# Eventbrite Email Scraper (`scraperoka/eventbrite-email-scraper`) Actor 📩 Eventbrite Email Scraper extracts attendee emails from event listings & tickets for smarter outreach. 🚀 Perfect for B2B lead gen, event marketing, and market research. Save time, boost targeting, and grow your pipeline—without manual scraping. - **URL**: https://apify.com/scraperoka/eventbrite-email-scraper.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ### Eventbrite Email Scraper 📬 **Eventbrite Email Scraper** helps you scrape emails from Eventbrite using your chosen keywords and email-domain filters. It’s built for anyone who needs to build an **Eventbrite email list builder** quickly—whether you’re a marketer, researcher, or lead-generation specialist—using **publicly available data** from Eventbrite profiles, bios, and posts related to your keywords, saving you hours of manual work. Whether you’re looking for an **Eventbrite attendee email list**, an **Eventbrite event organizer email scraper**, or an **Eventbrite participant email scraper**, this actor is designed to streamline **Eventbrite email harvesting** with keyword targeting and domain filtering so you can focus on outreach and analysis at scale. --- ### Why choose Eventbrite Email Scraper? | Feature | Benefit | | --- | --- | | ✅ **Keyword-based scraping** | Find emails from Eventbrite bios and posts related to your keywords using **Eventbrite email scraper** workflows | | ✅ **Custom email domain filters** | Target the inboxes you care about by using **Custom Email Domains** like `@gmail.com` | | ✅ **Max emails limit** | Control runtime and cost by stopping after **Max Emails** are collected (doesn’t guarantee the limit is reached) | | ✅ **Proxy support + resiliency** | Includes proxy configuration support and resilient request handling for more consistent **Eventbrite contact scraper** runs | | ✅ **Structured dataset output** | Each pushed record includes `network`, `keyword`, `title`, `description`, `url`, and `email` for easy import | | ✅ **Scales across multiple searches** | Works well for building an **Eventbrite bulk email scraper** dataset across keywords and filters | --- ### Key features - 🔍 **Keyword-driven Eventbrite email extraction**: Uses your provided keywords to discover relevant Eventbrite bios and posts for **Eventbrite event email extraction**. - 🌐 **Custom domain targeting**: Filters extracted emails to domains you specify via **Custom Email Domains**. - 🧠 **Prevents duplicates automatically**: Keeps track of already seen emails so you don’t re-collect the same **Eventbrite ticket buyer emails**. - 🛡️ **Reliability with engine choice**: Offers **engine** selection for **Cost Effective (New)** or **Legacy** behavior. - 💾 **Progress persistence**: Saves progress (including cursor position and `seen_emails`) during execution so long runs can be resumed. - 📊 **Dataset-ready records**: Pushes consistently structured rows to the default dataset as soon as emails are found. - 🔁 **Stops safely at your limit**: Respects **Max Emails** and stops when the limit is reached to help control scraping time. --- ### Input Provide input via an `input.json` file. Example structure: ```json { "keywords": ["song event"], "location": "", "platform": "Eventbrite", "customDomains": ["@gmail.com"], "maxEmails": 20, "engine": "legacy", "proxyConfiguration": {} } ```` #### Input Fields | Field | Required | Description | | --- | --- | --- | | `keywords` | ✅ Yes | A list of keywords to search for on Eventbrite. The scraper uses these keywords to find relevant Eventbrite bios and posts that may contain emails. | | `location` | ❌ No | Location to filter search results. Leave it empty (`""`) to not apply a location filter. | | `platform` | ❌ No | Select platform. The only supported option is `Eventbrite`. | | `customDomains` | ❌ No | List of custom email domains to target (for example, `@gmail.com`). The scraper filters extracted emails to those domains. | | `maxEmails` | ❌ No | Maximum number of emails to collect. The scraper stops once this limit is reached. Higher values may take longer and do not guarantee reaching the limit. | | `engine` | ❌ No | Choose scraping engine. `cost-effective` is **Cost Effective (New)**, and `legacy` is **Legacy**. | | `proxyConfiguration` | ❌ No | Proxy configuration for this Actor run (configure proxies here if you need custom network routing). | *** ### Output The actor pushes one JSON object per found email to the dataset as `Actor.pushData(row)`. Example output record: ```json { "network": "Eventbrite.com", "keyword": "song event", "title": "No title", "description": "No data", "url": "No URL", "email": "example@gmail.com" } ``` #### Output Fields | Field | Type | Description | | --- | --- | --- | | `network` | string | Source network label: `Eventbrite.com`. | | `keyword` | string | The keyword that led to this discovered result. | | `title` | string | Title text extracted from the result. | | `description` | string | Description/snippet text extracted from the result. | | `url` | string | The extracted result URL. | | `email` | string | The extracted email address (filtered by `customDomains`). | > Note: The actor stops when it reaches `maxEmails` (if set), but it may return fewer results if matching emails aren’t found. *** ### How to use Eventbrite Email Scraper (via Apify Console) 1. **Open Apify Console**\ Log in at https://console.apify.com and open the **Actors** section. 