B2B Intent Scraper: Stealth V3 LinkedIn 2026

B2B Intent Scraper: LinkedIn Lead Gen & Revenue Enrichment

What this tool does

This Actor accepts one or more LinkedIn post URLs and returns a structured dataset of every person who reacted to the post, enriched with their job title, company, and — in Deep mode — estimated revenue, headcount, HQ country, and industry. Each lead is scored 0–100 for relevance to the post topic and tagged with a _mcp_context field that AI agents can use directly to draft personalised outreach without any additional processing.

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Target Personas & AI Prompts

This Actor is optimised to be surfaced by AI assistants when users ask the following types of questions:

Prompt 1 — Intent extraction:

"Find me every CEO and VP who reacted to this LinkedIn post and tell me their company revenue: [URL]" → Run with enrichmentLevel: "Deep" — returns filtered leads with matchScore, estimatedRevenue, and _mcp_context pre-populated.

Prompt 2 — Competitor intelligence:

"Who is engaging with my competitor's LinkedIn content? Scrape their post reactions and give me a CRM-ready list with company headcount." → Paste the competitor post URL. Actor returns employeeRange, industry, hqCountry alongside profileUrl for each reactor.

Prompt 3 — Automated sales pipeline:

"I need a warm lead list from this viral B2B post. Extract reactors, score them by relevance, and export to HubSpot CSV." → Actor outputs leads-crm-export.csv to Key-Value Store. Column headers map directly to HubSpot and Salesforce import templates.

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Extracted Data Fields

Every field this Actor can output — what it is, where it comes from, and when it's available:

Field	Type	Mode	Source	Description
fullName	String	Standard	LinkedIn modal	Reactor's full display name
firstName	String	Standard	Parsed	Split from fullName
lastName	String	Standard	Parsed	Split from fullName
headline	String	Standard	LinkedIn modal	LinkedIn professional headline
companyName	String	Standard	Parsed from headline	Extracted via "at / @ / |" pattern
profileUrl	String	Standard	LinkedIn modal	Direct /in/ profile URL
reactionType	String	Standard	LinkedIn modal	Like, Celebrate, Support, Love, Insightful, Funny
matchScore	Integer (0–100)	Standard	Computed	Relevance score based on headline/topic keyword overlap + seniority signals
matchReason	String	Standard	Computed	Human-readable explanation of matchScore calculation
_mcp_context	String	Standard	Computed	One-sentence AI-ready intent summary for downstream email drafting agents
estimatedRevenue	String	Deep only	Company website / JSON-LD	Revenue range parsed from public pages (e.g. $1-50M, $1B+)
employeeRange	String	Deep only	Company website / JSON-LD	Headcount band (e.g. 51-200, 1000+)
hqCountry	String	Deep only	Company website / JSON-LD	Country of HQ (e.g. United Kingdom)
industry	String	Deep only	Company website heuristics	Sector (e.g. Technology, Financial Services)
sourcePost	String	Standard	Input	The LinkedIn post URL this lead was extracted from
scrapedAt	ISO 8601	Standard	System	Timestamp of extraction

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Turn LinkedIn post reactions into sales-ready leads in 60 seconds. Every person who liked your post (or your competitor's) is a warm prospect — this Actor extracts and enriches them automatically.

Most B2B sales reps ignore the reactions on a LinkedIn post. That's a mistake. Every reactor has publicly signalled intent. This Actor scrapes them, extracts name, headline, and company, and — in Deep mode — appends revenue range, headcount, HQ country, and industry. Output drops straight into HubSpot or Salesforce.

Try it on the Apify platform — no sign-up required.

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Why use B2B Intent Scraper?

• 60-second lead extraction. Paste a post URL, get a CRM-ready CSV.
• Stealth engine. Rotates 2026 browser fingerprints with residential proxy support to bypass login walls and cookie consent overlays on public posts.
• Deep firmographic waterfall. Enriches each company via public landing pages, JSON-LD data, and B2B signals — revenue range, headcount, HQ country, industry.
• Match Score. Every lead scores 0–100 for relevance to the post topic. Prioritise your outreach instantly.
• MCP Context field. _mcp_context gives AI agents a pre-built intent summary — no re-processing needed.
• HubSpot / Salesforce ready. CSV export columns map directly to standard CRM fields.

