TechnologyChecker use cases — sales, GTM, market analysis, custom audiences

TechnologyChecker tracks 40,000+ technologies across 50M+ domains with 20+ years of historical data, real-time subscriber and churn signals, and verified contacts. Here’s how different teams put that data to work.

Sales and lead generation

Find based on the technology they already use. Enrich your pipeline with data and verified decision-maker contacts.

Identify your target audience

Use the technology search to find companies running a competitor’s product, or a complementary tool that signals buying intent.Example: Find all companies using Mailchimp to pitch your email marketing alternative.

Build a filtered lead list

Combine technology filters with company data (industry, employee count, geography, and keywords) to create a precise prospect list with verified contacts.Example: “Uses Shopify AND NOT Klaviyo, 51-200 employees, United States” returns e-commerce companies missing a marketing automation tool.

Export and enrich

Download your list as CSV or JSON with up to 14 data columns including company name, LinkedIn URL, industry, employee count, and verified decision-maker contacts. Import directly into your CRM or upload as a custom audience to LinkedIn or Facebook.

Competitive displacement with churn signals

Search for companies using a competitor’s technology, then monitor for real-time churn signals. When companies drop a competitor, you get notified with verified contacts for the decision-makers. That gives you a 30-60 day window to reach out while they’re still evaluating options.Example: Set up a churn alert for “companies dropping Intercom.” When 47 companies churn this week, you have verified contacts for the VP of Customer Experience at each one.API endpoints:

GET /v1/technology/name/{name}/domains — Find domains using a specific technology
GET /v1/domain/{domain} — Get full tech stack for qualification
POST /v1/companies/batch — Bulk-enrich a list of prospect domains

Technology-based account scoring

Use technology stack data and ICP patterns from historical data as scoring signals in your . Companies using complementary tools in your ecosystem are more likely to convert.Example scoring model:

Signal	Score
Uses complementary technology	+20
Recently subscribed to related tool	+15
Recently churned from competitor	+25
Uses competitor product	+10
Enterprise tech stack (50+ technologies)	+10
Matches ICP technology pattern	+30

CRM enrichment

Automatically append technology data and contact information to CRM records using the batch API. Enrich existing accounts with tech stack, company metadata, LinkedIn firmographics, and verified contacts in a single call.API endpoints:

POST /v1/companies/batch — Enrich up to hundreds of domains per request
GET /v1/company/{domain} — Single company lookup with full firmographic data

Use the AND NOT logic in lead lists to exclude companies already using your product. This prevents wasting outreach on existing customers.

Custom audience ad targeting

Build technology-qualified custom audiences for LinkedIn, Facebook, and Google Ads. Target decision-makers at companies using specific technologies.

How it works
Supported platforms
Audience segments

Search for companies using any technology (40,000+ options)
Filter by company size, industry, geography, and contact role
Export verified email lists formatted for ad platform custom audiences
Create suppression lists of companies already using your product
Refresh audiences dynamically as subscriber/churn signals update the data

Example: A marketing automation company targets operations leaders at companies using Airtable. They search “companies using Airtable” (8,400 results), filter for US, 50-500 employees, SaaS industry (2,100 results), and export contacts with title “VP Operations” or “Head of Ops” (1,850 verified emails). Uploaded to LinkedIn as a Matched Audience.

No competitor at this price point offers technology-segmented custom audience exports. GTM teams running ABM campaigns on LinkedIn and Facebook can build targeted audiences in minutes, not weeks.

Marketing and demand generation

Build targeted campaigns using real technology adoption data, subscriber/churn signals, and custom audience exports. Segment audiences by tech stack, personalize outreach at scale, and size your with actual adoption numbers, not estimates.

