B2B Hiring Signals, Tech Stack & Buying Intent Scraper

Turn public job postings into high-converting B2B outbound triggers at a fraction of the cost of enterprise intent platforms. Scrape real-time job openings across LinkedIn Guest Jobs, Greenhouse, Lever, and Schema.org Career Pages, and automatically extract:

• 120+ B2B Tech Stack Tools categorized across CRM, Cloud, Data, AI/LLMs, ERP, and DevSecOps.
• Active Buying Signals & Pain Points (Legacy Migration, Greenfield Implementation, Rapid Team Scaling).
• B2B Opportunity & Intent Score (0–100) (opportunity_score & intent_score) to prioritize hot accounts.
• Actionable Sales Pitch Angles (primary_pitch_angle & all_pitch_angles) + Target Buyer Personas (target_decision_maker_titles) ready for Apollo / Clay people-search enrichment.
• Multi-Language Cold Email Icebreakers (en, es, pt, de, fr) ready to inject directly into Instantly, Smartlead, Lemlist, or HubSpot.

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⚡ Why Top RevOps Teams & Lead Gen Agencies Switch to This Actor

Feature	Legacy Intent Platforms (6sense / Bombora / BuiltWith)	Generic Job Scrapers + OpenAI Credits	B2B Hiring Signals & Intent Scraper
Annual Contract	❌ $15,000 – $60,000 / year	⚠️ Apify compute + $0.03/row LLM API cost	✅ $0/mo fixed — pure Pay-Per-Event
Tech Stack Detection	⚠️ Stale DNS/cookie footprints	❌ Raw HTML (requires costly LLM parsing)	✅ 120+ live tools extracted from active job reqs
Buying Signals	⚠️ Black-box topic surges	❌ None	✅ Verified quotes (Migration, New Rollout, Scaling)
Sales Pitch Angles	❌ None	❌ Manual prompt engineering	✅ primary_pitch_angle & all_pitch_angles included
Buyer Persona Mapping	❌ None	❌ None	✅ target_decision_maker_titles for Apollo/Clay
Multi-Language Copy	❌ None	⚠️ Extra LLM token cost	✅ Native en, es, pt, de, fr icebreakers at $0 extra
Memory & Compute Cost	N/A	❌ >1 GB RAM (slow Headless Chrome)	✅ Runs in 256 MB RAM (pooled HTTP/2 & TLS fingerprinting)

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🎯 High-ROI Use Cases for B2B Teams & Agencies

1. Competitor Displacement & Migration Campaigns: Filter for MIGRATION_OR_REPLACEMENT signals and tech stacks like HubSpot, Salesforce, Snowflake, or NetSuite to catch companies actively replacing legacy systems.
2. Clay.com Automated Outbound Waterfalls: Pull daily high-intent hiring leads (opportunity_score >= 75), feed target_decision_maker_titles + company_name into an Apollo/Contact finder column in Clay, and map cold_email_icebreaker directly into Instantly or Smartlead.
3. B2B Agency Client Fulfilment (Multi-Geo): Generate localized outbound hooks in English (en), Spanish (es), Portuguese (pt), German (de), or French (fr) without burning OpenAI/Anthropic credits.
4. Fractional Executive & Specialized Recruiting: Spot companies hiring their "first dedicated hire" or "founding engineer" (TEAM_EXPANSION) with disclosed salary budgets (salary_min / salary_max).

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🧠 How the B2B Opportunity & Buying Intent Engine Works

1. Buying Signal Categories (buying_signals)

• MIGRATION_OR_REPLACEMENT: Highlights transitions away from legacy systems ("migrating from HubSpot to Salesforce", "replacing legacy ERP", "modernizing our stack").
• NEW_IMPLEMENTATION: Identifies greenfield deployments and active vendor evaluations ("implementing Snowflake", "evaluating new tools", "rolling out Gong").
• TEAM_EXPANSION: Detects hypergrowth or strategic department builds ("founding engineer", "first dedicated hire", "building the team from scratch").

