Analyze technology stacks of a website

Cold outreach without context is spray-and-pray. You pull 10,000 domains from a list purchase or a form fill, send templated emails, and achieve only a 1-2% reply rate because the pitch could be directed to anyone. The list has names, but not qualified leads.

Knowing which technology each company runs is the shortest path from a raw domain list to a list of prospects you can rank and personalize. A Shopify prospect who runs Klaviyo is a different pitch from a WooCommerce prospect who runs Mailchimp. In practice, checking each site by hand doesn’t scale past a few dozen domains. Our Domain Analytics API performs that lookup at scale, with one call per domain, so you can integrate it into a lead enrichment workflow.

What tech stack data tells you about a company

Every website runs on a stack of tools that also serve as buying signals. The CMS, ecommerce platform, marketing automation tool, analytics stack, ad networks, payment processors, and hosting infrastructure each tell you something about the company’s maturity, spend level, and integration surface.

The Domain Technologies endpoint of our Domain Analytics API returns those signals as a structured response, grouped by category. You’ll see things like:

• Sales: ecommerce platforms (Shopify, WooCommerce), payment processors, cart functionality.
• Marketing: marketing automation (Klaviyo, HubSpot), personalization tools, advertising platforms.
• Web development: JavaScript frameworks (React, Next.js), CMS platforms, static site generators.
• Servers: CDNs, web servers, hosting providers, PaaS (Vercel, AWS).
• Security: WAFs, bot management, certificate authorities.
• Add-ons: platform-specific apps, including installed Shopify apps.

Each category answers a different qualification question. Sales categories tell you whether the prospect can even use your product. Marketing categories tell you where they are in the buying journey: greenfield sale or displacement sale. Web development categories tell you how technical the buyer likely is. Next.js on a site means there’s an engineering team on the other end, not a marketer clicking through templates.

The core use case: enrich a lead list by tech match

Say you’re a B2B SaaS company selling a Shopify add-on that improves post-purchase upsells. Your ICP is “DTC brands on Shopify doing $1M+ in annual revenue.” You’ve imported a list of 10,000 domains from a data vendor. The problem: you don’t know which of them run Shopify. Cold-emailing all 10,000 is expensive and damages your sender reputation. Cold-emailing the ~2,000 who use Shopify is a completely different conversation.

Here’s the workflow:

1. Batch your domain list. Split your 10,000 domains into batches your automation can handle. In Make, n8n, or a simple Python script, you’ll iterate through them. Our Domain Technologies endpoint accepts one target per task, and you can batch multiple tasks per request.
2. Call the API. Send each domain to Domain Technologies. You get back the full detected tech stack, grouped by category (see the sample in the next section).
3. Filter for tech match. In your workflow, check the technologies.sales.ecommerce array. If it contains "Shopify", the domain is a match. If not, drop it into a lower-priority queue. You can still market to them, but not with Shopify-specific copy.
4. Enrich further. For your matched Shopify prospects, look at what else they run. Does technologies.marketing.marketing_automation include "Klaviyo"? Your outbound copy can reference how your app integrates with Klaviyo. Do they already have a personalization tool like "Rebuy"? That’s a competitive signal. You can position against Rebuy or write copy that complements it.
5. Route. Depending on how your outbound stack is set up, push the enriched leads into your tool of choice (Instantly, Smartlead, HubSpot, whatever you use) with tags for each detected technology. Your sequences can then branch on those tags to send different opening lines to Shopify-only prospects vs Shopify+Klaviyo prospects.

In practice, the whole thing runs unattended. You feed a list in, and structured leads come out, each pre-segmented with a message template ready to go.

What our Domain Analytics API returns

Here’s the request and response for deathwishcoffee.com, a well-known DTC coffee brand.

Request example:

[
  {
    "target": "deathwishcoffee.com"
  }
]

The endpoint accepts a POST request with the target domain. You can batch multiple task objects in the same array, one target per task, up to our per-request task limit.

