# Wellfound Email Scraper (Fast Advanced And Cheapest) (`scrapedrift/wellfound-email-scraper`) Actor 🚀 Extract verified Wellfound emails fast with the Wellfound Email Scraper—advanced targeting & unbeatable pricing. Perfect for B2B lead gen, sales outreach, and recruiting. ⚡ Save time, boost conversions, and streamline prospecting. 🔥📩 - **URL**: https://apify.com/scrapedrift/wellfound-email-scraper.md - **Developed by:** [ScrapeDrift](https://apify.com/scrapedrift) (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 $3.99 / 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 ### Wellfound Email Scraper - Fast, Advanced and Cheapest ⚡ Copying contact details from Wellfound manually is slow and inconsistent. **Wellfound Email Scraper - Fast, Advanced and Cheapest** extracts email addresses from Wellfound using the keywords and email-domain filters you choose. It’s a go-to Wellfound scraper tool for lead generation email and email extraction from Wellfound profiles. Built for outreach teams, recruiters, and researchers who need usable contact data quickly. In one run, you can collect up to your selected `maxEmails` (with sensible defaults) and see results appear continuously as they’re found. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "network": "Wellfound.com", "keyword": "manager", "title": "Growth Manager — (example listing title)", "description": "Example snippet text that may contain an email address.", "url": "https://wellfound.com/example/profile-or-listing", "email": "alex@company.com" } ```` The actor pushes one dataset row per found email to the “Wellfound Emails Dataset” view called **Scraped Leads**. | Field | Type | What It Tells You | |---|---|---| | `network` | string | Confirms the source network so you can separate datasets when combining sources. | | `keyword` | string | The exact keyword that drove this result—useful for analyzing lead quality by search intent. | | `title` | string | A human-readable title from the scraped result to help you contextualize the email. | | `description` | string | The extracted surrounding text where the email was detected (handy for auditing). | | `url` | string | The link to the scraped result, so you can verify and reference the lead later. | | `email` | string | The primary email address found for outreach or enrichment. | | `status` | string | Not provided in the pushed output fields. If an error happens while pushing data, the actor logs the error; your dataset rows only include successfully pushed items. | | `error_message` | string | Not provided in the pushed output fields. Errors are handled internally with logging (you’ll see activity in the Apify run logs). | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "keywords": ["manager", "founder"], "location": "San Francisco, CA", "customDomains": ["@gmail.com", "@company.com"], "maxEmails": 50 } ``` | Parameter | Required | What It Does | |---|---|---| | `keywords` | ✅ | A list of keywords to search for to find relevant Wellfound results that may contain contact emails. | | `location` | ⬜ | Optional location filter to narrow results to a specific geographic area. | | `customDomains` | ⬜ | Email domains to prioritize (for example, `@gmail.com` or `@company.com`). Emails are extracted only for the domains you include. | | `maxEmails` | ⬜ | Maximum number of emails to collect before stopping the run (helps control scraping time and cost). | *** ### What It Does This actor extracts email addresses from Wellfound based on your `keywords` and `customDomains`, and writes the results into your dataset as they’re found. #### Email extraction from Wellfound results It identifies email addresses tied to the domains you specify and pairs them with context such as the result `title`, `description`, and `url`. This makes it easier to review and qualify leads before outreach. #### Fast bulk searching with keyword x domain coverage Wellfound Email Scraper - Fast, Advanced and Cheapest iterates across your provided `keywords` and `customDomains`, so you can widen or narrow coverage depending on your targeting. If you’re running a Wellfound outreach email list build, this saves hours of manual verification. #### Clean, dataset-ready output for analysis and outreach Each dataset row includes `network`, `keyword`, `title`, `description`, `url`, and `email`. That structure is ideal for importing into CRM workflows or using for downstream enrichment. #### Resilient runs with resume support It maintains progress so you can continue without starting over from scratch. If you stop a run and re-launch, it resumes using the saved cursor and the set of already-seen emails. #### Controlled limits to keep runs efficient With `maxEmails`, you can set a clear stop condition. That helps keep longer runs from running away—especially when you’re experimenting with different keywords for a Wellfound contact email finder strategy. Overall, Wellfound Email Scraper - Fast, Advanced and Cheapest turns publicly available Wellfound contact signals into an actionable dataset. *** ### Why Wellfound Email Scraper - Fast, Advanced and Cheapest? There are plenty of ways to pull contact data from Wellfound—here’s why Wellfound Email Scraper - Fast, Advanced and Cheapest stands out. #### Built for fast lead generation workflows You set your `keywords`, optionally your `location`, and your email domains, and the actor starts producing results