2. **Find Eventbrite Email Scraper**\ Search for **Eventbrite Email Scraper** and open the actor page. 3. **Configure the INPUT**\ In the **INPUT** panel, provide at least `keywords` (required). Add `customDomains` to control which inbox domains you want, and optionally set `maxEmails` to cap collection. 4. **Choose Engine (optional)**\ Set `engine` to `legacy` or `cost-effective` depending on your preference. For many workflows, leaving the default is fine. 5. **Set Proxy Configuration (optional)**\ If you need custom routing, fill in `proxyConfiguration`. The actor supports proxy configuration for more reliable runs. 6. **Run the actor**\ Click **Run**. During execution, you’ll see logs about pages fetched and emails being pushed. For large searches or high email limits, runs can take longer. 7. **Review results in OUTPUT**\ Open the dataset produced by the run and export it as JSON or CSV from the dataset view. No coding required—get Eventbrite email extraction results in minutes with **Eventbrite Email Scraper**. 🚀 *** ### Advanced features & SEO optimization - 🧩 **Engine choice for Eventbrite email scraper runs**: Switch between `cost-effective` and `legacy` to match your reliability vs speed needs for **scrape emails from Eventbrite** workflows. - 🎯 **Built around keyword targeting**: Engineered to excel at **Eventbrite email list builder** use cases where you want **Eventbrite email harvesting** based on the keywords you provide. - 💠 **Domain-filtered email harvesting**: Uses your **customDomains** list (like `@gmail.com`) to focus **Eventbrite data scraping emails** on the inboxes that matter. - 💾 **Progress saving for long runs**: Persists cursor and previously seen emails so large tasks are safer to run end-to-end. *** ### Best use cases - 📈 **Marketing lead generation**: Build an **Eventbrite email list builder** by collecting outreach-ready emails tied to relevant event topics and organizers. - 🎓 **Research & competitive intelligence**: Analyze patterns by extracting **Eventbrite event organizer email scraper** contacts for specific niches and keyword clusters. - 🧾 **CRM enrichment at scale**: Feed **Eventbrite attendee email list** data into your CRM pipeline to accelerate segmentation and personalization. - 🎫 **Event partnership sourcing**: Use **Eventbrite participant email scraper** style extraction to find speakers, collaborators, or groups associated with event-related keywords. - ✉️ **Bulk outreach preparation**: Create a dataset for **Eventbrite bulk email scraper** sequences—then deduplicate in your own system using the provided `email` field. - 🧠 **Data analyst workflows**: Join the dataset on `keyword`, `url`, and `title` to study what topics correlate with email availability. *** ### Technical specifications - **Supported Input Formats** - ✅ `keywords`: array of strings - ✅ `customDomains`: array of strings (e.g. `@gmail.com`) - ✅ `location`: string (optional filter) - ✅ `platform`: string (default `Eventbrite`) - **Proxy Support** - ✅ Supported via `proxyConfiguration` - ✅ Engine selection includes `cost-effective` and `legacy` modes - **Retry Mechanism** - ✅ Includes retry and fallback behavior for resilient scraping - **Dataset Structure** - ✅ Each found email produces one row with: `network`, `keyword`, `title`, `description`, `url`, `email` - **Rate Limits & Performance** - ⚠️ Large keyword searches and higher `maxEmails` can take longer (runtime depends on result availability) - **Limitations** - ❌ Email availability depends on publicly accessible Eventbrite bios/posts matching your keywords - ⚠️ Setting a higher `maxEmails` increases potential runtime and doesn’t guarantee reaching that number *** ### FAQ #### What emails does the Eventbrite Email Scraper extract? ✅ It extracts email addresses from Eventbrite bios and posts that are related to your provided keywords, and it filters results based on the email domains you specify in `customDomains`. #### How do I get better results from Eventbrite Email Scraper? ✅ Use specific `keywords` and provide targeted `customDomains` (for example, `@gmail.com`) so the actor focuses on the emails you’re most likely to want for outreach. If you see low results, broaden your keywords and domains and re-run. #### Can I limit how many