Find Companies Using Stripe: A Guide to Technographic Prospecting

Your product integrates with Stripe. You want to find prospects who already use Stripe—because they're pre-qualified buyers. A company that already processes payments through Stripe is far more likely to adopt your Stripe-connected tool than one running PayPal or a custom payment gateway. Here's how technographic data makes that possible.

Instead of cold-emailing thousands of random companies, you scan their websites to detect what technologies they use. When you find Stripe, you know they're a fit. This is technographic prospecting—and it's how the best sales teams build pipeline today.

What Is Technographic Prospecting?

Technographic prospecting is the practice of qualifying sales leads based on the technologies they use. Rather than filtering prospects by company size, industry, or geography alone, you add a technology layer: does this company use the specific tools that make them a good fit for our product?

For example, if you sell a Stripe analytics dashboard, your ideal customer is any company that processes payments through Stripe. If you sell a Shopify app, you want merchants running Shopify. If your product monitors AWS infrastructure, you need companies on AWS.

The concept is simple. The execution has historically been expensive. Companies like BuiltWith charge $295/month or more for access to their technographic prospecting tools. Wappalyzer's plans start at $250/month. That pricing puts technographic data out of reach for most startups, freelancers, and small sales teams.

DetectZeStack changes this. With a free tier of 100 requests/month and a Pro plan at $9/month for 1,000 requests, you can run technographic prospecting at a fraction of the cost.

How DetectZeStack Detects Stripe

When you scan a website through the DetectZeStack API, it checks for Stripe across multiple detection layers. No single signal is definitive on its own, but together they provide high-confidence detection.

Stripe.js script inclusion

The most common signal. When a website loads Stripe's payment SDK, it includes <script src="https://js.stripe.com/v3/"> in its HTML. DetectZeStack's HTTP analysis layer parses the page source and identifies this script tag. Most e-commerce sites, SaaS platforms, and marketplaces that use Stripe will load Stripe.js on at least their checkout or pricing pages.

DNS CNAME records

Some Stripe integrations create DNS records that point to js.stripe.com or other Stripe-owned domains. DetectZeStack resolves DNS CNAME chains for the target domain and checks them against known Stripe patterns. This detection works even when Stripe.js isn't loaded on the homepage—the DNS records reveal the integration regardless of which page you scan.

HTTP headers

Stripe's checkout pages and payment forms can set specific HTTP headers. DetectZeStack inspects response headers for patterns associated with Stripe's infrastructure, including Server headers and custom headers that Stripe's hosted checkout uses.

TLS certificate patterns

When a site uses Stripe's hosted checkout (checkout.stripe.com), the TLS certificate chain reveals Stripe's certificate authority and organization details. DetectZeStack inspects TLS certificates during its scan, adding another detection signal that browser-based tools cannot access.

API Example: Detecting Stripe on a Domain

Here's how to check if a website uses Stripe. Get a free API key from RapidAPI (no credit card required) and run:

curl -s "https://detectzestack.p.rapidapi.com/analyze?url=example-saas.com" \
  -H "X-RapidAPI-Key: YOUR_KEY" \
  -H "X-RapidAPI-Host: detectzestack.p.rapidapi.com" | jq '.'

The response includes every technology detected on the domain. Here's what it looks like when Stripe is found:

{
  "url": "https://example-saas.com",
  "domain": "example-saas.com",
  "technologies": [
    {
      "name": "Stripe",
      "categories": ["Payment processors"],
      "confidence": 100,
      "website": "https://stripe.com"
    },
    {
      "name": "React",
      "categories": ["JavaScript frameworks"],
      "confidence": 100
    },
    {
      "name": "Cloudflare",
      "categories": ["CDN"],
      "confidence": 100
    },
    {
      "name": "Google Analytics",
      "categories": ["Analytics"],
      "confidence": 100
    },
    {
      "name": "Vercel",
      "categories": ["PaaS"],
      "confidence": 100
    },
    {
      "name": "Let's Encrypt",
      "categories": ["SSL/TLS certificate authority"],
      "confidence": 70
    }
  ]
}

The key field is "name": "Stripe" with "categories": ["Payment processors"]. When you see this in the response, you know the target domain uses Stripe for payments. The confidence score of 100 means the detection is definitive—Stripe.js was found in the page source.

Notice that the same API call also returns the rest of the tech stack: React for the frontend, Cloudflare for CDN, Vercel for hosting, Google Analytics for tracking, and Let's Encrypt for TLS. This full-stack view lets you qualify prospects on multiple dimensions, not just Stripe.

