LinkedIn Lead Generator - B2B Sales Prospecting

Find qualified B2B decision-makers on LinkedIn by describing your ideal customer. This actor uses AI-powered company discovery and people search to deliver verified leads with LinkedIn profiles, confidence scores, and full company data — all in under 10 minutes.

Pay only for results: $2.00 per run + $0.06 per lead. No monthly subscriptions, no wasted credits.

Who is this for?

• Sales teams & SDRs building targeted outreach lists
• Growth marketers running account-based marketing campaigns
• Founders & CEOs doing hands-on B2B prospecting
• Recruiters sourcing candidates at specific companies
• Agencies generating leads for clients at scale
• VC firms mapping founders and C-suite across a market segment

How it works

1. Define your ideal customer — Set job titles, seniority levels, industries, company size, and geography using the simple input form
2. AI discovers matching companies — Semantic search finds companies matching your criteria, then AI filters out noise and validates each result
3. People search finds decision-makers — For each qualifying company, the actor finds people matching your target roles on LinkedIn
4. AI scores and filters leads — Every lead gets a confidence score based on how well they match your ideal customer profile
5. Export your leads — Download as an Excel spreadsheet or browse in the Apify dataset table

The entire pipeline typically completes in 3-10 minutes depending on the number of leads requested.

What you get per lead

Field	Example
Contact Name	Jane Smith
Job Title	VP of Engineering
LinkedIn URL	linkedin.com/in/janesmith
Contact Location	San Francisco, CA
Seniority Level	VP
Confidence Score	0.85
Confidence Reason	Strong match: SaaS company, VP-level, West Coast
Company Name	Acme Corp
Company Website	acme.com
Industry	SaaS & Cloud Platforms
Employee Count	250
Company Revenue	$10M-$50M
Company Location	San Francisco, CA
Founded Year	2018
Company Description	B2B developer tools platform...

Results are exported in two formats:

• Apify Dataset — Browse, filter, and download as JSON, CSV, XML, or Excel directly from the Apify console
• Excel file — A formatted .xlsx workbook saved to the key-value store with separate sheets for leads, companies, and run statistics

Use cases

Find VP-level SaaS buyers on the US West Coast

Set job titles to "VP of Sales, Head of Sales", industries to "SaaS & Cloud Platforms", locations to "California, Washington, Colorado", seniority to VP, Director, Head. Get 50 targeted leads for $5.00.

Source engineering leaders at fintech startups in Europe

Set job titles to "CTO, VP of Engineering, Head of Engineering", industries to "Fintech", locations to "United Kingdom, Germany, Netherlands", company size 50-500 employees.

Build an ABM list for cybersecurity decision-makers

Set job titles to "CISO, VP of Security, Head of IT Security", industries to "Financial Services, Healthcare, Enterprise Software", locations to "United States". Use the confidence threshold to keep only highly relevant matches.

Find founders at early-stage AI companies

Set job titles to "Founder, CEO, Co-Founder", industries to "Artificial Intelligence", company size 10-100, seniority to Founder, C-Suite. Add company keywords like "seed", "Series A" for tighter targeting.

Recruit senior engineers at fast-growing startups

Set job titles to "Senior Software Engineer, Staff Engineer, Principal Engineer", industries to "Developer Tools, Infrastructure", locations to "San Francisco, New York". Use "Similar Company URLs" to find companies like your top hiring targets.

Pricing

This actor uses Apify's pay-per-event pricing. You pay only for what you use — no monthly subscription required.

Fee	Amount	Description
Base fee	$2.00	Charged once per run (covers AI search and processing)
Per lead	$0.06	Charged for each qualified lead delivered

Cost examples

Leads requested	Total cost	Cost per lead
10 leads	$2.60	$0.26
25 leads	$3.50	$0.14
50 leads	$5.00	$0.10
100 leads	$8.00	$0.08
200 leads	$14.00	$0.07

The more leads you request, the lower your cost per lead. You're never charged for leads that don't meet your confidence threshold — only qualified, AI-verified results count.

