# Event Profiles · Export Attendees & Speakers (`corent1robert/brella-event-profiles`) Actor Export the full attendee or speaker list from any Brella event. Get names, companies, titles, emails, and interests in one clean dataset — ready for your CRM or outreach tool. Turn any Brella event into a lead list. One run, one spreadsheet, every participant. - **URL**: https://apify.com/corent1robert/brella-event-profiles.md - **Developed by:** [Corentin Robert](https://apify.com/corent1robert) (community) - **Categories:** Lead generation, Automation, Integrations - **Stats:** 2 total users, 1 monthly users, 66.7% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 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 ## Brella — attendee & speaker lists for your event **[Brella](https://www.brella.io/)** is an **event platform** used for programmes, **networking**, and **meetings** (in-person, hybrid, or virtual). Attendees use the Brella app to show **who they are**, **what they’re looking for**, and to **book meetings**. This Actor is for **organizers, marketing, and sales** who need that same data **in one spreadsheet** — one **row per person** — instead of opening hundreds of profiles by hand. **What you get:** a **single table** you can open in **Excel or Google Sheets**, filter, and send to your **CRM** or outreach tools. Export **everyone in the networking list** or **speakers from the agenda**, for the **Brella event presets** listed below. Download from the **Dataset** tab when the run finishes. **Emails** only appear if that person chose to show their email in Brella — otherwise the cell may be empty. Use the data in line with Brella’s rules and privacy law. **Your event isn’t in the list below?** Send your **event details** (name, dates, and what we need to wire the Brella org/event) — we can **add a new preset** to this Actor so it appears in the dropdown and you can **export the same way** as ChangeNOW or START Summit. [corentin@outreacher.fr](mailto:corentin@outreacher.fr) --- ### Supported events Pick these in the Actor input (or use the dropdown in the Apify console). | Event | Value to choose | Notes | |-------|-----------------|--------| | **ChangeNOW** | `changenow` | Current preset for the ChangeNOW edition configured in this Actor | | **START Summit** | `startsummit` | Current preset for the START Summit edition configured in this Actor | If the conference year changes, presets may be updated in a new Actor version. **Running a different Brella event?** Share the event info — we’ll **create the preset and add it to this list** so you don’t have to fork anything; you’ll pick it in the input and run as usual. --- ### Why use it | You want… | You get… | |-----------|----------| | **A real lead list after the show** | Names, companies, titles, interests, and links in columns — ready to work with | | **Speakers only** | A focused list of people on stage (with bio text when Brella shows it) | | **Less manual work** | No exporting contacts one by one from the app | | **Visibility while it runs** | Progress and time remaining in the run view so you know it’s working | --- ### What you get (dataset fields) Each item is one object (one row after export). Key fields: | Field | Description | |-------|-------------| | `role` | `attendee` or `speaker` | | `attendeeId` | Brella attendee / speaker record id | | `userId` | Brella user id (attendees; speakers may be empty) | | `firstName`, `lastName`, `fullName` | Name fields | | `email` | If visible on profile; often `null` | | `companyName`, `companyTitle` | Company and title | | `companyCountries` | Array of region/country strings | | `imageUrl` | Photo URL when available | | `linkedin`, `twitter`, `website` | Social / web | | `persona` | e.g. Investor, Startup — Brella taxonomy | | `jobFunction`, `industry` | Function and industry labels | | `pitch` | Short intro text (attendees) or bio-derived text (speakers) | | `bio` | Speaker bio (speakers mode; when present) | | `joinedAt` | Registration / join timestamp (attendees) | | `interests` | Array of strings (stages, topics, “network about” lines) | | `profileUrl` | Link to the person on Brella (attendees) | The Apify **Dataset** also offers a simple **table view** so you can preview before downloading. **Attendees vs speakers:** “Attendees” is the full crowd who registered. “Speakers” is the people on the agenda. The exact columns can differ slightly (e.g. more speaker bio on stage mode). --- ### How to run #### Step 1 — Mode - **Attendees** — Export **everyone who participated** (the full participant list). - **Speakers** — Export **only speakers** (people on the agenda). #### Step 2 — Event Choose **ChangeNOW** or **START Summit** — same list as [Supported events](#supported-events). #### Step 3 — Filters & profile depth (JSON or API only) The **Apify Console form** only shows **Mode** and **Event**. Filters and “complete profiles” are **not** on the visual form — set them in the **JSON input** (switch to JSON in the run dialog) or via the **API**. Use the **`exportOptions`** array (multiselect values listed below). **Empty array `[]`** = quickest export (list data only). | Value | Meaning | |--------|---------| | `require_email`, `require_website`, `require_linkedin`, `require_company`, `require_photo`, `require_pitch` | **Row filters** (AND — all selected must match). | | `complete_profiles` | Slower run: extra step per person for best email & photo when Brella shows them. | - **Attendees:** filters use **list**-phase data. For maximum email coverage, run without `require_email` once or filter in Excel afterward. - **Speakers:** use **company** / **photo** / **pitch** requirements only — email / website / LinkedIn filters alone are rejected (empty columns for speakers). #### Examples **Prefilled test run (Console JSON tab & repo `input.json`)** — ChangeNOW, **5 rows**, **enriched** (complete profiles): ```json { "mode": "attendees", "event": "changenow", "maxResults": 5, "exportOptions": ["complete_profiles"] } ```` For a **full** export with **list-only** (no per-person detail step), set **`"exportOptions": []`** or **`"attendeeData": "list"`**. Omit **`maxResults`** to load everyone (default is no cap). **ChangeNOW — full list, list-only (fastest)** ```json { "mode": "attendees", "event": "changenow", "exportOptions": [] } ``` **Only people with an email and a company (quick export)** ```json { "mode": "attendees", "event": "changenow", "exportOptions": ["require_email", "require_company"] } ``` **Legacy JSON** still works: `attendeeData` (`"full"` / `"list"`) overrides `exportOptions`; old boolean fields (`onlyWithEmail`, etc.) still work if present. ```json { "mode": "attendees", "event": "changenow", "attendeeData": "list" } ``` **START Summit — speakers** ```json { "mode": "speakers", "event": "startsummit" } ``` **Fine-tuning (optional JSON):** power users can adjust `maxResults`, `detailConcurrency`, and `detailBatchDelayMs` — see **Developers** below. List requests always use the API maximum page size (100 rows per page) until all participants are loaded. #### Apify “Run options” in the console The Apify interface always shows **timeout**, **build**, and sometimes **maximum cost per run** — that’s **platform UI**, not something this Actor can remove. This Actor sets a **default timeout of 3600s**; you can lower the cap or cost limit in the run dialog if your plan allows it. *** ### Speed tips - Big event + **Complete profiles** on = longest runs — use **filters** so fewer people enter that step, or leave **Complete profiles** off. - If a run struggles or Brella rate-limits you, turn **Complete profiles** off first, or ask a developer to tune advanced settings (see Developers). *** ### Output & export - **On Apify:** Open the finished run → **Dataset** → **Download** — pick the format you prefer (**Excel-friendly CSV** and **Excel** are the most common for marketing teams). - **Local runs:** the Actor can also write **`output.csv`** in the project folder for developers. *** ### Who it’s for - **Marketing & growth** — post-event lead lists, partner reporting, campaign follow-up - **Event teams** — participant or speaker exports after the conference - **Sales / BD** — outreach prep from persona and interest data - **Analysts** — persona and industry mix - **Data / ops** — clean tables for your tools and workflows *** ### Developers - **Stack:** TypeScript, Apify SDK, Node 20 (see `Dockerfile`). - **Entry:** `src/main.ts` — event presets in `EVENT_PRESETS`, Brella service URL in code. - **Local:** `npm install && npm run build` — copy `input.json` to the default key-value store or use `npm run run:local` if defined in `package.json`. - **Tests:** No network mocks in repo; validate with a small `maxResults` against a real session. **Performance (technical):** List endpoints use a fixed **100 rows per page** (Brella max) until all pages are fetched. Full attendee mode issues one detail request per person for richer rows; list-only mode skips that. Default parallel detail concurrency is 120 (cap 300). List paging uses batched parallel fetches. On HTTP 429 from Brella, lower `detailConcurrency` or set `detailBatchDelayMs` (e.g. 25–100 ms). **Changelog:** see `CHANGELOG.md`. *** ### Legal Use only when you have **legitimate access** to the event data in Brella. Respect the platform’s terms and GDPR / local privacy rules; do not use the Actor to bypass access controls. *** ### Support **Custom