Building a Prospecting Pipeline

One API call tells you about one domain. To build a real prospect list, you need to scan hundreds or thousands of domains and filter the results. Here's the workflow:

Step 1: Build your target domain list

Start with a list of companies you want to qualify. Sources include:

• LinkedIn Sales Navigator — export company domains from your ICP search
• Industry directories — SaaS directories like G2, Capterra, or Product Hunt list company websites
• Competitor customer pages — many SaaS companies publish customer logos with links
• Conference attendee lists — sponsor and exhibitor pages often include website URLs
• Crunchbase or PitchBook — filter by funding stage, industry, and employee count

Put these domains in a simple text file, one per line.

Step 2: Scan each domain through the API

Step 3: Filter for Stripe users

Step 4: Export to CSV for your CRM

Here's a Python script that does all four steps:

import requests
import csv
import time
import sys

API_KEY = "YOUR_RAPIDAPI_KEY"
HEADERS = {
    "X-RapidAPI-Key": API_KEY,
    "X-RapidAPI-Host": "detectzestack.p.rapidapi.com"
}
API_URL = "https://detectzestack.p.rapidapi.com/analyze"

def scan_domain(domain):
    """Scan a single domain and return detected technologies."""
    resp = requests.get(API_URL, headers=HEADERS, params={"url": domain})
    if resp.status_code == 200:
        return resp.json()
    return None

def main():
    # Read target domains from file
    with open("domains.txt") as f:
        domains = [line.strip() for line in f if line.strip()]

    # Scan each domain and collect Stripe users
    stripe_prospects = []
    for domain in domains:
        print(f"Scanning {domain}...")
        result = scan_domain(domain)
        if result and "technologies" in result:
            tech_names = [t["name"] for t in result["technologies"]]
            if "Stripe" in tech_names:
                stripe_prospects.append({
                    "domain": result.get("domain", domain),
                    "url": result.get("url", ""),
                    "technologies": ", ".join(tech_names)
                })
                print(f"  -> Stripe detected!")
        time.sleep(0.5)  # Be polite with rate limiting

    # Export to CSV
    with open("stripe_prospects.csv", "w", newline="") as f:
        writer = csv.DictWriter(f, fieldnames=["domain", "url", "technologies"])
        writer.writeheader()
        writer.writerows(stripe_prospects)

    print(f"\nDone. Found {len(stripe_prospects)} Stripe users out of {len(domains)} domains.")
    print("Results saved to stripe_prospects.csv")

if __name__ == "__main__":
    main()

Create a domains.txt file with your target domains:

notion.so
linear.app
vercel.com
figma.com
airtable.com
loom.com
calendly.com

Run the script and you get a stripe_prospects.csv file ready to import into HubSpot, Salesforce, or any CRM. Each row is a company confirmed to use Stripe, along with their full tech stack for additional context.

Beyond Stripe: Prospecting by Any Technology

The same approach works for any technology DetectZeStack can detect—and it detects over 3,000. Swap "Stripe" in the filter for whatever technology matters to your sales motion:

To filter by technology category instead of a specific product, modify the filter in the Python script:

# Filter for any payment processor, not just Stripe
techs = result["technologies"]
payment_techs = [t for t in techs if "Payment processors" in t.get("categories", [])]
if payment_techs:
    # This company uses some payment processor
    prospect["payment_tech"] = ", ".join(t["name"] for t in payment_techs)

This catches companies using Stripe, PayPal, Square, Braintree, or any other payment processor—useful if you sell to merchants regardless of their specific payment provider.

Pricing: Technographic Data Without the Enterprise Price Tag

Technographic prospecting has traditionally been an enterprise-only capability because of the cost. Here's how the pricing compares:

BuiltWith and Wappalyzer offer polished dashboards and pre-built lead lists. If you need a turnkey prospecting UI with millions of pre-scanned domains, they're worth the price. But if you're a developer, growth hacker, or small sales team that can write a 30-line Python script, you get the same underlying data through DetectZeStack's API at 1/30th the cost.

The free tier gives you 100 requests/month—enough to validate the approach before committing any budget. Pro at $9/month covers 1,000 domains, which is a solid monthly prospecting batch for most startups.

Tips for Better Results

• Scan the right pages. Stripe.js is often loaded only on pricing or checkout pages. If you scan only the homepage and miss Stripe, try scanning example.com/pricing or example.com/checkout as well.
• Use rate limiting. The Python script includes a time.sleep(0.5) between requests. This keeps you under RapidAPI's rate limits and avoids getting throttled.
• Combine with firmographic data. Knowing a company uses Stripe is the technology filter. Layer it with company size, industry, and funding stage from LinkedIn or Crunchbase to build truly targeted prospect lists.
• Track changes over time. DetectZeStack's /history endpoint shows when a domain adds or removes technologies. A company that just added Stripe is an even hotter lead—they're actively building their payment infrastructure.
• Export the full tech stack. Don't just filter for Stripe. The full technology profile gives your sales team valuable context for personalized outreach. "I noticed you're running React on Vercel with Stripe for payments" is a much better opener than a generic cold email.