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Published September 8, 2026 · Updated September 8, 2026
The answer up front: technographic data - which technologies a company runs - is collected three ways, and each method has a blind spot worth knowing before you pay. Crawlers (BuiltWith $295-995/mo, free single lookups forever) see everything the browser downloads and nothing it does not - backend databases and on-prem are invisible. Crowdsourced fingerprinting (Wappalyzer, $250+/mo, free extension) is fresher on popular sites, thinner on the long tail. Job-postings NLP (TheirStack from free/1,000 credits, and parts of HG Insights and ZoomInfo) catches exactly the backend stack crawlers miss - because engineers name it in hiring ads - but lags actual adoption by months. Below: real prices, the accuracy physics, the three sales plays with published numbers, and the free tier that covers most teams.
Disclosure: Valley (that is us) sells signal-based outbound - an adjacent lane, not an intent-data feed - so we profit if you conclude signals beat scores. The facts are sourced so you can check them.
How we know this category: we run signal-based outbound for 1,000+ LinkedIn accounts (30M+ messages sent). Every price below was verified September 8, 2026 against the vendor's live page, or labeled as reported where the vendor publishes nothing - buyer-reported medians come from Vendr's transaction marketplace.
Valley is an AI outbound platform that finds the people most likely to buy from you - from live buying signals, natural-language search, or your own lists - qualifies them against your ICP, researches each one, and sends personalized messages across email and LinkedIn that get 15-45% reply rates, against a category average of about 2%.
► Stack tells you fit. Signals tell you when: Valley layers timing on your targeting - free for 7 days
The tools, with verified prices (September 8, 2026)
Tool | Method | Price | Free option |
|---|---|---|---|
BuiltWith | Crawling, 491.9M domains, 18+ years of history; top ~2M sites refreshed weekly, the long tail at least quarterly | Basic $295 · Pro $495 · Team $995 per month | Single-site lookups free, forever |
Wappalyzer | Crawl + browser-extension fingerprinting; re-verified monthly | Pro $250 · Business $450 · Enterprise $850+ per month | 50 lookups/mo + the extension |
TheirStack | NLP over 34M+ job postings - catches backend/on-prem tech; every signal links to its source posting | Packs from $109/1,000 credits; API from $49/mo | 1,000 company credits on signup |
Datanyze | Browser-extension prospecting (ZoomInfo-owned; not the pre-2018 platform) | $29 or $55 per month | Free Lite tier |
HG Insights | Multi-method incl. postings; usage intensity, spend and renewal-window data; now owns MadKudu | Enterprise; reported median ~$55K/yr (Vendr) | - |
ZoomInfo technographics | Bundled in higher tiers | Reported $25-36K/yr tiers, sales-gated | - |
Clay | Technographics via provider waterfall (PredictLeads 'Find Tech Stack', BuiltWith-sourced enrichments) | Free tier; from $167/mo | 100 credits/mo |
The accuracy physics (what each method cannot see)
Crawlers only see what the browser downloads: no technographics crawler sees the data warehouse, the on-prem deployment, or anything behind server-side rendering. BuiltWith's breadth comes with staleness on the long tail (quarterly refresh means a removed tool can linger for months); Wappalyzer trades depth for fewer false positives. Job-postings NLP inverts the trade: it names the invisible backend stack (85-95% claimed accuracy where the tech is explicitly named in the ad) but describes what the company is HIRING for, which lags what it runs. The honest setup for serious targeting is one crawler plus one postings source, cross-checked on the accounts that matter.
The three plays, with the published numbers
Competitor displacement: target accounts running the tool you beat. HG Insights claims customers see 25-30% higher win rates on competitive deals (vendor-claimed, labeled as such). Complement targeting: the "running Salesforce with no engagement layer" play - ZoomInfo's published customer cases include an 84% MQL lift and doubled conversion attributed to technographic-informed models (vendor cases, same caveat). Renewal-window timing: outreach ~90 days before a contract lapses, using verification-date data - the play HG explicitly sells data for. One stat to refuse: the "3x higher conversion vs traditional ABM" figure circulating in this space traces to no primary source; we could not verify it and neither can the pages quoting it.
Where technographics fit in a signal stack (our lane, declared)
Stack data answers FIT - who could buy. It says nothing about WHEN. The teams getting outsized reply rates pair a fit filter (technographics, firmographics) with timing signals - profile views, post engagement, hiring, funding - and message only the overlap. That overlap is Valley's native motion: signals select the moment, ICP rules (including stack criteria) qualify the fit, 200+ sources of research (the prospect's stack among them) feed a message in your voice, and you approve every send. 15-45% reply rates vs ~2% (methodology). Related: intent data tools · hiring signals.
► Fit filter plus timing signal beats either alone: see it run on your ICP - free for 7 days
How to choose in 30 seconds
Checking one company: BuiltWith free lookup, right now. Front-end stack at scale: BuiltWith or Wappalyzer by budget. Backend/on-prem reality: TheirStack via job postings. Spend, usage-intensity and renewal windows: HG Insights. Turning fit into timed conversations: Valley.
FAQ
What is technographic data? Structured data about which technologies a company uses - analytics, CRM, cloud, frameworks - collected by crawling sites, fingerprinting via browser extensions, or parsing job postings. It is the standard fit filter for tool-adjacent selling.
How accurate is technographic data? Method-dependent: crawlers are precise on front-end tech but blind to backends and stale on the long tail (BuiltWith refreshes the top 2M sites weekly, the rest at least quarterly); postings-based data reaches the backend but lags adoption by months. Cross-check two methods on accounts that matter.
Is there free technographic data? Yes, genuinely useful: BuiltWith single-site lookups are free forever, Wappalyzer's extension plus 50 monthly lookups is free, and TheirStack starts everyone with 1,000 credits.
What is the best sales play with technographics? Displacement (they run your competitor), complement (they run the platform you extend), and renewal-window timing. The published lift numbers are all vendor-claimed - treat them as direction, not gospel, and add a timing signal before you write.
Does Valley use technographic data? As one input: stack criteria can shape your ICP rules, and a prospect's technology context feeds the research behind each message. Valley's job is the step after the filter - turning fit plus timing into an approved, personalized conversation. 7-day free trial.
► From stack list to first reply: start free, see a reply this week