events:** Not listed in [Supported events](#supported-events)? Email **what we need for your Brella event** — we add it to the Actor’s preset list so extraction stays one click. # Actor input Schema ## `mode` (type: `string`): Networking participants (everyone in Brella) or speakers from the agenda. ## `event` (type: `string`): Which Brella-powered conference preset this run uses. ## `exportOptions` (type: `array`): Optional. Not shown in the form — edit in JSON. Default is full profile enrichment; use \[] or attendeeData list for list-only. ## `detailConcurrency` (type: `integer`): Optional tuning for full-profile runs. Leave unset unless you need to change speed or retries. ## `detailBatchDelayMs` (type: `integer`): Optional pause between batches in full-profile mode. Leave unset in most cases. ## `maxResults` (type: `integer`): Cap rows loaded from the list (before filters). Omit for everyone. ## `accessToken` (type: `string`): Maintainer override only ## `client` (type: `string`): Maintainer override only ## `uid` (type: `string`): Maintainer override only ## Actor input object example ```json { "mode": "attendees", "event": "changenow", "exportOptions": [ "complete_profiles" ] } ``` # Actor output Schema ## `results` (type: `string`): All exported people (attendees and/or speakers, depending on mode): profile fields for CRM or spreadsheets # 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 = { "mode": "attendees", "event": "changenow", "exportOptions": [ "complete_profiles" ] }; // Run the Actor and wait for it to finish const run = await client.actor("corent1robert/brella-event-profiles").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 = { "mode": "attendees", "event": "changenow", "exportOptions": ["complete_profiles"], } # Run the Actor and wait for it to finish run = client.actor("corent1robert/brella-event-profiles").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 '{ "mode": "attendees", "event": "changenow", "exportOptions": [ "complete_profiles" ] }' | apify call corent1robert/brella-event-profiles --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=corent1robert/brella-event-profiles", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Event Profiles · Export Attendees & Speakers", "description": "Export the full attendee or speaker list from any Brella event. \nGet names, companies, titles, emails, and interests in one clean dataset — \nready for your CRM or outreach tool. Turn any Brella event into a lead list. \nOne run, one spreadsheet, every participant.", "version": "2.0", "x-build-id": "Ub85bnU3DGgSGiuuf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/corent1robert~brella-event-profiles/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-corent1robert-brella-event-profiles", "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/corent1robert~brella-event-profiles/runs": { "post": { "operationId": "runs-sync-corent1robert-brella-event-profiles", "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/corent1robert~brella-event-profiles/run-sync": { "post": { "operationId": "run-sync-corent1robert-brella-event-profiles", "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": { "mode": { "title": "Who to export", "enum": [ "attendees", "speakers" ], "type": "string", "description": "Networking participants (everyone in Brella) or speakers from the agenda." }, "event": { "title": "Brella event", "enum": [ "changenow", "startsummit" ], "type": "string", "description": "Which Brella-powered conference preset this run uses." }, "exportOptions": { "title": "Export options", "minItems": 0, "uniqueItems": true, "type": "array", "description": "Optional. Not shown in the form — edit in JSON. Default is full profile enrichment; use [] or attendeeData list for list-only.", "items": { "type": "string" }, "default": [ "complete_profiles" ] }, "detailConcurrency": { "title": "Detail concurrency", "type": "integer", "description": "Optional tuning for full-profile runs. Leave unset unless you need to change speed or retries." }, "detailBatchDelayMs": { "title": "Detail batch delay (ms)", "type": "integer", "description": "Optional pause between batches in full-profile mode. Leave unset in most cases." }, "maxResults": { "title": "Max results (optional)", "type": "integer", "description": "Cap rows loaded from the list (before filters). Omit for everyone." }, "accessToken": { "title": "Access Token", "type": "string", "description": "Maintainer override only" }, "client": { "title": "Client", "type": "string", "description": "Maintainer override only" }, "uid": { "title": "UID", "type": "string", "description": "Maintainer override only" } } }, "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 } } } } } } } } } } ```