How it compares to alternatives

Feature	This Actor	Apollo.io	PhantomBuster	Other Apify Actors
Pricing model	Pay per lead ($0.06)	Monthly subscription ($49-149/mo)	Monthly credits ($69-159/mo)	Per-run or monthly
AI lead scoring	Yes (confidence 0-1)	Basic filters only	No	No
AI noise filtering	Yes (removes non-companies)	N/A	N/A	No
AI search expansion	Yes (3x query variation)	No	No	No
Company data included	Full (size, revenue, location, industry)	Partial (some gated)	Minimal	Varies
LinkedIn profiles	Yes	Yes (with limits)	Yes	Varies
Seniority filtering	Yes (9 levels)	Yes	No	Rarely
Department filtering	Yes (12 departments)	Yes	No	No
Excel export	Yes (auto-generated)	CSV only	CSV only	Usually no
No subscription required	Yes	No	No	Varies

Input configuration

Required fields (just 3)

• Job Titles — The roles you're looking for (e.g., "CTO", "VP of Sales"). Comma-separate variations: "CTO, Chief Technology Officer"
• Target Industries — Industries to search (e.g., "SaaS & Cloud Platforms", "Fintech", "Healthcare IT")
• Target Locations — Where to look (e.g., "California", "United Kingdom", "Berlin")

Everything else is optional and has sensible defaults.

People filters

Field	Description	Default
Seniority Level	Filter by Founder, C-Suite, VP, Director, Head, Manager, Senior, Entry, or Intern	C-Suite, VP, Director, Head
Department	Filter by Executive, Engineering, Product, Marketing, Sales, Finance, Operations, HR, IT, Legal, Support	All departments
Exclude Job Titles	Remove leads containing specific keywords (e.g., "intern", "assistant", "freelance")	None

Company filters

Field	Description	Default
Company Description	Natural language description of target companies for better AI matching	None
Company Keywords	Extra keywords to refine auto-generated searches (e.g., "AI", "developer tools")	None
Min Employees	Only include companies with at least this many employees	50
Max Employees	Exclude companies above this size. Set to 0 for no limit	No limit

Location filters

Field	Description	Default
Exclude Locations	Remove leads from specific regions (e.g., "India", "China")	None

Search configuration

Field	Description	Default
Search Queries	Override auto-generated queries with your own custom search terms	Auto-generated
Similar Company URLs	Provide websites of ideal customers to discover more companies like them	None
Exclude Domains	Skip your own company, existing customers, or competitors	None

Quality controls

Field	Description	Default
Maximum Leads	Number of leads to return (10-500). More leads = lower cost per lead	50
Min Confidence Score	AI relevance threshold (0.0-1.0). Use 0.7+ for tighter targeting	0.6
Enable AI Enhancement	AI-powered query expansion, noise filtering, and lead scoring	ON
Run Label	Tag this run for your reference (e.g., "Q1 DACH outreach")	None

Output fields

Each lead in the dataset contains:

Field	Description
companyName	Company name
companyDomain	Primary domain (e.g., stripe.com)
companyWebsite	Full website URL
companyIndustry	Industry classification
companySize	Size category (e.g., 51-200 employees)
companyEmployeeCount	Estimated employee count
companyRevenue	Estimated revenue range
companyLocation	Company headquarters location
companyFoundedYear	Year the company was founded
companyDescription	Brief company description
contactName	Full name of the contact
contactTitle	Job title
contactLinkedIn	LinkedIn profile URL
contactLocation	Contact's location
seniority	Seniority level (Founder, C-Suite, VP, Director, Head, Manager, Senior, Entry)
geoTier	Geographic tier based on your target locations
confidenceScore	AI relevance score (0.0-1.0)
confidenceReason	Explanation of the confidence score

Additional outputs

• OUTPUT.xlsx — Pre-formatted Excel workbook with leads, companies, and stats sheets (Key-Value Store)
• stats.json — Detailed pipeline statistics including companies discovered, hit rates, costs, and LLM usage

How the AI pipeline works

This actor goes beyond simple keyword matching. Here's what happens under the hood:

