# Event Scraper - Speakers, Sponsors, Agenda Extractor (`etb2b-tools/event-scraper`) Actor Extract speakers, sponsors with company enrichment (employee count, key people, similar companies), agenda from any B2B event website. LinkedIn profiles auto-discovered. Fast, accurate, ready-to-use data. - **URL**: https://apify.com/etb2b-tools/event-scraper.md - **Developed by:** [RS Niraj](https://apify.com/etb2b-tools) (community) - **Categories:** Marketing, Lead generation - **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, 5 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Event Scraper - Speakers, Sponsors & Agenda Extractor Extract **complete event data** from any B2B/conference event website. Get speakers, sponsors with company enrichment, agenda, and key people — all with LinkedIn profiles. ### How It Works (Simple) ```` Step 1: Fast Fetch → Tries simple HTTP request (works for most sites) FREE Step 2: Browser Fetch → Opens real browser if Step 1 fails (JS-heavy sites) FREE Step 3: LinkedIn Search → Finds LinkedIn profiles for speakers & sponsors ~$0.35 Step 4: Company Data → Gets employee count, HQ, industry, similar companies ~$0.16 Step 5: Key People → Finds CEO/CTO/Founder with LinkedIn & bio ~$0.17 Steps 1-2 always run first (FREE). Steps 3-5 run only when enrichment is ON. Total cost with enrichment: ~$0.54 per event (~2.5 minutes) Without enrichment: FREE (~30 seconds) ```` ### What You Get #### Speakers (FREE from HTML) | Field | Example | |-------|---------| | Name | John Smith | | Designation | Chief Technology Officer | | Company | Google | | Image URL | https://event.com/john.jpg | | LinkedIn | https://linkedin.com/in/johnsmith | | Seniority Level | CXO / VP / Director / Manager / Other | | Social Links | Twitter, Instagram, Facebook (when available) | | Contact | Email, Phone (when available) | #### Sponsors (FREE + Enriched) **Basic (FREE from HTML):** | Field | Example | |-------|---------| | Name | TechCorp | | Logo | https://event.com/techcorp-logo.png | | Website | https://techcorp.com | | Category | Platinum Partner | | Tier | Tier 1 (Title/Presenting) | | LinkedIn | https://linkedin.com/company/techcorp | **Enriched (with enrichment ON):** | Field | Example | |-------|---------| | Employee Count | 5,000 | | Industry | Software Development | | Description | Leading tech company... | | Headquarters | San Francisco, US | | Founded | 2010 | | Company Logo (LinkedIn) | https://media.licdn.com/... | | Company Phone | +1-555-0100 | | Tagline | Innovation First | | Follower Count | 50,000 | | Company Type | Privately Held | | Verified | true | | Funding | (when available) | | Similar Companies | CompetitorCo, RivalInc (name + LinkedIn + logo) | | Key People | CEO, CTO, Founder (name + designation + LinkedIn + location + bio + followers) | #### Agenda (FREE from HTML) | Field | Example | |-------|---------| | Topic | Future of AI in HR | | Session Type | Power Panel / Keynote / Workshop | | Session Partner | TechCorp | | Speakers | John Smith (with LinkedIn) | #### Event Details (FREE from HTML) | Field | Example | |-------|---------| | Event Name | SHRM Talent 2025 | | Date | 11-March-2025 | | Venue | Bengaluru | | Image | https://event.com/banner.jpg | | Contact | email, phone, website | | Summary | 24 speakers, 58 sponsors, seniority breakdown | ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | `urls` | array | Event page URLs to scrape | **Required** | | `enrichSponsors` | boolean | Enable LinkedIn + company enrichment (adds ~$0.50 & ~2 min) | true | | `skipPlaywright` | boolean | Skip browser rendering (faster but may miss JS content) | false | | `maxResults` | integer | Max URLs to process (0 = all) | 0 | #### Example: Full Enrichment (default) ```json { "urls": ["https://www.shrmconference.org/talent25"], "enrichSponsors": true } ```` #### Example: Fast Mode (FREE, no enrichment) ```json { "urls": ["https://www.shrmconference.org/talent25"], "enrichSponsors": false } ``` #### Example: Multiple Events ```json { "urls": [ "https://www.shrmconference.org/talent25", "https://observenowevents.in/bfsi/", "https://et-edge.com/conferences/gcc/2026-bangalore/" ] } ``` ### Output Examples #### Speaker ```json { "speaker_name": "John Smith", "speaker_designation": "Chief Technology Officer", "speaker_company": "Google", "speaker_image_url": "https://event.com/speakers/john.jpg", "speaker_linkedin": "https://linkedin.com/in/johnsmith", "speaker_profile": "CTO