# Architects Email Scraper (`solid-scraper/architects-email-scraper`) Actor 🏗️ Find architect business emails fast! Our SEO-focused email scraper targets verified architects by firm, location, and niche—ideal for lead generation, agencies, and sales teams. ⚡ Export instantly. 📩 Start building your pipeline today! - **URL**: https://apify.com/solid-scraper/architects-email-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ### Architects Email Scraper 📬 **Architects Email Scraper** is an Apify actor that helps you find architecture firm contact information and extract emails alongside phone numbers and social media profiles. It’s designed to solve the time-consuming part of building an **architects email database**—so you can quickly create **architects contact lists** for outreach, lead generation, and research. Whether you’re a marketer, recruiter, or data analyst, this **architect email scraper** streamlines collecting **AEC email lead scraper** data from publicly available web sources and pairing it with structured business details—saving you hours of manual work. --- ### 🚀 Why choose Architects Email Scraper? | Feature | Benefit | | --- | --- | | ✅ **Purpose-built for architecture firms** | Find and extract contact info for the “Architects” niche using your location filters | | ✅ **Structured output for easy import** | Store results with fields like `name`, `website`, `scraped_emails`, and more in a consistent dataset format | | ✅ **Reliability with proxy support** | Works with your **proxy configuration** to improve stability for larger runs | | ✅ **Data completeness (email + phone + social)** | Extract emails, phone numbers, and social links (when available) rather than emails-only snapshots | | ✅ **Scale by limits** | Control how many businesses to scrape using `maxBusinesses` and choose whether limits apply per location | | ✅ **Resilient scraping workflow** | Includes success/failure tracking and records a `scrape_status` for each business | --- ### 🔎 Key features - ✅ **Architect-focused search**: Uses your `googleMapsSearchTerm` (default **Architects**) to target relevant businesses in each location - 🌍 **Location-aware scraping**: Accepts multiple entries in `googleMapsLocation` to build broader architect email lead scraper lists - 🧾 **Contact extraction from websites**: Scrapes business websites to extract `scraped_emails`, `scraped_phones`, and `scraped_social_media` - 🛡️ **Proxy support for reliability**: Includes a `proxyConfiguration` option (recommended for larger-scale jobs) - 💾 **Dataset-first results**: Pushes each business (and, when available, each extracted email) directly to the Apify dataset - 📞 **Phone + social included**: Extracts additional contact context alongside emails for richer follow-up - 🔁 **Clear success tracking**: Outputs `emails_found`, `pages_scraped`, and a `scrape_status` value for transparency --- ### 📝 Input Provide input via an `input.json` file. Example structure: ```json { "googleMapsSearchTerm": "Architects", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ```` #### Input Fields | Field | Required | Description | | --- | --- | --- | | `googleMapsSearchTerm` | No | Business type or niche to search for (the default prefill is **Architects**). | | `googleMapsLocation` | Yes | Target geographic locations to search. Provide an array of locations like `["Miami, Florida"]` (you can include multiple). | | `maxBusinesses` | No | Target number of businesses to find (allowed range **1–1000**). The run stops when the target is reached. | | `scrapeMaxBusinessesPerLocation` | No | If `true`, the actor collects up to `maxBusinesses` results **per location**. If `false`, it combines locations into one total limit. | | `proxyConfiguration` | No | Proxy settings for scraping. Recommended for large-scale scraping. Uses the built-in proxy editor with your settings (including `proxy support`). | | `proxyConfiguration • proxy support` | No | Enables Apify Proxy by default (prefilled to `true`). | > Note: Only `googleMapsLocation` and `googleMapsSearchTerm` are required. *** ### 📦 Output The actor saves each result row into the **Business Contact Data** dataset as JSON objects. ```json [ { "name": "Example Architecture Firm", "website": "https://example.com", "phone": "+1-555-123-4567", "full_address": "123 Main St New York NY 10001 US", "city": "New York", "state": "NY", "zip": "10001", "country_code": "US", "scraped_emails": ["info@example.com"], "scraped_phones": ["+1-555-987-6543"], "scraped_social_media": ["https://www.linkedin.com/company/example/"], "emails_found": 1, "pages_scraped": 5, "avg_rating": 4.5, "total_reviews": 123, "lat": 40.7128, "long": -74.006, "place_id": "ChIJ...", "scrape_status": "success" } ] ``` #### Output Fields | Field | Type | Description | | --- | --- | --- | | `name` | string | Business name for the architect/firm. | | `website` | string | The business website URL extracted for scraping. | | `phone` | string | Phone value coming from the business listing data. | | `full_address` | string | Combined address string (built from street/city/state/zip/country\_code). | | `city` | string | City portion of the business address. | | `state` | string | State portion of the business address. | | `zip` | string | ZIP/postal code portion of the business address. | | `country_code` | string | Country code portion of the business address. | | `scraped_emails` | array | Emails extracted from the business website (empty if none found). | | `scraped_phones` | array | Phone numbers extracted from the business website (may be empty). | | `scraped_social_media` | array | Social media profile