1. Query Expansion — AI generates 3 semantic variations per search query to discover companies you wouldn't find with keywords alone
2. Company Discovery — Semantic web search finds companies matching your criteria (not just keyword matching)
3. Similar Company Discovery — If you provide example company URLs, finds more companies like them
4. Noise Classification — AI reviews every search result and removes non-company pages (blog posts, job boards, directories)
5. Size Validation — Filters companies by employee count using entity data. Unknown size = included (benefit of the doubt)
6. People Search — Finds individuals at each qualifying company matching your target job titles
7. Smart Retry — If no people are found at a company, AI generates alternative search queries and tries again
8. Lead Assembly — Deduplicates by LinkedIn URL, classifies seniority and geography
9. Confidence Scoring — AI scores every lead (0.0-1.0) based on how well they match your ideal customer profile
10. Quality Filtering — Removes leads below your confidence threshold, keeps the best matches

Tips for best results

• Be specific with job titles — "VP of Engineering" works better than just "VP". Comma-separate variations: "VP of Engineering, Head of Engineering"
• Use company description — A natural language description like "B2B startups building developer tools" significantly improves AI matching accuracy
• Start with 25-50 leads — Run a small batch first to verify the results match your expectations, then scale up
• Adjust confidence threshold — Default 0.6 works well for broad searches. Use 0.7+ when you need tighter targeting and are willing to get fewer leads
• Use Similar Company URLs — If you know 2-3 ideal customer websites, add them to discover more companies like them. This is often the highest-quality discovery method
• Combine filters — Seniority + Department + Location filters applied together produce highly targeted lists

Integrations

Export your leads in any format from the Apify console:

• JSON — Direct API access for CRM imports
• CSV — Import into Google Sheets, Excel, or any spreadsheet tool
• Excel (.xlsx) — Pre-formatted workbook with leads, companies, and stats sheets
• Webhooks — Trigger downstream workflows via Apify integrations
• API — Access results programmatically via the Apify API

Connect to your existing sales stack: HubSpot, Salesforce, Outreach, Apollo, Lemlist, or any tool that accepts CSV/JSON imports.

FAQ

How fresh is the data? The actor searches the live web on every run. Company data and LinkedIn profiles reflect current information at the time of the search — no stale databases.

Does this scrape LinkedIn directly? No. The actor uses semantic search APIs to discover companies and find people. It does not log into LinkedIn, scrape LinkedIn pages, or violate LinkedIn's terms of service. LinkedIn profile URLs are extracted from publicly indexed web data.

How is this different from other lead scrapers? AI is used at every stage: query expansion, noise filtering, people matching, and confidence scoring. Traditional scrapers return raw results without quality assessment. You get fewer but more relevant leads.

Why no email addresses or phone numbers? This actor focuses on discovering the right people at the right companies with high confidence. Email finding and phone lookup are separate enrichment steps — we recommend pairing results with a dedicated enrichment tool like Hunter.io or Apollo for email verification.

What's the difference between confidence score and seniority level? Seniority level is a categorical filter (VP, Director, etc.) based on job title patterns. Confidence score is an AI-generated relevance rating (0.0-1.0) that considers the entire lead — title, company, industry, location — against your ideal customer profile.

Can I use custom search queries instead of auto-generated ones? Yes. Add your own search queries under "Search Configuration" and the actor will use those instead of auto-generating from your industry + location settings.

What if I get fewer leads than requested? The actor returns the best matching leads up to your maximum. If there aren't enough qualifying leads in your target market, you'll get fewer. You're only charged for leads actually delivered. Try broadening your industries, locations, or seniority levels.

How do I reduce cost per lead? Request more leads in a single run. The $2.00 base fee is fixed, so larger batches have a lower per-lead cost. 200 leads = $0.07/lead vs. 10 leads = $0.26/lead.

Can I exclude my existing customers or competitors? Yes. Add their domains to the "Exclude Domains" field and they'll be removed from all results.

What happens if processing costs exceed the budget? The actor has a built-in cost guard. If processing costs approach the internal limit, it stops gracefully and returns whatever leads have been discovered so far. You always get partial results — never an empty run.

What markets does this work best for? Best results for English-language markets (US, UK, Canada, Australia, Western Europe). Works for any market, but company and people data coverage is highest in English-speaking regions.

Data privacy

This actor discovers publicly available business information from the open web. No LinkedIn login is used, no private data is accessed. Users are responsible for compliance with applicable data protection laws (GDPR, CCPA, etc.) when using the output data for outreach.

Changelog

• v1.0 — Initial public release. AI-powered company discovery, people search, lead scoring, seniority/department/location filtering, Excel export, pay-per-event pricing.