🔗 LinkedIn Hiring Signals & B2B Leads

Most LinkedIn scrapers hand you a pile of job titles and stop. This one keeps going — from a public job page all the way to a named decision-maker with a business email you can actually send to, and it shows its work at every step.

This page is built around that output. We start with the record you came for, then explain exactly how each value in it is earned.

💼 Jobs · 📈 Hiring signals · 🎯 Decision-makers · 📧 Evidence-backed emails · 📞 Phones · ⭐ Reviews · 🔄 Change alerts

Here's the chain — a run stops at whichever scrapeType you pick:

🔎 queries · 📍 locations · 🔗 URLs
              │
              ▼
     ┌──────────────────┐
     │  💼 Public jobs  │ ──── scrapeType: jobs ─────▶ 💼 Job records
     └──────────────────┘
              │ roll roles up per company
              ▼
     ┌──────────────────┐
     │ 🏢 Company +     │ ──── scrapeType: signals ──▶ 📈 Ranked accounts
     │ 📈 hiring score  │                              (hiringSignalScore)
     └──────────────────┘
              │ match decision-makers to personas
              ▼
     ┌──────────────────┐
     │ 🎯 Contact       │
     │ 📧 email 📞 phone│ ─── scrapeType: contacts ──▶ ⭐ Scored lead
     │ ✅ MX/SMTP check │                              (email + confidence)
     └──────────────────┘

  🔄 scrapeType: monitor ── new / closed roles vs. the last snapshot

---

⭐ The record everything leads to

A single contact row ties together the whole chain — who, at which hiring company, with what email, and how sure we are:

{
  "recordType": "contact",
  "contactType": "decision_maker",
  "fullName": "Jordan Lee",
  "jobTitle": "Head of Talent Acquisition",
  "targetPersona": "recruiter",
  "company": "Acme Robotics",
  "companyLinkedinUrl": "https://www.linkedin.com/company/acme-robotics",
  "linkedinUrl": "https://www.linkedin.com/in/…",
  "email": "jordan.lee@acme.com",
  "emailStatus": "generated",
  "emailConfidence": 0.72,
  "emailDeliveryStatus": "accepted",
  "emailMxValid": true,
  "emailSmtpAccepted": true,
  "phone": "+1 415-555-0142",
  "phoneE164": "+14155550142",
  "evidenceUrl": "https://…",
  "confidence": 0.81,
  "scrapedAt": "2026-08-07T18:30:02Z"
}

Three things make this row worth more than a scraped name. Here's each one, and where it comes from.

---

🔦 Spotlight 1 — The email carries its own proof

The email field is never a naked string. It ships with a provenance label and a deliverability verdict that are kept deliberately separate, so you always know both where an address came from and whether mail routes to it.

Field	What it tells you
emailStatus	Provenance — public (found in the open) vs generated (a likely company pattern, always labeled as guessed)
emailConfidence	0–1 confidence in the address itself
emailMxValid	The domain actually accepts mail (MX check)
emailSmtpChecked · emailSmtpAccepted	A mailbox-acceptance probe, when the receiving server allows it
emailDeliveryStatus	The routing verdict — e.g. accepted
emailCatchAll	Flags catch-all domains where acceptance means less
emailVerificationSource · emailVerifiedAt	What ran the check, and when
emailEvidenceUrl	The public source, for anything not generated

Why the split matters: a generated address that passes MX + SMTP is a confident send; a public address on a catch-all domain is not. Two different fields, two different decisions — nothing is collapsed into a single misleading "verified ✅".

Turn this on with includeEmails and verifyGeneratedEmails (both on by default). Phones follow the same rule: returned only when public evidence exists, with a normalized phoneE164 and phoneEvidenceUrl alongside.

---

🔦 Spotlight 2 — Companies ranked by how hard they're hiring

Before you ever look at a person, signals mode tells you which companies deserve the attention. Each company row rolls up its live roles into an explainable score:

Field	What it measures
hiringSignalScore	The prioritization number for the account
hiringSignalLabel	The plain-language band for that score
signalReasons	The specific reasons behind it — no black box
openJobs · remoteJobs · salaryVisibleJobs	Volume and quality of current demand
departmentBreakdown · sampleTitles	Where they're growing and for what

Paired with identity fields — websiteUrl, domain (with domainStatus, domainConfidence, domainEvidenceUrl), companyLegalName, companyAddress — a signals run is a ranked account list, not a job dump. Flip excludeStaffingAgencies on (default) to keep it to direct employers.

---

🔦 Spotlight 3 — Every row admits what it doesn't know

The killer feature isn't a field — it's the honesty layer wrapped around all of them. Each record carries:

• confidence — how much to trust this row overall
• availabilityStatus, dataCompleteness, unavailableFields — a per-row completeness report
• Missing source values written as not_available; fields that don't apply to a mode written as not_applicable

Nothing is invented to fill a gap. A blank is labeled as a blank, and you can filter on it. That's what makes the emails above safe to act on.