links extracted from the business website (may be empty). | | `emails_found` | number | Count of scraped emails found for that business. | | `pages_scraped` | number | Number of processed URLs/pages during website scraping. | | `avg_rating` | number | Average rating for the business listing. | | `total_reviews` | number | Total reviews count for the business listing. | | `lat` | number | Latitude for the business location. | | `long` | number | Longitude for the business location. | | `place_id` | string | Place identifier from the business listing data. | | `scrape_status` | string | Status indicator such as `success`, `failed`, or `no_website`. | > Dataset behavior note: when emails are found, the actor pushes flattened rows—one dataset row per extracted email—with the email value stored in `email_found`. *** ### 🧭 How to use Architects Email Scraper (via Apify Console) 1. **Open Apify Console**\ Log in at [console.apify.com](https://console.apify.com) and open the **Actors** page. 2. **Find the actor**\ Search for **Architects Email Scraper** and open the actor details. 3. **Configure your input**\ In the **INPUT** section, set: - **Location** (`googleMapsLocation`) — one or more locations as an array - **Search Term** (`googleMapsSearchTerm`) — default is **Architects** Then optionally set: - **Maximum Businesses With Emails** (`maxBusinesses`) - **Scrape Max Businesses Per Location** (`scrapeMaxBusinessesPerLocation`) - **Proxy Configuration** (`proxyConfiguration`) 4. **Choose proxy settings (recommended for scale)**\ If you plan to scrape many businesses or multiple locations, enable proxy configuration using the provided proxy editor options. 5. **Run the actor**\ Click **Run** to start. You’ll see progress in logs as it processes locations and scrapes websites. 6. **Review the output dataset**\ After completion, open the **OUTPUT** tab and view the dataset named **Business Contact Data** (table view includes fields like Business Name, Emails Found, Phone Numbers, and Status). 7. **Export your results**\ Export the dataset to JSON/CSV from Apify (use it directly in CRM workflows, outreach lists, or analysis pipelines). No coding required—get accurate **architects email scraper** results in minutes ✅ *** ### ⚙️ Advanced features & SEO optimization - 📊 **Engineered for architects email lead scraper workflows**: Tailored for the “Architects” niche so you can build **architect email database** style outputs faster. - 🔄 **Input scaling with clear limits**: Use `maxBusinesses` to stop at the business volume you want, with `scrapeMaxBusinessesPerLocation` controlling whether limits are per location or global. - 💼 **Richer AEC context**: Works as an **AEC email lead scraper** by extracting not only emails, but also `scraped_phones` and `scraped_social_media`. - 🛡️ **Built-in proxy support for reliable scraping**: Use `proxyConfiguration` (including `proxy support`) to improve stability for bulk runs. *** ### 🎯 Best use cases - 📈 **Marketing team lead generation**: Build targeted architects lead generation emails by turning architecture firm websites into structured outreach-ready data. - 🧑‍🔬 **Market researchers**: Compile an architect email database by location and niche for competitive research and trend analysis. - 🏗️ **B2B sales pipelines**: Enrich CRM records with business contacts plus phone and social links for better follow-up. - ✉️ **Email ops and list hygiene teams**: Use email counts (`emails_found`) and scrape status (`scrape_status`) to understand coverage before outreach. - 📍 **Regional business development**: Compare architects contact list coverage across multiple `googleMapsLocation` entries. - 🧾 **Data analysts**: Join extracted fields like `avg_rating`, `total_reviews`, `lat`, and `long` to analyze firm distribution alongside contactability. - 💻 **Automation engineers**: Feed dataset rows into downstream workflows (e.g., lead scoring, enrichment, routing to sales reps) using consistent output fields. *** ### 🔧 Technical specifications **Supported Input Formats** - ✅ `googleMapsLocation` as an array of location strings - ✅ `googleMapsSearchTerm` as a string (defaults to **Architects**) - ✅ `maxBusinesses` as an integer (1–1000) - ✅ `scrapeMaxBusinessesPerLocation` as a boolean - ✅ `proxyConfiguration` as a proxy object (supports `proxy support`) **Proxy Support** - ✅ Proxy support via `proxyConfiguration` with `proxy support` (prefilled to `true`) **Retry Mechanism** - ✅ Includes resilience in the overall workflow so runs can continue collecting results even when some businesses fail (tracked in `scrape_status`) **Dataset Structure** - ✅ Dataset: **Business Contact Data** - ✅ Flattened rows: when `scraped_emails` are found, the actor pushes one row per extracted email using `email_found` - ✅ Key fields include `scraped_emails`, `scraped_phones`, `scraped_social_media`, `emails_found`, `pages_scraped`, and `scrape_status` **Rate Limits & Performance** - ✅ Designed for bulk-style scraping by using controlled limits (`maxBusinesses`) and structured concurrency for website scraping **Limitations** - ❌ If a business has no `website`, it will be marked with `scrape_status` of `no_website` and `scraped_emails` will be empty. - ❌ Email availability depends on what’s publicly present on each target business website. *** ### ❓ FAQ #### Is Architects Email Scraper a bulk email finder for architects? ✅ Yes. **Architects Email Scraper** is specifically set up as a bulk email finder for architects by searching your provided locations and then extracting emails (plus phone and social links) from business websites. #### What inputs