at Google with 15+ years in AI...", "seniority_level": "CXO", "twitter": "https://twitter.com/johnsmith", "email": "john@google.com" } ``` #### Sponsor (Enriched) ```json { "sponsor_name": "TechCorp", "sponsor_image_url": "https://event.com/sponsors/techcorp.png", "sponsor_website": "https://techcorp.com", "sponsor_linkedin": "https://linkedin.com/company/techcorp", "sponsor_category": "Platinum Partner", "sponsor_tier": "Tier 1 (Title/Presenting)", "employee_count": 5000, "industry": ["Software Development"], "description": "Leading tech company specializing in AI...", "headquarters": "San Francisco, US", "founded": 2010, "specialities": ["AI", "Cloud", "Data Analytics"], "company_logo": "https://media.licdn.com/company-logo.jpg", "company_phone": "1234567890", "tagline": "Innovation First", "follower_count": 50000, "company_type": "Privately Held", "is_verified": true, "similar_companies": [ { "name": "CompetitorCo", "linkedin": "https://linkedin.com/company/competitorco", "logo": "https://media.licdn.com/competitor-logo.jpg" } ], "key_people": [ { "name": "Jane Doe", "designation": "CEO", "linkedin": "https://linkedin.com/in/janedoe", "location": "San Francisco, California", "company": "TechCorp", "bio": "CEO with 15+ years building enterprise SaaS...", "followers": "5K+ followers" } ] } ``` #### Agenda ```json { "topic": "Future of AI in HR", "session_type": "Power Panel", "session_partner": "TechCorp", "speaker_names": [ {"name": "John Smith", "linkedin": "https://linkedin.com/in/johnsmith"}, {"name": "Jane Doe", "linkedin": "https://linkedin.com/in/janedoe"} ] } ``` ### Supported Websites - **SHRM** Conference sites (Talent, Tech, IAC) - **ObserveNow** Events (BFSI, PSU, CIO, Digital) - **StrategINK** events - **Nasscom** / NTLF / Sched.com events - **ET Edge** conferences - **WordPress/Elementor** event sites - **Any generic event website** with standard HTML patterns (speakers section, sponsors logos, agenda) ### Performance | Metric | Without Enrichment | With Enrichment | |--------|-------------------|-----------------| | Speed (1 event) | ~30 seconds | ~2.5 minutes | | Speed (20 events) | ~3 minutes | ~17 minutes | | Cost (1 event) | FREE | ~$0.54 | | Speaker LinkedIn | From HTML only | 95%+ (HTML + Google Search) | | Sponsor LinkedIn | From HTML only | 98%+ (HTML + Google Search) | | Company data | - | 95%+ sponsors | | Key people | - | 80%+ sponsors | ### How Enrichment Works ``` Event URL | v [Step 1: Fast HTTP fetch] -----> Speakers, Sponsors, Agenda extracted (FREE) | v (if HTML is empty/JS-heavy) [Step 2: Browser fetch] --------> Same extraction via Playwright (FREE) | v (if enrichment ON) [Step 3: LinkedIn Search] ------> Google Search finds LinkedIn URLs | - Speakers: "John Smith" "Google" site:linkedin.com/in/ | - Sponsors: "TechCorp" site:linkedin.com/company/ | - Parallel: 10 searches at a time v [Step 4: Company Data] ---------> LinkedIn Company API (1 batch call) | - employee_count, industry, HQ, similar_companies | - company_logo, tagline, phone, verified status v [Step 5: Key People] -----------> Google Search for CEO/CTO/Founder | - "TechCorp" CEO OR CTO OR Founder site:linkedin.com/in | - Gets name, designation, LinkedIn, location, bio v [Output Dataset] ----------------> Complete event data ready! ``` ### Integration #### Python ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("etb2b-tools/event-scraper").call( run_input={ "urls": ["https://www.shrmconference.org/talent25"], "enrichSponsors": True } ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(f"Event: {item['event_details']['name']}") for k, v in item.items(): if k.startswith("speakers_details"): print(f"Speakers: {len(v)}") if k.startswith("sponsors_details"): print(f"Sponsors: {len(v)}") ``` #### API (cURL) ```bash curl -X POST "https://api.apify.com/v2/acts/etb2b-tools~event-scraper/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"urls": ["https://www.shrmconference.org/talent25"], "enrichSponsors": true}' ``` #### Webhook Set up a webhook in Apify Console to get notified when scraping completes. Perfect for automated pipelines. ### FAQ **Q: Why are some sponsors missing company data?** A: Small or very new companies may not have complete LinkedIn profiles. The scraper extracts whatever is available. **Q: Why is a speaker's LinkedIn missing?