# Event Organizer Leads — Emails & LinkedIn from Luma (`avinashchby/event-organizer-leads`) Actor Extract organizer names, emails, LinkedIn URLs, and websites from Luma and Eventbrite event pages. Paste event URLs or run a keyword search — get a cold outreach-ready lead list in minutes. No API key needed. - **URL**: https://apify.com/avinashchby/event-organizer-leads.md - **Developed by:** [Avinash](https://apify.com/avinashchby) (community) - **Categories:** Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## 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 Organizer Lead Extractor > **What this actor does:** Visits Luma and Eventbrite event pages and extracts organizer contact info — name, email, LinkedIn, website, Instagram, and Twitter. Turn a list of event URLs (or a keyword search) into an outreach-ready lead list. ### Features - **Two input modes**: URL list mode OR keyword search mode - Extracts: organizer name, email, LinkedIn URL, website, Instagram, Twitter - Supports **Luma** (lu.ma) and **Eventbrite** event pages - In search mode: auto-discovers event URLs then visits each page - No API key required - Output: structured JSON compatible with Apollo, Instantly, Smartlead, and HubSpot CSV import ### Use Cases - **Cold email outreach**: Find emails of event organizers in your niche - **Partnership development**: Identify companies running events in your space - **Sponsorship prospecting**: Discover organizers of conferences and summits to sponsor - **Community research**: Map who's organizing events in a specific city or industry - **Sales intelligence**: Build targeted lists of event-driven companies ### Input Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `eventUrls` | array | List of Luma or Eventbrite event URLs | — | | `query` | string | Search keyword (if no URLs provided) | — | | `source` | string | "luma", "eventbrite", or "both" (search mode) | "luma" | | `city` | string | City filter for search mode | — | | `maxResults` | number | Max leads to extract | 50 | ### Output Fields | Field | Description | |-------|-------------| | `eventName` | Event title | | `eventUrl` | Event page URL | | `eventDate` | ISO 8601 event date | | `organizerName` | Organizer or host name | | `organizerEmail` | Email address (if publicly listed) | | `organizerLinkedIn` | LinkedIn company or profile URL | | `organizerWebsite` | External website URL | | `organizerInstagram` | Instagram URL | | `organizerTwitter` | Twitter/X URL | | `source` | "luma" or "eventbrite" | | `scrapedAt` | Scrape timestamp | ### Example Input — URL Mode ```json { "eventUrls": [ "https://lu.ma/ai-founders-dinner", "https://www.eventbrite.com/e/startup-summit-2026-tickets-123456789" ], "maxResults": 50 } ```` ### Example Input — Search Mode ```json { "query": "AI startup networking", "source": "luma", "city": "San Francisco", "maxResults": 30 } ``` ### Example Output ```json { "eventName": "AI Founders Dinner SF", "eventUrl": "https://lu.ma/ai-founders-dinner", "eventDate": "2026-05-20T19:00:00.000Z", "organizerName": "Sarah Chen", "organizerEmail": "sarah@aistartups.com", "organizerLinkedIn": "https://linkedin.com/company/ai-startups-sf", "organizerWebsite": "https://aistartups.com", "source": "luma", "scrapedAt": "2026-04-23T10:00:00.000Z" } ``` ### Questions answered by this actor - Who organizes AI events in San Francisco and how do I contact them? - What are the emails of startup conference organizers in London? - Which companies run the most tech networking events in New York? - How do I find LinkedIn profiles of hackathon organizers in my city? ### Data Extraction Methodology - **Luma events**: Extracts from `__NEXT_DATA__` JSON embedded in the page (host profiles with LinkedIn, Instagram, Twitter handles, website URLs) - **Eventbrite events**: Parses JSON-LD schema.org markup + scans page text for email addresses and social links - **Email detection**: Regex scan of full page text — finds emails in descriptions, contact sections - **LinkedIn detection**: Pattern matching for linkedin.com/company/ and linkedin.com/in/ URLs ### Frequently Asked Questions **Is this legal?** This actor collects only publicly available information that organizers have voluntarily published on public event pages. **How accurate are emails?** Emails are extracted from event descriptions and organizer profiles where they've been intentionally shared. Accuracy depends on how much info the organizer made public. **Can I use this for cold email?** Always comply with CAN-SPAM, GDPR, and applicable regulations in your jurisdiction. **What if an organizer has no contact info?** The actor returns the event and organizer name even if no email or LinkedIn is found — partial data is still useful for research. # Actor input Schema ## `eventUrls` (type: `array`): List of Luma or Eventbrite event page URLs to extract organizer info from. If provided, 'query' and 'source' are ignored. ## `query` (type: `string`): Keywords to search for events (used when eventUrls is empty). E.g. 'AI startup San Francisco'. ## `source` (type: `string`): Which platform to search when using keyword search mode. ## `city` (type: `string`): City to filter events by (search mode only) ## `maxResults` (type: `integer`): Maximum number of organizer leads to extract. Default: 50. ## Actor input object example ```json { "source": "luma", "maxResults": 50 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("avinashchby/event-organizer-leads").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 = {} # Run the Actor and wait for it to finish run = client.actor("avinashchby/event-organizer-leads").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 '{}' | apify call avinashchby/event-organizer-leads --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=avinashchby/event-organizer-leads", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Event Organizer Leads — Emails & LinkedIn from Luma", "description": "Extract organizer names, emails, LinkedIn URLs, and websites from Luma and Eventbrite event pages. Paste event URLs or run a keyword search — get a cold outreach-ready lead list in minutes. No API key needed.", "version": "1.0", "x-build-id": "v66hugZW9Wm0pwHdu" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/avinashchby~event-organizer-leads/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-avinashchby-event-organizer-leads", "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/avinashchby~event-organizer-leads/runs": { "post": { "operationId": "runs-sync-avinashchby-event-organizer-leads", "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/avinashchby~event-organizer-leads/run-sync": { "post": { "operationId": "run-sync-avinashchby-event-organizer-leads", "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", "properties": { "eventUrls": { "title": "Event URLs", "type": "array", "description": "List of Luma or Eventbrite event page URLs to extract organizer info from. If provided, 'query' and 'source' are ignored.", "items": { "type": "string" } }, "query": { "title": "Search keyword", "type": "string", "description": "Keywords to search for events (used when eventUrls is empty). E.g. 'AI startup San Francisco'." }, "source": { "title": "Source platform", "enum": [ "luma", "eventbrite", "both" ], "type": "string", "description": "Which platform to search when using keyword search mode.", "default": "luma" }, "city": { "title": "City", "type": "string", "description": "City to filter events by (search mode only)" }, "maxResults": { "title": "Max leads", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of organizer leads to extract. Default: 50.", "default": 50 } } }, "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 } } } } } } } } } } ```