do I need to run it? You must provide `googleMapsLocation` and `googleMapsSearchTerm`. You can also set `maxBusinesses`, choose whether limits apply per location with `scrapeMaxBusinessesPerLocation`, and optionally configure `proxyConfiguration`. #### Does it extract phones and social media, or only emails? ✅ It extracts emails, phone numbers, and social media profiles. Emails go to `scraped_emails`, phones to `scraped_phones`, and social links to `scraped_social_media`. #### Will it save results even if some businesses fail? ✅ Yes. Each business row includes `scrape_status` so you can distinguish `success`, `failed`, and `no_website`. Failed or unavailable website cases will produce empty email/phone/social arrays. #### Can I control how many businesses are collected? ✅ Yes. Use `maxBusinesses` to set the maximum business count. If you enable `scrapeMaxBusinessesPerLocation`, the actor targets up to `maxBusinesses` results per location; otherwise it uses a single combined limit. #### How does the output work when multiple emails are found? When emails are found, the actor pushes flattened rows so you’ll see one dataset row per extracted email using `email_found`, while the rest of the business fields remain associated. #### Do I need to use a proxy? Not strictly. But ✅ proxy configuration is recommended for larger-scale scraping. You can set `proxyConfiguration` and it includes `proxy support`. *** ### 🤝 Support & feature requests Have questions or want improvements for **Architects Email Scraper**? We’d love to hear from you. - 💡 **Feature Requests**: Example ideas include adding additional export formats, improving dataset row structure, or expanding extraction coverage for more contact fields. - 📧 **Contact**: Reach out via . Your feedback helps shape the roadmap for future versions of this **architects email scraper**. *** *If you want an SEO-optimized architects email scraper that’s built for real-world outreach workflows, **Architects Email Scraper** makes it easy to collect and structure contact data at scale.* *** ### Disclaimer **This tool only accesses publicly accessible sources**. It does not access private profiles, authenticated data, or password-protected pages. You are responsible for ensuring your use complies with applicable laws and platform terms (including GDPR/CCPA where relevant) and for respecting each source’s policies and rate limits. For data removal requests, contact . Use **Architects Email Scraper** responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `googleMapsSearchTerm` (type: `string`): Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists'). ## `googleMapsLocation` (type: `array`): Target geographic location for the email scraper (e.g., 'Miami, Florida'). ## `maxBusinesses` (type: `integer`): Target number of businesses to find (1-1000). The scraper will stop when this target is reached. ## `scrapeMaxBusinessesPerLocation` (type: `boolean`): If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit. ## `proxyConfiguration` (type: `object`): Proxy settings for scraping. Recommended for large-scale scraping. ## Actor input object example ```json { "googleMapsSearchTerm": "Architects", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "googleMapsSearchTerm": "Architects", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/architects-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 = { "googleMapsSearchTerm": "Architects", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/architects-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 '{ "googleMapsSearchTerm": "Architects", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call solid-scraper/architects-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/architects-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Architects Email Scraper", "description": "🏗️ Find architect business emails fast! Our SEO-focused email scraper targets verified architects by firm, location, and niche—ideal for lead generation, agencies, and sales teams. ⚡ Export instantly. 📩 Start building your pipeline today!", "version": "1.0", "x-build-id": "vxRyPntpKMuXUFsye" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~architects-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-architects-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~architects-email-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-architects-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~architects-email-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-architects-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "googleMapsLocation", "googleMapsSearchTerm" ], "properties": { "googleMapsSearchTerm": { "title": "Search Term", "type": "string", "description": "Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists').", "default": "Architects" }, "googleMapsLocation": { "title": "Location", "type": "array", "description": "Target geographic location for the email scraper (e.g., 'Miami, Florida').", "default": [ "New York" ], "items": { "type": "string" } }, "maxBusinesses": { "title": "Maximum Businesses With Emails", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Target number of businesses to find (1-1000). The scraper will stop when this target is reached.", "default": 5 }, "scrapeMaxBusinessesPerLocation": { "title": "Scrape Max Businesses Per Location", "type": "boolean", "description": "If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit.", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for scraping. Recommended for large-scale scraping." } } }, "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 } } } } } } } } } } ```