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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.
1

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.
2

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.
3

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.
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
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:
SignalScore
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
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.
  1. Search for companies using any technology (40,000+ options)
  2. Filter by company size, industry, geography, and contact role
  3. Export verified email lists formatted for ad platform custom audiences
  4. Create suppression lists of companies already using your product
  5. 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.
Enrich CRM records with technology and firmographic data to build precise profiles. Target accounts using specific technologies that signal product fit.Example workflow:
  1. Define your ICP tech stack (e.g., companies using HubSpot + Shopify)
  2. Build a filtered list with lead lists adding industry and employee count
  3. Enrich with POST /v1/companies/batch for full firmographic data
  4. Export contacts as custom audiences for LinkedIn and Facebook
  5. Set up subscriber/churn alerts to dynamically refresh targeting
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+/yearforthiskindofintelligence.TechnologyCheckerstartsat50K+/year for this kind of intelligence. TechnologyChecker starts at 89/month.
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.”

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.
1

Set up customer monitoring

Add your customer domains to monitoring lists and configure subscriber/churn alerts for competing technologies.
2

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.
3

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.
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.
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.
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.
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}

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.
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
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:
  1. GET /v1/category/{id}/market-share — Total category size and competitive split
  2. GET /v1/technology/{id}/history — Growth trajectory for specific technologies
  3. GET /v1/technology/{id}/stats — Current adoption snapshot
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 pointExample
Company name and domainacme.com
Industry / verticalSaaS, E-commerce, Healthcare
Employee count51-200
HQ location and countrySan Francisco, USA
Founded year2015
Company typePrivately Held
LinkedIn URLlinkedin.com/company/acme
Detected technologiesShopify, Klaviyo, Stripe, React
Technology categoriesE-commerce, Marketing automation, Payments
Detection timelineFirst seen, last seen, active/inactive
Verified contactsDecision-maker emails, roles, LinkedIn profiles
Available data fields vary by endpoint. See the API reference for response schemas per endpoint.