Account-based marketing
Personalized outreach
Content and SEO

Enrich CRM records with technology and firmographic data to build precise profiles. Target accounts using specific technologies that signal product fit.Example workflow:

Define your ICP tech stack (e.g., companies using HubSpot + Shopify)
Build a filtered list with lead lists adding industry and employee count
Enrich with POST /v1/companies/batch for full firmographic data
Export contacts as custom audiences for LinkedIn and Facebook
Set up subscriber/churn alerts to dynamically refresh targeting

Use tech stack data to personalize messaging at scale. Reference specific tools a prospect already uses to increase response rates.Example: “We noticed you’re using Mailchimp. Our platform integrates natively with it, so your team can start in minutes without migrating data.”API endpoints:

GET /v1/domain/{domain} — Get a prospect’s full tech stack before outreach
GET /v1/company/{domain} — Company metadata for personalization

The market intelligence API returns historical data with monthly granularity. Ideal for time-series charts, ABM enrichment, and TAM calculations.

ICP analysis and market research

Use 20+ years of historical data to build data-driven ICP profiles, track competitive market share, and analyze technology adoption trends. HG Insights charges

50K+/year for this kind of intelligence. TechnologyChecker starts at

89/month.

ICP pattern analysis
Market share analysis
Trend tracking
Migration pattern analysis

Identify common technology patterns among your best customers using historical data:

Find which technology combinations correlate with your highest-LTV customers
Build technology-based ICP scoring models with empirical data
Segment prospects by technology maturity level
Analyze which technologies predict company growth stages

Example: “Our highest-LTV customers use Stripe + Segment + a headless CMS. TechnologyChecker finds 2,400 companies matching this pattern that aren’t yet customers.”

Monitor technology adoption and decline over time with monthly granularity going back 20+ years.What you can answer:

Is React gaining or losing market share compared to Vue.js?
When did Shopify overtake WooCommerce?
Which technologies peaked and are now declining?

API endpoint: GET /v1/technology/{id}/history

Browse market data

Interactive market share charts, quarterly growth, and historical trend visualizations.

Market intelligence API

Programmatic access to stats, trends, and market share data.

Churn prevention

Monitor existing customer tech stacks for early warning signals. Get alerted when customers subscribe to competing platforms or drop complementary tools. The best time to intervene is before the renewal conversation, not during it.

Set up customer monitoring

Add your customer domains to monitoring lists and configure subscriber/churn alerts for competing technologies.

Detect early warning signals

Get real-time alerts when customers adopt competing platforms or drop complementary tools. Use 20-year historical data to predict which technology changes correlate with churn.

Intervene proactively

Reach out with retention messaging before renewal conversations, armed with technology context and historical patterns. Export at-risk customer contacts for targeted retention campaigns.

When customer success teams can see that an account adopted a competing platform months before renewal, they can address migration concerns proactively. Finding out during the renewal conversation is usually too late.

Buying window detection

Reach prospects during active evaluation periods, not weeks later when they’ve already decided.

Churn-triggered buying windows

When a company drops a tool, they typically evaluate replacements for 30-60 days. That’s your window.Example: Set alerts for churn from a competing CRM. When 47 companies churn this week, outreach within 48 hours to reach them during active evaluation.

Subscription-triggered evaluation signals

A company subscribing to multiple tools in a category signals they’re actively comparing options.Example: A company subscribes to both Stripe and Braintree. They’re evaluating payment processors. Reach out with your payment platform integration.

Historical evaluation patterns

20-year historical data shows typical evaluation timelines by technology category. You can see how long companies in your space usually take to make a decision.Example: Companies evaluating CRM replacements typically take 45-90 days. Time your outreach sequence accordingly.

Developer integrations

Integrate technology detection into your applications, pipelines, and internal tools with a API. The API quickstart walks you through authentication and your first request.

Lead scoring pipeline
Competitive monitoring
Batch enrichment

Enrich incoming leads in real-time by querying their tech stack as part of your signup or qualification flow.

Python

import requests

def score_lead(domain: str, api_key: str) -> dict:
    headers = {"Authorization": f"Bearer {api_key}"}
    response = requests.get(
        f"https://api.TechnologyChecker.io/v1/domain/{domain}",
        headers=headers,
    )
    data = response.json()["data"]
    tech_names = [t["name"] for t in data["active_technologies"]]

    score = 0
    if "Shopify" in tech_names:
        score += 20  # E-commerce target
    if "Google Analytics" in tech_names:
        score += 10  # Data-aware company
    if len(tech_names) > 30:
        score += 15  # Complex tech stack

    return {"domain": domain, "score": score, "technologies": tech_names}

Track when target accounts change their tech stack by periodically polling domain endpoints.