2. Opportunity & Intent Score (0–100) Algorithm

Each lead receives an objective score (opportunity_score / intent_score):

• Detected B2B Tech Stack: Up to +30 pts (+8 pts per verified tool).
• Buying Signals Present: Up to +35 pts (+20 pts per migration/implementation trigger).
• Operational Pain Points Detected: Up to +10 pts (+5 pts per pain point).
• Decision-Maker Seniority: +10 pts (C-Level, VP, Director, Head, Lead).
• Explicit Compensation Disclosed: +10 pts.
• Baseline Active Hiring Intent: +15 pts.

Tiers:

• HIGH_INTENT (75–100): Immediate outbound priority — active budget, tooling stack, and strategic urgency confirmed.
• MEDIUM_INTENT (45–74): Strong fit for automated nurture sequences and account scoring.
• LOW_INTENT (< 45): General hiring activity without explicit tooling or migration triggers.

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📋 Sample Enriched Output JSON

{
  "lead_id": "9f8c2a1e4b7d6012",
  "company_name": "AcmeCloud",
  "company_website": "https://acmecloud.com",
  "company_linkedin_url": "https://www.linkedin.com/company/acmecloud",
  "job_title": "Head of Revenue Operations",
  "department": "Sales & GTM",
  "seniority_level": "Director / Head",
  "location": "United States",
  "workplace_type": "Remote",
  "salary_min": 130000.0,
  "salary_max": 165000.0,
  "salary_currency": "USD",
  "salary_raw_text": "$130,000 - $165,000",
  "detected_tech_stack": [
    "Salesforce",
    "HubSpot",
    "Gong",
    "Clay",
    "Snowflake",
    "Looker",
    "dbt"
  ],
  "tech_categories": {
    "CRM & Sales": ["Salesforce", "HubSpot", "Gong", "Clay"],
    "Cloud & Data Infrastructure": ["Snowflake", "dbt"],
    "Marketing & Product Analytics": ["Looker"]
  },
  "buying_signals": [
    "[MIGRATION_OR_REPLACEMENT] \"migration from HubSpot to Salesforce and implement Gong...\"",
    "[TEAM_EXPANSION] \"rapidly scaling our Revenue Operations team...\""
  ],
  "intent_score": 100,
  "opportunity_score": 100,
  "intent_tier": "HIGH_INTENT",
  "primary_pitch_angle": "Tech Stack Migration & Legacy Replacement",
  "all_pitch_angles": [
    "Tech Stack Migration & Legacy Replacement",
    "Hypergrowth Team Scaling & Onboarding Acceleration",
    "RevOps Automation & Pipeline Conversion Optimization",
    "Data Pipeline Reliability & Cloud Cost Governance",
    "Executive 90-Day Quick-Win Initiative (Sales & GTM)"
  ],
  "detected_pain_points": [
    "Legacy System & Tech Debt",
    "Pipeline & Revenue Predictability"
  ],
  "target_decision_maker_titles": [
    "VP of Revenue Operations",
    "Chief Revenue Officer (CRO)",
    "Head of Sales Operations",
    "VP of Sales"
  ],
  "cold_email_icebreaker": "Saw AcmeCloud is hiring a Head of Revenue Operations focused on Salesforce, HubSpot, Gong while driving migration or replacement—usually a key moment when teams look to streamline their Sales & GTM stack.",
  "icebreaker_language": "en",
  "job_url": "https://www.linkedin.com/jobs/view/1234567890",
  "source_platform": "linkedin_guest",
  "posted_at": "2026-10-18T08:00:00Z",
  "scraped_at": "2026-10-19T10:15:00+00:00"
}

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🚀 Step-by-Step Integration Guide (Clay, Make, n8n & Apollo)

1. Clay.com (Automated Signal-to-Outbound Waterfall)

1. In your Clay workbook, click Add Source / Add Column -> Apify -> Run Actor.
2. Select b2b-hiring-signals-tech-stack-scraper.
3. Set onlyHighIntent: true, choose your icebreakerLanguage (en, es, pt, de, fr), and enter your target keywords (["Revenue Operations", "Data Engineer"]).
4. Map the returned items directly into Clay columns:
   • Pass company_name + target_decision_maker_titles into Clay's Find People at Company (Apollo / LinkedIn) enrichment.
   • Use primary_pitch_angle, detected_pain_points, and cold_email_icebreaker as merge variables in your Instantly or Smartlead push column.