emails are collected? ✅ Yes. Set `maxEmails` to a value between 1 and 10000. The actor stops once it reaches the limit, which helps control runtime and cost. #### Do I need a proxy configuration to run this actor? ✅ No, not always. The actor supports proxy configuration via `proxyConfiguration`, and you can also choose the `engine` to fit your needs for different reliability/speed preferences. #### What output format do I get? ✅ The actor saves results as structured JSON objects in the dataset. Each record includes `network`, `keyword`, `title`, `description`, `url`, and `email`. #### Is this an API-only tool? ❌ No. You can run it directly in Apify Console with an `input.json` payload and then download/export the dataset afterward. #### How should I use the extracted emails? ✅ Use the dataset for legitimate lead generation, outreach, and research purposes. Always follow applicable privacy laws (including GDPR/CCPA where relevant), spam regulations, and Eventbrite/platform terms of service. #### Where can I request changes or report issues? 💬 Contact us at with your feedback about Eventbrite Email Scraper. *** ### Support & feature requests Want to improve **Eventbrite Email Scraper** or request enhancements for your Eventbrite email scraper workflow? 💡 - 💡 **Feature Requests**: Examples include adding more output fields, supporting additional export formats, or improving filtering options for Eventbrite email extraction. - 📧 **Contact**: Email us at . Your feedback directly shapes the roadmap for future versions of Eventbrite Email Scraper. 🙌 *** ### Eventbrite Email Scraper — Final thoughts *Eventbrite Email Scraper* is designed to be an **SEO-optimized Eventbrite email scraper** that helps you collect keyword-relevant Eventbrite emails fast—so you can build and enrich lead lists at scale without manual searching. # Actor input Schema ## `keywords` (type: `array`): A list of keywords to search for. ## `location` (type: `string`): Location to filter search results. ## `platform` (type: `string`): Select platform. ## `customDomains` (type: `array`): List of custom email domains ## `maxEmails` (type: `integer`): Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time. ## `engine` (type: `string`): Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `proxyConfiguration` (type: `object`): Configure proxies for this Actor. ## Actor input object example ```json { "keywords": [ "song event" ], "location": "", "platform": "Eventbrite", "customDomains": [ "@gmail.com" ], "maxEmails": 20, "engine": "legacy" } ``` # 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 = { "keywords": [ "song event" ], "location": "", "customDomains": [ "@gmail.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/eventbrite-email-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 = { "keywords": ["song event"], "location": "", "customDomains": ["@gmail.com"], } # Run the Actor and wait for it to finish run = client.actor("scraperoka/eventbrite-email-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 '{ "keywords": [ "song event" ], "location": "", "customDomains": [ "@gmail.com" ] }' | apify call scraperoka/eventbrite-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/eventbrite-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Eventbrite Email Scraper", "description": "📩 Eventbrite Email Scraper extracts attendee emails from event listings & tickets for smarter outreach. 🚀 Perfect for B2B lead gen, event marketing, and market research. Save time, boost targeting, and grow your pipeline—without manual scraping.", "version": "0.0", "x-build-id": "dx0X4ICxdEzV0ZzNJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~eventbrite-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-eventbrite-email-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~eventbrite-email-scraper/runs": { "post": { "operationId": "runs-sync-scraperoka-eventbrite-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~eventbrite-email-scraper/run-sync": { "post": { "operationId": "run-sync-scraperoka-eventbrite-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "A list of keywords to search for.", "default": [ "song event" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "platform": { "title": "Platform", "enum": [ "Eventbrite" ], "type": "string", "description": "Select platform.", "default": "Eventbrite" }, "customDomains": { "title": "Custom Email Domains", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com" ], "items": { "type": "string" } }, "maxEmails": { "title": "Max Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of emails to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.", "default": 20 }, "engine": { "title": "Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Configure proxies for this Actor." } } }, "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 } } } } } } } } } } ```