immediately. This makes it practical for recruiters, B2B prospecting email scraper workflows, and bulk email scraper for recruiters tasks. #### Flexible targeting with email-domain filters Instead of collecting every possible email variant, you control which domains matter most using `customDomains`. That’s a straightforward way to improve relevance for lead generation email lists (for example, focusing on company domains for higher B2B fit). #### Transparent, dataset-first results Data is pushed incrementally to the Apify dataset as it’s found. This keeps your dataset usable even if the job ends early due to limits or the available result set—ideal for iterative research runs. *** ### Real-World Use Cases Here's how different teams put Wellfound Email Scraper - Fast, Advanced and Cheapest to work: **Recruiters building targeted shortlists**\ A recruiter starts with a list of job-relevant keywords like “manager” and “founder” and selects email domains (e.g., `@company.com`) to prioritize professional inboxes. They run the actor, review the dataset rows with `title`, `url`, and `description`, then immediately import the emails into their outreach pipeline. The result is faster Wellfound outreach email list creation without manual copying. **Sales development for B2B outreach**\ An SDR team wants a resume email extraction tool-style output for Wellfound prospects who match their ICP roles. They run the actor with role-focused `keywords` and domain filters so they only capture the emails they can actually use for company-level follow-ups. Within a single run, they get a structured dataset they can analyze and segment by `keyword`. **Marketing agencies collecting outreach leads**\ A boutique agency prepares multiple campaigns and needs consistent contact data per client niche. They change `keywords` and `customDomains` per campaign, keeping the output schema consistent for easy spreadsheet exports and reporting. This reduces cleanup time and helps them move from research to outreach faster using a Wellfound scraper tool approach. **Data analysts qualifying lead quality by intent**\ A researcher runs several iterations with different `keywords` and compares which searches produce emails more often. Because each row includes `keyword` alongside the extracted `email`, they can quantify performance across keyword themes and refine the next run. This turns an advanced email scraper workflow into measurable data for decision-making. **Automation specialists integrating into pipelines**\ A developer sets up recurring tasks that scrape Wellfound leads and feed the results into internal systems. They trigger runs with the Apify input schema (especially `keywords`, `customDomains`, and `maxEmails`) and treat the dataset as a consistent source of truth for downstream enrichment. The outcome is a repeatable B2B prospecting email scraper process with minimal manual steps. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Go to the actor page on Apify**\ Open the actor in the Apify console: . 2. **Enter your inputs**\ Add your required `keywords`. Optionally set `location`, choose `customDomains`, and set `maxEmails` to control how many emails to collect. 3. **Configure proxy settings (recommended for larger runs)**\ If you want more reliable scraping, enable proxy support in Run Options. (Exact proxy setup is handled by Apify integration.) 4. **Start the run and watch the live log**\ You’ll see progress in the logs as emails are found and pushed to the dataset. 5. **Open the Dataset tab to see results**\ “Scraped Leads” fills incrementally with fields like `keyword`, `title`, `url`, and `email`. 6. **Export in your preferred format**\ Download from the Apify dashboard as JSON, CSV, or Excel. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, Wellfound Email Scraper - Fast, Advanced and Cheapest fits directly into your existing workflow. You can export your dataset from Apify in **JSON, CSV, or Excel** using the dataset tab. For teams that prefer automation, you can connect the actor to your pipeline using Apify’s standard integration options and the Apify API. If you’re using tools like spreadsheets, CRMs, or enrichment steps, you can plug in the dataset rows (including `email`, `keyword`, `url`, and `description`) directly—ideal for an email scraper for job boards or Wellfound outreach email list process. *** ### Pricing Wellfound Email Scraper - Fast, Advanced and Cheapest runs on Apify, which includes a **free tier** — no credit card needed to start. Free tier usage uses platform credits and is often enough for several real test runs. For bigger workloads, you can run pay-as-you-go based on Apify compute usage (billed per Actor compute unit / CU). Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Incremental dataset writing | Results are pushed to the dataset as they’re found. | | Resuming interrupted runs | Progress is saved and the actor resumes using a stored cursor and seen emails. | | Domain-focused extraction | Emails are collected based on your `customDomains` filters. | | Result caps | `maxEmails` stops the run once the limit is reached. | | Push failures | If a dataset push fails, the actor logs the error. | **Limitations:** This actor extracts emails from publicly available sources and relies on what’s visible in those pages at runtime. If there are fewer relevant results for your chosen `keywords` and `customDomains`, you may collect fewer than `maxEmails`. For enterprise-scale needs or custom configurations, reach out and we’ll help. *** ### Frequently Asked Questions #### Is there a free plan? Apify provides a free tier for actors on the platform. You can start with a test run using your `keywords` and a lower `maxEmails` to validate results before scaling. #### Do I need to log in or create an account on Wellfound? No—this actor is designed to extract publicly available data and emails from Wellfound results based on your inputs. #### How accurate is the extracted data? Accuracy depends on what’s present in publicly available Wellfound-related pages and the email domains you include in `customDomains`. The actor extracts emails that match your specified domain patterns and pairs them with the associated `url` and `description` for context. #### How many results can I get per run? You control this with `maxEmails`. The scraper stops once the number of unique collected emails reaches your limit. #### How fresh is the data? The data freshness depends on when you run the actor. Each run collects emails from currently accessible publicly visible sources and outputs them into your dataset. #### Is this legal? Does it comply with GDPR / CCPA? Use is governed by the law where you operate and the platform’s Terms of Service. The actor processes **publicly available data**, but it’s still your responsibility to ensure compliance with GDPR, CCPA, and any applicable regulations. #### Can I export to Google Sheets or Excel? Yes. You can export your dataset from Apify as JSON, CSV, or Excel, and then import it into Google Sheets or your preferred spreadsheet workflow. #### Can I schedule this to run automatically? Yes, you can schedule runs using Apify’s scheduling capabilities. This is useful when you want periodic updates for a Wellfound lead generation email process. #### Can I access results via the API? Yes. Apify supports programmatic access to actor runs and their datasets via the Apify API, so you can pull results into your systems automatically. #### What happens when the actor encounters an error? If an error occurs while pushing results, the actor logs the failure and continues processing. The run also saves progress so you can resume from the last saved cursor when you re-run. *** ### Get Help & Use Responsibly Got a question about Wellfound Email Scraper - Fast, Advanced and Cheapest or a feature you'd like added? Reach out at and we’ll help. If you have ideas like adding more email-domain presets or improving keyword targeting workflows, tell us—we actively maintain the actor based on user feedback. **Disclaimer:** This actor collects **publicly available data**. It does not access private accounts, login-gated pages, or password-protected content. You are responsible for complying with GDPR, CCPA, and the relevant platform Terms of Service. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `keywords` (type: `array`): A list of keywords or queries to search for. ## `location` (type: `string`): Location to filter search results. ## `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. ## Actor input object example ```json { "keywords": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ], "maxEmails": 20 } ``` # 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": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapedrift/wellfound-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": [ "manager", "founder", ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com", ], } # Run the Actor and wait for it to finish run = client.actor("scrapedrift/wellfound-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": [ "manager", "founder" ], "location": "", "customDomains": [ "@gmail.com", "@yahoo.com" ] }' | apify call scrapedrift/wellfound-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapedrift/wellfound-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wellfound Email Scraper (Fast Advanced And Cheapest)", "description": "🚀 Extract verified Wellfound emails fast with the Wellfound Email Scraper—advanced targeting & unbeatable pricing. Perfect for B2B lead gen, sales outreach, and recruiting. ⚡ Save time, boost conversions, and streamline prospecting. 🔥📩", "version": "1.0", "x-build-id": "WcyjqZkIwP7qI6gTl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapedrift~wellfound-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapedrift-wellfound-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapedrift~wellfound-email-scraper/runs": { "post": { "operationId": "runs-sync-scrapedrift-wellfound-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapedrift~wellfound-email-scraper/run-sync": { "post": { "operationId": "run-sync-scrapedrift-wellfound-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 or Queries", "type": "array", "description": "A list of keywords or queries to search for.", "default": [ "manager", "founder" ], "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "Location to filter search results.", "default": "" }, "customDomains": { "title": "Enter Custom Email Domains (e.g. @gmail.com, @yahoo.com)", "type": "array", "description": "List of custom email domains", "default": [ "@gmail.com", "@yahoo.com" ], "items": { "type": "string" } }, "maxEmails": { "title": "Enter 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 } } }, "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 } } } } } } } } } } ```