Response example:

{
  "version": "0.1.20260701",
  "status_code": 20000,
  "status_message": "Ok.",
  "time": "0.5921 sec.",
  "cost": 0.001,
  "tasks_count": 1,
  "tasks_error": 0,
  "tasks": [
    {
      "id": "07161439-1535-0483-0000-100349d68103",
      "status_code": 20000,
      "status_message": "Ok.",
      "time": "0.5432 sec.",
      "cost": 0.001,
      "result_count": 1,
      "path": ["v3", "domain_analytics", "technologies", "domain_technologies", "live"],
      "data": {
        "api": "domain_analytics",
        "function": "domain_technologies",
        "target": "deathwishcoffee.com"
      },
      "result": [
        {
          "type": "domain_technology_item",
          "domain": "www.deathwishcoffee.com",
          "title": "#1 Organic and #1 Fair Trade Coffee\n – Death Wish Coffee",
          "description": "Bold, Smooth and Delicious since 2012. We source USDA Organic and Fair Trade Certified™ arabica and robusta coffee beans from India, Peru, and other countries throughout South and Central America for our everyday coffee roasts. Sustainably sourced coffee with high quality standards to ensure consistency in every cup.",
          "domain_rank": 322,
          "last_visited": "2026-07-15 10:38:42 +00:00",
          "country_iso_code": "US",
          "language_code": "en",
          "content_language_code": "de",
          "social_graph_urls": [
            "https://twitter.com/deathwishcoffee",
            "https://www.facebook.com/deathwishcoffee",
            "https://www.instagram.com/deathwishcoffee/",
            "https://www.youtube.com/channel/UC1uurJMded2rRJioe8yka7g"
          ],
          "technologies": {
            "servers": { "cdn": ["Cloudflare"] },
            "other": { "miscellaneous": ["HTTP/3"] },
            "marketing": {
              "marketing_automation": ["Klaviyo"],
              "personalisation": ["Rebuy"],
              "advertising": ["Simpli.fi", "theTradeDesk"]
            },
            "sales": {
              "payment_processors": ["Ordergroove"],
              "ecommerce": ["Shopify", "Cart Functionality"]
            },
            "add_ons": { "shopify_apps": ["Rebuy"] }
          }
        }
      ]
    }
  ]
}

Two things worth noting. First, the technologies object is a nested map of category → subcategory → array of detected tools. That structure makes it easy to check for a specific tool with a single lookup (result[0].technologies.sales.ecommerce.includes("Shopify")). Second, the endpoint returns adjacent enrichment fields alongside the tech data, including domain_rank, last_visited, social_graph_urls, and (when available) emails and phone_numbers. You get a company snapshot per call, not only a tech list.

Relevant endpoints:

• Domain Technologies: the endpoint used above.
• Domains by Technology: the reverse lookup. Pull every domain in our database running a specified technology. Useful for building a lead list from a tech signal instead of enriching an existing one.
• Domain Whois Overview: pair tech data with WHOIS and backlink stats for a richer enrichment signal.

Two adjacent use cases worth knowing about

Once you’ve got tech-stack detection wired into your workflow, two other patterns pay off quickly.

Exclude-list filtering. If you sell a Klaviyo alternative, the last thing you want is to waste outbound cycles on prospects who are already deeply invested in Klaviyo. Feed your list through the same endpoint, but invert the filter: technologies.marketing.marketing_automation contains "Klaviyo" → deprioritize or drop. The savings compound. On a 10,000-domain list, if 30% already run the competitor, you’ve cut your outbound spend and reply-rate dilution by roughly the same amount, at a per-lookup cost measured in cents.

TAM refinement before you buy the list. List vendors sell by size, not by fit. Before spending the budget on a 50,000-domain B2B ecommerce list, sample a random 500 domains through our Domain Technologies endpoint. If only 12% of the sample runs the platform your product integrates with, your effective addressable market is closer to 6,000 than 50,000. The list price should be renegotiated accordingly. It’s a cheap sanity check that can rewrite your list-buying budget before you spend it.

Turn a lead list into a lead pipeline

Tech-stack detection turns a lead list of 10,000 names into a lead list of 10,000 leads. Each domain already contains information about the platforms, tools, and infrastructure that the company has bet on. Our Domain Analytics API makes reading that information a repeatable, pay-as-you-go operation you can drop into any outbound workflow. If you want to see the response shape for your own domain list, you can try it for free (no card required). You can run a live query in under a minute.