

How is this different from BuiltWith? Same idea (technographics), different economics and ergonomics: you pay per enriched domain instead of a monthly seat, it runs in bulk on your own domain lists, routes through residential proxies, and returns schema-stable JSON/CSV/Excel with derived flags (hasEcommerce, hasPaidAds, sophisticationTier) built for lead segmentation.

Why do some big sites return only a few technologies? Sophisticated sites often serve first-party-domained, tag-managed, or consent-gated scripts that hide third-party fingerprints, and route everything through their own CDN. We report only what we can see with confidence. Turning on fetchExtraPage usually surfaces more.

Can it detect a specific tool, like "all sites using Klaviyo"? Yes — run your domain list, then filter the dataset where technologies contains the tool (Klaviyo, Intercom, Stripe, Shopify, etc.). That filtered set is your target list.

What about rate limits and blocking? Requests go through Apify's residential proxy with a User-Agent and a proxy-rotation retry on transient failures, which handles most datacenter blocks. Keep maxConcurrency modest on very large lists.

Is it agent / automation friendly? Yes. No auth, no browser step, deterministic structured output with a table view — ideal to call as a tool from an LLM/agent or wire into a pay-per-call workflow.

Automate it

Set a schedule in Apify to re-profile a watchlist of accounts (catch when a prospect adds Stripe, switches to Shopify, or turns on a Meta Pixel — all buying signals), and connect the dataset to a webhook, Google Sheet, Slack, or your CRM. Chain it after a domain-finder and before Company Enrichment + Website Contact Finder to run a full, hands-off technographic lead pipeline with zero infrastructure to maintain.

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Detection is signal-based and best-effort. This Actor is not affiliated with BuiltWith, Wappalyzer, or any of the technologies it detects.