2. Make & n8n (Scheduled Daily Slack & CRM Alerts)

1. Add the Apify — Run an Actor module on a daily schedule (e.g., 07:30 AM).
2. Add Apify — Get Dataset Items to iterate over the exported leads.
3. Filter by opportunity_score >= 75 and route directly to HubSpot / Salesforce / Pipedrive or a #hot-buying-signals Slack channel.

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⚙️ Input Parameters Reference

Parameter	Type	Default	Description
searchKeywords	Array	["Revenue Operations", "Data Engineer", "Salesforce"]	Job titles or technologies to target.
locations	Array	["United States", "United Kingdom", "Spain"]	Countries, states, or cities to monitor.
targetAtsSlugs	Array	[]	Optional direct Greenhouse/Lever company slugs (e.g., ["stripe", "cloudflare"]).
customCareerUrls	Array	[]	Optional direct career page URLs supporting Schema.org JobPosting JSON-LD.
postedWithinDays	String	"7"	Recency filter ("1", "7", "14", or "30" days).
requiredTechFilter	Array	[]	Only save and bill leads mentioning at least one of these tools.
onlyHighIntent	Boolean	false	Filter out postings with intent_score < 60 before saving or billing.
icebreakerLanguage	String	"en"	Outbound copy language: "en", "es", "pt", "de", or "fr".
maxItems	Integer	50	Hard budget cap on total leads exported and billed.
proxyConfiguration	Object	{"useApifyProxy": true}	Apify Proxy configuration.

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💰 Fair & Transparent Pay-Per-Event (PPE) Pricing

You only pay for verified, deduplicated leads that pass all your filters and are delivered to your dataset (strict 1:1 billing guarantee):

Event	Free ($0/mo)	Starter ($19/mo)	Scale ($199/mo)	Business ($999/mo)	When is it charged?
Result (apify-default-dataset-item)	$10.00 / 1,000	$6.00 / 1,000	$5.00 / 1,000	$4.00 / 1,000	Only when a unique lead passes all your filters and is saved
High-Intent Bonus (high-intent-lead-detected)	$15.00 / 1,000	$12.00 / 1,000	$10.00 / 1,000	$8.00 / 1,000	Only when opportunity_score >= 75 (HIGH_INTENT)
Actor Start (apify-actor-start)	$0.00005	$0.00005	$0.00005	$0.00005	Once per Actor run initialization

🛡️ Triple Cost & Compute Protection

1. Zero Charge for Filtered or Failed Items: Postings that fail to load, lack descriptions, are duplicates, or are excluded by onlyHighIntent / requiredTechFilter are never billed.
2. Hard maxItems & Platform Spending Limit: Immediately halts the moment maxItems or your Apify ACTOR_MAX_PAID_DATASET_ITEMS / event_charge_limit_reached cap is hit.
3. Automatic max_attempts Circuit Breaker: Caps raw evaluations at 5 × maxItems (min 100) to protect proxy and compute usage when hyper-strict filters are configured.

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🔒 Enterprise Security, Low-Memory Architecture & GDPR Compliance

• 100% GDPR & CCPA Compliant by Design: Extracts strictly corporate, public B2B job specifications (company name, role requirements, corporate tech stack, and salary bands). No personal candidate data or private profiles are collected.
• 256 MB RAM Ultra-Light Footprint: Uses a single shared HTTP/2 connection pool (httpx.AsyncClient), concurrent batching (asyncio.gather + asyncio.Semaphore), and a hard 2 MB streaming cap per response.
• Hardened Against SSRF, DNS Rebinding & ReDoS: Every custom URL and redirect hop undergoes strict scheme/port validation, full DNS resolution verification against private/loopback/CGNAT/cloud-metadata IPv4 & IPv6 ranges, IP-pinning with TLS sni_hostname, and bounded regex evaluation windows.