ACTION_ID: company_tech_stack_enrichment_from_builtwith NAME: BuiltWith: Enrich Company Tech Stack CATEGORY: scrape CREDITS: 2 Find what a website is built with, via BuiltWith. The broadest tech-stack source of the three providers in Floqer, but BuiltWith is a web crawler — coverage is wide because it detects from crawlable surface signals (HTML, JS, headers, DNS, CDN, etc.), which means many results are *inferred* rather than confirmed. Treat as "the company likely uses or has used this" not "the company definitely runs this in production today." INDEX: 1. Inputs 2. Outputs 3. How to configure 4. Key notes 5. Where it fits in a workflow 6. When to use 7. When not to use ================================================================================ 1. INPUTS ================================================================================ company_domain (url, required) Company Domain. URL/Domain of the company. keyword_or_category_filter (string, optional) Keyword or Category Filter. Filter for specific technologies or categories. Comma-separated. Quoted words ("Java") do exact match. last_detected_date_filter (string, optional) Last Detected Date Filter. Relative dates ("5 days ago") or absolute (yyyy-MM-dd, "2022-07-31"). ================================================================================ 2. OUTPUTS ================================================================================ all_technologies (json) — All Technologies. Tech stack of the company. all_technologies_csv (string) — All Technologies CSV. technology_count (number) — Technology Count. matching_keywords_found (string) — Matching Keywords Found. total_matching_technologies_found (number) Total Matching Technologies Found. company_meta (json) — Company Meta. Incidental firmographic blob returned by BuiltWith alongside the tech-stack payload. Keys observed: `Vertical`, `Social` (array of social-network URLs — coverage varies, may be missing entirely), `CompanyName` (parsing is unreliable; can arrive concatenated with page content), `Telephones` (array), `Emails` (array), `City`, `State`, `Postcode`, `Country`. Reasonable use: `City` / `State` / `Postcode` / `Country` as a free location seed when you're already running BuiltWith. ⚠ Not the recommended source for anything else — see KEY NOTES. ================================================================================ 3. HOW TO CONFIGURE ================================================================================ Configure Action body: { "inputs": { "company_domain": "{{input.company_domain}}", "keyword_or_category_filter": "Salesforce, \"Shopify\"", "last_detected_date_filter": "30 days ago" } } Field-by-field: - company_domain URL or bare domain of the company. - keyword_or_category_filter Comma-separated keywords or categories. Quote a term ("Java") to force an exact match. - last_detected_date_filter Relative (`5 days ago`) or absolute (`yyyy-MM-dd`). ================================================================================ 4. KEY NOTES ================================================================================ - BuiltWith returns a wide tech-stack list. On stripe.com a test run returned ~840 technologies; on small SaaS sites, 60–400-range is typical. Use `keyword_or_category_filter` to scope to the technologies you care about — otherwise downstream filtering on `all_technologies_csv` is the simplest path. - Coverage is broad because the data comes from web-crawl inference, but inference means false-positives happen. If a signal is borderline-critical to a sales decision, double-check against `company_tech_stack_enrichment_using_their_stack` (more precise + adds job-posting signal) or `company_tech_stack_floqer` (departmentally bucketed). - `last_detected_date_filter` is most useful for recency-sensitive signals (e.g. "company added Salesforce in the last 90 days"). Because detections include historical FirstDetected dates as old as 2013 in some cases, the unfiltered list is also useful for "did they ever touch this stack" questions — something neither TheirStack nor Floqer native cleanly supports. - `company_meta` is a convenience byproduct of the BuiltWith API response, not a primary purpose of this action. Treat it as best-effort context — fields are inconsistently populated across companies, and there's no guarantee on freshness or accuracy. The one byproduct use that's worth documenting is **location seeding**: `City`, `State`, `Postcode`, `Country` give you a quick HQ-area read for routing / territory assignment / geo filtering when you're already running BuiltWith for the tech-stack payload. Coverage in this field is reasonably good even when other fields are blank. Validate against a dedicated firmographics source for anything sales-critical. Other fields (`Social`, `Telephones`, `Emails`, `Vertical`, `CompanyName`) are present but coverage is patchy and quality varies — names sometimes arrive concatenated with random page content, the `Social` key can be missing entirely, and there's no guarantee a specific social network (e.g. LinkedIn) will be surfaced. Don't build workflows that depend on these fields. For authoritative versions of any of them, use a dedicated action: - `company_enrich_using_people_data_labs` — broad firmographics - `enrich_company_linkedin_profile` — LinkedIn-scraped - `store_leads_enrich_company` — e-commerce companies - `company_headcount_distribution_by_country` — headcount focus ================================================================================ 5. WHERE IT FITS IN A WORKFLOW ================================================================================ Pattern: company domain -> company_tech_stack_enrichment_from_builtwith -> workflow_path_filter (matching tech) -> outreach. ================================================================================ 6. WHEN TO USE ================================================================================ Use company_tech_stack_enrichment_from_builtwith when: - You want the broadest possible tech-stack coverage and are OK with some inferred / false-positive signals — better recall, weaker precision. - You need historical "ever-touched" signal (FirstDetected / LastDetected dates per technology). BuiltWith is the only provider of the three that surfaces these. - You want category metadata per detected technology (each item carries a `Tag`, `Categories`, `Parent`, `Description`, `Link` to the source-of-record blog post for that version, etc.). Useful for downstream LLM steps that want richer per-tech context than a bare name string. Prefer the alternative providers when precision matters more than recall, when you need pre-bucketed-by-department output, or when cost/latency matters at scale — see WHEN NOT TO USE. ================================================================================ 7. WHEN NOT TO USE ================================================================================ Want a more precise tech-stack signal — fewer false positives because the source is solid technographics + job-posting requirements (e.g. "this company posted a job that requires Salesforce admin experience" is hard signal that they actually use Salesforce in production). -> company_tech_stack_enrichment_using_their_stack (https://floqer.com/docs/action-detail/company_tech_stack_enrichment_using_their_stack.txt) Want pre-bucketed-by-department output (sales / marketing / HR / IT security / etc.) so you can ICP-filter on "uses X in department Y" without writing the bucketing yourself. -> company_tech_stack_floqer (https://floqer.com/docs/action-detail/company_tech_stack_floqer.txt) Need a company's LinkedIn URL (or any specific social URL). BuiltWith's `company_meta.Social` surfaces social URLs when present in its crawl, but coverage is patchy — LinkedIn specifically missed ~a third of a small-SaaS sample. Don't depend on it. -> llm_web_agents (run a tight "find the LinkedIn /company/ URL for this company" mission with output_format declaring a single `linkedin_url` field — reliable and grounded with citations) -> enrich_company_linkedin_profile (when you already have the LinkedIn URL and want the full LinkedIn scrape) Need firmographics (HQ details beyond city/state, employee count, industry classification, funding, etc.). -> company_enrich_using_people_data_labs (full firmographic enrichment via PDL) ================================================================================ This file is maintained manually. Last updated: 2026-05-14. Full interactive reference: https://floqer.com/docs/reference Action catalog: https://floqer.com/docs/action-catalog.txt