# B2B Intent Scraper: Stealth V3 LinkedIn 2026 (`automationnation/b2b-intent-enricher`) Actor Turn LinkedIn post reactions into sales-ready leads in 60 seconds. Extracts name, headline, and company from every reactor — then Deep mode appends revenue range, headcount, HQ country, and industry. Outputs a CRM-import-ready dataset with match scores for HubSpot or Salesforce. - **URL**: https://apify.com/automationnation/b2b-intent-enricher.md - **Developed by:** [Nathan Carter](https://apify.com/automationnation) (community) - **Categories:** Lead generation, Automation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $150.00 / 1,000 enriched intent lead packs This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ### 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. --- #### 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. --- #### 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 | --- **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](https://apify.com) — no sign-up required. --- ### 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. --- ### 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. --- ### 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) | ```json { "postUrls": ["https://www.linkedin.com/posts/apify_web-scraping-ai-activity-7194618893044948992-xkL2"], "enrichmentLevel": "Deep", "proxyConfig": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` *** ### Output #### Dataset item example ```json { "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 | *** ### 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 | *** ### 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. *** ### 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.* *** ### 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. *** ### 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. # Actor input Schema ## `postUrls` (type: `array`): Paste one or more public LinkedIn post URLs. Every person who reacted to each post will be extracted and enriched. Use competitor posts to build warm prospect lists from people already interested in your space. ## `enrichmentLevel` (type: `string`): Standard returns name, headline, company, and Match Score. Deep also crawls each company's public website to append estimated revenue range, employee headcount, HQ country, and industry — used to calculate firmographic fit for outbound campaigns. ## `proxyConfig` (type: `object`): Residential proxy is strongly recommended. LinkedIn applies IP-based rate limiting that blocks datacenter IPs on most public posts. Apify's RESIDENTIAL proxy group provides clean IP rotation and significantly improves extraction success rate. ## Actor input object example ```json { "postUrls": [ "https://www.linkedin.com/posts/apify_web-scraping-ai-activity-7194618893044948992-xkL2" ], "enrichmentLevel": "Standard", "proxyConfig": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "postUrls": [ "https://www.linkedin.com/posts/apify_web-scraping-ai-activity-7194618893044948992-xkL2" ], "proxyConfig": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("automationnation/b2b-intent-enricher").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "postUrls": ["https://www.linkedin.com/posts/apify_web-scraping-ai-activity-7194618893044948992-xkL2"], "proxyConfig": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("automationnation/b2b-intent-enricher").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "postUrls": [ "https://www.linkedin.com/posts/apify_web-scraping-ai-activity-7194618893044948992-xkL2" ], "proxyConfig": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call automationnation/b2b-intent-enricher --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automationnation/b2b-intent-enricher", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "B2B Intent Scraper: Stealth V3 LinkedIn 2026", "description": "Turn LinkedIn post reactions into sales-ready leads in 60 seconds. Extracts name, headline, and company from every reactor — then Deep mode appends revenue range, headcount, HQ country, and industry. Outputs a CRM-import-ready dataset with match scores for HubSpot or Salesforce.", "version": "0.1", "x-build-id": "4GzfJCqzpnfqMdIl0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automationnation~b2b-intent-enricher/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automationnation-b2b-intent-enricher", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automationnation~b2b-intent-enricher/runs": { "post": { "operationId": "runs-sync-automationnation-b2b-intent-enricher", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automationnation~b2b-intent-enricher/run-sync": { "post": { "operationId": "run-sync-automationnation-b2b-intent-enricher", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "postUrls" ], "properties": { "postUrls": { "title": "LinkedIn Post URLs", "type": "array", "description": "Paste one or more public LinkedIn post URLs. Every person who reacted to each post will be extracted and enriched. Use competitor posts to build warm prospect lists from people already interested in your space.", "items": { "type": "string" } }, "enrichmentLevel": { "title": "Enrichment Level", "enum": [ "Standard", "Deep" ], "type": "string", "description": "Standard returns name, headline, company, and Match Score. Deep also crawls each company's public website to append estimated revenue range, employee headcount, HQ country, and industry — used to calculate firmographic fit for outbound campaigns.", "default": "Standard" }, "proxyConfig": { "title": "Proxy Configuration", "type": "object", "description": "Residential proxy is strongly recommended. LinkedIn applies IP-based rate limiting that blocks datacenter IPs on most public posts. Apify's RESIDENTIAL proxy group provides clean IP rotation and significantly improves extraction success rate." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```