---

🧭 Getting the record you want

scrapeType picks how far down the chain a run goes. Same searches and toggles, different destination:

Mode	Ends at
jobs	Clean, structured job records — the fastest export
signals	Companies ranked by hiringSignalScore
contacts	Decision-makers with evidence-backed emails & phones
monitor	New / closed roles vs. the last watchlist snapshot
selfTest	An Actor health check + diagnostics

Go straight to leads:

{
  "scrapeType": "contacts",
  "queries": ["SAP consultant"],
  "targetPersonas": ["recruiter", "hiring_manager"],
  "includeEmails": true,
  "includePhones": true,
  "verifyGeneratedEmails": true,
  "maxContactsPerCompany": 5
}

Rank accounts by hiring intent:

{
  "scrapeType": "signals",
  "queries": ["backend engineer", "VP Sales"],
  "locations": ["Germany", "Remote"],
  "excludeStaffingAgencies": true
}

Just the jobs, fast:

{
  "scrapeType": "jobs",
  "queries": ["software engineer"],
  "locations": ["New York"],
  "includeDetails": true,
  "maxResults": 100
}

Watch for changes on a schedule:

{
  "scrapeType": "monitor",
  "queries": ["data engineer"],
  "watchlistName": "data-team-watch"
}

Runs read public LinkedIn pages request-only — no login, no cookies. maxResults caps the primary records (jobs, companies, or contacts); related company, contact, review and diagnostic rows can add to the final item count.

---

🗂️ Where the records land

Every row is tagged with recordType and routed to its own tab:

Tab	Holds
Overview	One quick-scan line per record — type, status, confidence, completeness
Jobs	Full job records: seniority, employment type, function, applicants, benefits, apply mode
Companies	Hiring signals + identity, domain, address, public emails/phones
Contacts	Decision-makers, deliverability-checked emails, phones, evidence
Reviews	Public company rating / review evidence from supported sources
Changes	New and closed roles vs. the previous watchlist snapshot
Diagnostics	Per-run counts, timings, error breakdown — never charged

---

📚 Full field reference

---

🎛️ Input reference

Field	Type	Default	Purpose
scrapeType	enum	jobs	jobs · signals · contacts · monitor · selfTest
queries	array	["software engineer"]	Titles / skills / keywords; each combines with every location
locations	array	[]	Cities, regions, countries (New York, Germany, Remote)
startUrls	array	[]	Exact public LinkedIn job / search URLs
companyUrls	array	[]	LinkedIn company pages or websites to enrich directly
targetPersonas	array	["recruiter","hiring_manager"]	Roles prioritized in Contacts mode
includeDetails	bool	true	Full description, seniority, type, function, benefits, applicants
includeCompanyEnrichment	bool	true	Website, domain, legal identity, address, hiring-signal score
includeContacts	bool	true	Find public decision-makers matching the personas
includeEmails	bool	true	Public + patterned business emails (guessed ones labeled)
verifyGeneratedEmails	bool	true	Syntax + MX + optional SMTP acceptance checks
includePhones	bool	true	Public phones, with E.164 when possible
includeReviews	bool	true	Public company rating / review evidence
includeTitles · excludeTitles	array	[]	Allow/deny jobs by title substring
includeCompanies · excludeCompanies	array	[]	Allow/deny by company name
includeCountries · excludeCountries	array	[]	Allow/deny by country name or ISO code
excludeStaffingAgencies	bool	true	Drop staffing / recruiting intermediaries
maxResults	int	100	Max primary job / company / contact records
maxPages	int	5	Result pages per query/location combo
maxReviewsPerCompany	int	5	Review rows per company (0 = none)
maxContactsPerCompany	int	5	Contacts per company
watchlistName	string	default	Snapshot name Monitor compares against
maxConcurrency	int	10	Public pages processed at once (1–100)
maxRetries	int	5	Attempts for a temporarily unavailable request
proxyConfiguration	object	Residential	Connection settings (Residential recommended)

---

💬 Common questions

Do I need a LinkedIn login or cookies? No — public pages are read request-only.

What separates a generated email from a public one? Provenance. public was found in the open; generated is a likely company pattern, always labeled as guessed and never dressed up as evidence. Deliverability (emailDeliveryStatus) is scored independently either way.

Do I pay for blocked or empty pages? You're charged per saved result — jobs, signals, contacts, reviews, changes. Diagnostics rows aren't charged, and a run that hits its charge limit stops early and says so.

How do I track hiring over time? Run scrapeType: "monitor" with a stable watchlistName and search scope on a schedule; new and closed roles appear in the Changes tab from the second run on.

---

Pick a scrapeType, add a search or a company URL, and press Start — the record at the top of this page is what comes back.

💬 If a run turned into a lead you could actually send to, leaving a review on the Apify Store is the best way to support it — a rating lifts the Actor in search and tells me where to aim next.

🏷️ Tags: linkedin · linkedin jobs · lead generation · b2b leads · sales intelligence · hiring signals · recruiting · email finder · contact enrichment · jobs scraper