JavaScript

async function checkTechChanges(domain, previousTech, apiKey) {
  const response = await fetch(
    `https://api.TechnologyChecker.io/v1/domain/${domain}`,
    { headers: { Authorization: `Bearer ${apiKey}` } }
  );
  const { data } = await response.json();
  const currentTech = data.active_technologies.map((t) => t.name);

  const added = currentTech.filter((t) => !previousTech.includes(t));
  const removed = previousTech.filter((t) => !currentTech.includes(t));

  return { domain, added, removed };
}

Enrich a CRM export with technology and company data in bulk.

cURL

curl -X POST https://api.TechnologyChecker.io/v1/companies/batch \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"domains": ["stripe.com", "shopify.com", "github.com"]}'

Authentication

Set up bearer token auth.

API reference

Explore endpoints and integration guides.

Rate limits

Plan-based request limits.

Investment and due diligence

Technology adoption is a proxy for market traction. Track portfolio companies, evaluate acquisition targets, and spot breakout technologies before they hit mainstream coverage. Combine adoption data with analysis for data-driven investment decisions.

Portfolio monitoring

Track adoption metrics for portfolio companies’ products. Month-over-month growth in website adoption is an early indicator of revenue trends. Use subscriber/churn signals to detect competitive threats in real-time.Key metrics:

Active domains (current adoption)
Total domains (all-time reach)
Monthly growth rate from historical data
Market share position within category
Subscriber growth rate vs. churn rate

Market sizing

Use adoption counts to estimate total addressable market. If a category tracks 500K websites and the leader holds 35% share, there’s quantifiable room for challengers.API approach:

GET /v1/category/{id}/market-share — Total category size and competitive split
GET /v1/technology/{id}/history — Growth trajectory for specific technologies
GET /v1/technology/{id}/stats — Current adoption snapshot

Mapping the competitive picture

Build a complete view of how technologies compete. Spot consolidation trends, emerging challengers, and market leaders losing ground using 20-year historical data and real-time subscriber/churn signals.Example: A VC firm tracks that Linear’s subscriber growth rate is 3x faster than Asana’s in the 100-500 employee segment, while 60% of companies leaving Asana move to Linear or Notion.

Available company data

Every domain lookup or lead list includes technology data combined with firmographic fields and verified contacts.

Data point	Example
Company name and domain	acme.com
Industry / vertical	SaaS, E-commerce, Healthcare
Employee count	51-200
HQ location and country	San Francisco, USA
Founded year	2015
Company type	Privately Held
LinkedIn URL	linkedin.com/company/acme
Detected technologies	Shopify, Klaviyo, Stripe, React
Technology categories	E-commerce, Marketing automation, Payments
Detection timeline	First seen, last seen, active/inactive
Verified contacts	Decision-maker emails, roles, LinkedIn profiles

Available data fields vary by endpoint. See the API reference for response schemas per endpoint.

Lead lists

Build targeted prospect lists with technology and company filters plus custom audience exports.

Domain lookup

Scan any website to see its full technology stack.

Market research

Analyze market share, growth rates, and adoption trends.

API reference

Full REST API documentation with interactive examples.

​Sales and lead generation

​Custom audience ad targeting

​Marketing and demand generation

​ICP analysis and market research

Browse market data

Market intelligence API

​Churn prevention

​Buying window detection

​Developer integrations

Authentication

API reference

Rate limits

​Investment and due diligence

​Available company data

​Related pages

Lead lists

Domain lookup

Market research

API reference

Sales and lead generation

Custom audience ad targeting

Marketing and demand generation

ICP analysis and market research

Churn prevention

Buying window detection

Developer integrations

Investment and due diligence

Available company data

Related pages