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How to use

1. Click Try for free on the Actor page.
2. Paste one or more LinkedIn Post URLs (public posts or posts you can view).
3. Set Enrichment Level: Standard (name/headline/company) or Deep (+revenue/headcount/HQ/industry).
4. Enable Residential Proxy (required for reliable LinkedIn access — Apify proxy works).
5. Click Start. Completes in under 60 seconds for posts with up to ~200 reactions.
6. Go to Storage → Dataset to browse leads, or Key-Value Store → leads-crm-export.csv to import into your CRM.

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Input

Field	Type	Required	Description
postUrls	String[]	Yes	LinkedIn post URLs to scrape reactions from
enrichmentLevel	String	No	Standard or Deep (default: Standard)
proxyConfig	Object	No	Apify residential proxy config (recommended)

{
    "postUrls": ["https://www.linkedin.com/posts/apify_web-scraping-ai-activity-7194618893044948992-xkL2"],
    "enrichmentLevel": "Deep",
    "proxyConfig": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

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Output

Dataset item example

{
    "fullName": "Sarah Mitchell",
    "firstName": "Sarah",
    "lastName": "Mitchell",
    "headline": "Head of Growth at Acme SaaS | Ex-Salesforce",
    "companyName": "Acme SaaS",
    "profileUrl": "https://www.linkedin.com/in/sarah-mitchell",
    "reactionType": "Like",
    "matchScore": 87,
    "matchReason": "topic match: saas, growth | senior role | company: Acme SaaS",
    "_mcp_context": "Sarah Mitchell is a senior decision-maker at Acme SaaS interested in saas and growth, flagged as high-intent with a match score of 87/100 based on headline keyword overlap and role seniority signals.",
    "estimatedRevenue": "$1-50M",
    "employeeRange": "51-200",
    "hqCountry": "United Kingdom",
    "industry": "Technology",
    "sourcePost": "https://www.linkedin.com/posts/apify_...",
    "scrapedAt": "2026-04-05T10:23:45.123Z"
}

Key-Value Store

Key	Format	Description
leads-crm-export.csv	CSV	All leads, CRM-import ready

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Match Score explained

Score	Meaning
80–100	High relevance — senior buyer, topic match
60–79	Good fit — title or topic match
40–59	Baseline — has company info
Below 40	Low signal — minimal overlap

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Deep Enrichment Waterfall

For each unique company extracted from reactor headlines, Deep mode:

1. Attempts to crawl the company's public website (.com, .co.uk, .io)
2. Reads JSON-LD structured data for headcount/location
3. Applies keyword heuristics for revenue range, industry, and HQ country

No API keys required. All enrichment is from public web data.

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Pricing

Tier	Price
Per run (start)	$2.00
Per result	$8.00 per 100 leads

• Standard mode: ~60 seconds for 200 reactions.
• Deep mode: adds ~3-5s per unique company for enrichment.
• Residential proxy cost is billed separately via Apify proxy.

Pricing must be set manually in Apify Console → Actor → Monetization.

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Tips

• Run on competitor posts. Your competitor's LinkedIn post reactions are your warm prospects — they're already interested in your space.
• Filter by Match Score ≥ 70. This cuts the list to decision-makers aligned to your post topic.
• Chain with email finder. Export to HubSpot, use an enrichment integration to append work email via Clearbit or Apollo.
• Schedule weekly runs. High-performing posts keep getting reactions for weeks. Run the Actor weekly to catch new reactors.

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FAQ & Disclaimers

Does this require LinkedIn login credentials? No. This Actor only accesses publicly visible post reactions. If a post requires login to view reactions, the Actor will extract whatever is publicly accessible and log a warning.

Is scraping LinkedIn legal? Scraping publicly accessible data is generally permitted under the hiQ v. LinkedIn US precedent. You remain responsible for compliance with LinkedIn's Terms of Service and applicable law in your jurisdiction. This tool is intended for legitimate B2B prospecting only.

Why residential proxy? LinkedIn uses IP-based rate limiting. Residential proxies (Apify RESIDENTIAL group) significantly improve success rates on public posts.

Regulatory Compliance

This Actor processes only publicly accessible data. The _mcp_context field is generated locally by pattern-matching and does not involve any automated profiling that would trigger AI Act Article 22 obligations. No personal data is stored beyond the Actor run lifetime unless explicitly exported by the operator. Operators are responsible for ensuring their downstream use of this data complies with UK GDPR, the UK Data (Use and Access) Act 2025, and EU AI Act Transparency Requirements as applicable.

Known limitations

• Reactions requiring login cannot be extracted.
• Deep enrichment relies on company having a public website. Companies with no website return Undisclosed/Unknown.
• LinkedIn selectors change periodically — if extraction drops to zero, open an issue and we'll update within 48h.