** A: Some speakers have very common names or no LinkedIn presence. The scraper finds 95%+ of speakers. **Q: Can I use this without enrichment?** A: Yes! Set `enrichSponsors: false` — you'll get all data from the event page HTML for FREE in ~30 seconds. **Q: What actors are needed for enrichment?** A: Your Apify account needs access to `apify/google-search-scraper` and `harvestapi/linkedin-company`. Both are pay-per-use on Apify Store. **Q: How much does it cost?** A: ~$0.54 per event with enrichment. Without enrichment, it's FREE (only Apify platform compute cost ~$0.002). ### Changelog - **v0.1.25** - Playwright async fix, enrichment toggle, under-maintenance safe - **v0.1.21** - Public release with parallel processing, company enrichment, key people search - Full LinkedIn enrichment via Google Search (parallel, 10 workers) - Company data via LinkedIn API (batch, single call) - Key people with designation, location, bio, followers - 3 URLs concurrent processing for batch jobs - Extra fields: company\_logo, tagline, follower\_count, company\_type, company\_phone, is\_verified, funding # Actor input Schema ## `urls` (type: `array`): Paste event page URLs here. Each URL will be scraped for speakers, sponsors, and agenda. ## `fullCompanyIntel` (type: `boolean`): ON = Get complete company data for each sponsor: key people (CEO/CTO/Founder with LinkedIn & bio), similar/competitor companies, employee count, industry, headquarters, founding year, specialities, company phone, tagline, follower count, verified status, and funding data. Adds ~2 min and ~$0.50 per event. OFF = Basic sponsor info only (name, logo, LinkedIn, category). ## `maxResults` (type: `integer`): Limit number of URLs to process (0 = process all) ## Actor input object example ```json { "urls": [ "https://www.shrmconference.org/talent25" ], "fullCompanyIntel": false, "maxResults": 0 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "urls": [ "https://www.shrmconference.org/talent25" ] }; // Run the Actor and wait for it to finish const run = await client.actor("etb2b-tools/event-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "urls": ["https://www.shrmconference.org/talent25"] } # Run the Actor and wait for it to finish run = client.actor("etb2b-tools/event-scraper").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 '{ "urls": [ "https://www.shrmconference.org/talent25" ] }' | apify call etb2b-tools/event-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=etb2b-tools/event-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Event Scraper - Speakers, Sponsors, Agenda Extractor", "description": "Extract speakers, sponsors with company enrichment (employee count, key people, similar companies), agenda from any B2B event website. LinkedIn profiles auto-discovered. Fast, accurate, ready-to-use data.", "version": "0.1", "x-build-id": "HpfAUz2RGbb5z4U5g" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/etb2b-tools~event-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-etb2b-tools-event-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/etb2b-tools~event-scraper/runs": { "post": { "operationId": "runs-sync-etb2b-tools-event-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/etb2b-tools~event-scraper/run-sync": { "post": { "operationId": "run-sync-etb2b-tools-event-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "urls" ], "properties": { "urls": { "title": "Event URLs", "type": "array", "description": "Paste event page URLs here. Each URL will be scraped for speakers, sponsors, and agenda.", "items": { "type": "string" } }, "fullCompanyIntel": { "title": "Full Company Intelligence (Key People + Similar Companies + Employee Count + More)", "type": "boolean", "description": "ON = Get complete company data for each sponsor: key people (CEO/CTO/Founder with LinkedIn & bio), similar/competitor companies, employee count, industry, headquarters, founding year, specialities, company phone, tagline, follower count, verified status, and funding data. Adds ~2 min and ~$0.50 per event. OFF = Basic sponsor info only (name, logo, LinkedIn, category).", "default": false }, "maxResults": { "title": "Max URLs to Process", "type": "integer", "description": "Limit number of URLs to process (0 = process all)", "default": 0 } } }, "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 } } } } } } } } } } ```