# Car Dealer Email Scraper (`solid-scraper/car-dealer-email-scraper`) Actor ๐Ÿ“ง Car Dealer Email Scraper finds verified car dealership contacts fastโ€”by location, keywords, and niche. Perfect for lead gen, sales teams, and agencies to boost outreach and conversions instantly. - **URL**: https://apify.com/solid-scraper/car-dealer-email-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (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 $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 ### Car Dealer Email Scraper ๐Ÿ“ฌ **Car Dealer Email Scraper** automatically searches for car dealerships and extracts contact information from publicly available sourcesโ€”so you can build a dealer email list faster without manual copy-paste. Whether youโ€™re a marketer, sales lead, or data analyst, this **car dealer email scraper** (and **automotive dealer email scraper**) helps you find **dealer website email extractor** results by city, and then turn them into outreach-ready data at scaleโ€”saving you hours of manual work. --- ### Why choose Car Dealer Email Scraper? | Feature | Benefit | |---|---| | โœ… **Email + contact extraction from business websites** | Extracts emails and other contact fields in one run per dealership | | โœ… **Targeted by location** | Lets you focus results on the geographic areas you care about | | โœ… **Structured dataset output** | Saves consistent fields (address, phone, email, rating/reviews, and more) for easier analysis | | โœ… **Built-in resilience for scraping** | Includes fallbacks and resilience during website scraping for better completion rates | | โœ… **Scale-focused stopping logic** | Stops when it reaches your target number of businesses with emails | | โœ… **Proxy support for reliable scraping** | Helps keep scraping stable for larger batches | --- ### Key features - ๐Ÿ” **Automotive dealer email discovery:** Searches using your business type query and location inputs, then scrapes website contact info - ๐ŸŒ **Dealer website email extraction:** Prioritizes extracting emails from dealership websites and records what was found - ๐Ÿ’Œ **Email-first output:** Outputs **one dataset row per email** when emails are found (ideal for outreach workflows) - ๐Ÿ“ž **Phone and social media capture:** Collects `scraped_phones` and `scraped_social_media` for each dealership record - ๐Ÿ“Š **Rich dealership context fields:** Includes fields like `avg_rating`, `total_reviews`, and `full_address` alongside contact data - ๐Ÿ’พ **Real-time dataset saving:** Each scraped result is pushed to the Apify dataset as soon as itโ€™s ready - ๐Ÿ›ก๏ธ **Reliability controls:** Includes runtime controls for completion and resilience (including stopping when quotas are reached) - ๐Ÿš€ **Email-only mode support:** Can run in a mode intended to only save businesses with emails (when enabled) --- ### Input Provide input via an `input.json` file. Example structure: ```json { "googleMapsSearchTerm": "Car Dealer", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ```` #### Input Fields | Field | Required | Description | |---|---:|---| | `googleMapsSearchTerm` | โœ… | The business type or niche to search for (for example: `car dealer` or `auto dealership`). | | `googleMapsLocation` | โœ… | A list of geographic locations to target (example format: `New York`). | | `maxBusinesses` | โŒ | Target number of businesses with emails to find (allowed range: `1-1000`). The actor stops when this target is reached. | | `scrapeMaxBusinessesPerLocation` | โŒ | If enabled, collects up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single overall total limit. | | `proxyConfiguration` | โŒ | Proxy settings for scraping. Recommended for larger-scale runs. | | `proxyConfiguration.proxy support` | โŒ | When set to `true`, enables Apify Proxy. (Recommended for large batches.) | *** ### Output The actor saves each scraped dealershipโ€™s data into the Apify dataset, using a **flattened output** format (one row per email when emails are found). Example dataset record: ```json { "street_address": "123 Main St", "city": "New York", "zip": "10001", "state": "NY", "country_code": "US", "full_address": "123 Main St New York NY 10001 US", "website": "https://example.com", "avg_rating": 4.6, "total_reviews": 132, "name": "Example Auto Dealership", "place_id": "ChIJxxxxxxxxxxxx", "phone": "+1 212-555-0123", "lat": 40.7128, "long": -74.006, "scraped_phones": ["+1 212-555-0123"], "scraped_social_media": ["https://www.linkedin.com/company/example/"], "emails_found": 3, "pages_scraped": 7, "scrape_status": "success", "email_found": "sales@example.com" } ``` #### Output Fields | Field | Type | Description | |---|---|---| | `name` | string | Business (dealership) name. | | `website` | string | Dealership website URL (cleaned). | | `phone` | string | Primary phone value captured for the dealership. | | `full_address` | string | Combined formatted address (`street_address city state zip country_code`). | | `city` | string | City extracted for the dealership. | | `state` | string | State extracted for the dealership. | | `zip` | string | ZIP/postal code extracted for the dealership. | | `country_code` | string | Country code extracted for the dealership. | | `email_found` | string | The specific email address for this row (one row per email when emails are found). | | `scraped_phones` | array | Array of phone numbers scraped from the dealership website. | | `scraped_social_media` | array | Array of social media links scraped from the dealership website. | | `emails_found` | number | Count of scraped emails found for the dealership. | | `pages_scraped` | number | Number of processed URLs/pages during website scraping (from the job progress). | | `avg_rating` | number | Average rating value captured for the dealership. | | `total_reviews` | number | Total review count captured for the dealership. | | `lat` | number | Latitude coordinate associated with the dealership. | | `long` | number | Longitude coordinate associated with the dealership. | | `place_id` | string | Place identifier for the dealership. | | `scrape_status` | string | Scraping status (for example: `success`, `failed`, `no_website`, `error`). | **Export tip:** After the run finishes, you can export the dataset from Apify as JSON or CSV for downstream workflows (CRMs, outreach lists, and analysis). *** ### How to use Car Dealer Email Scraper (via Apify Console) 1. **Open Apify Console** Log in at [console.apify.com](https://console.apify.com) and open the actor page for **Car Dealer Email Scraper**. 2. **Add your search term** In **INPUT**, set `googleMapsSearchTerm` to your niche, such as `car dealer` or `auto dealership`. 3. **Add one or more target locations** Enter your cities/regions in `googleMapsLocation` (it supports an array, e.g. `["New York"]`). 4. **Set your target volume** Use `maxBusinesses` to control how many businesses with emails you want to collect (range `1-1000`). 5. **Choose per-location limits (optional)** Toggle `scrapeMaxBusinessesPerLocation`: if enabled, each location can produce up to `maxBusinesses`; if disabled, all locations share one overall total limit. 6. **(Recommended) Configure proxy settings** In `proxyConfiguration`, use `proxy support` for more reliable scraping on larger batches. 7. **Run the actor and monitor logs** Start the run. Youโ€™ll see progress logs while it scrapes businesses and then scrapes websites for contact info. 8. **Open the dataset and export** When finished, open the **dataset** results view (youโ€™ll see one row per email in most cases) and export to JSON/CSV. No coding requiredโ€”get accurate results in minutes with **Car Dealer Email Scraper**. *** ### Advanced features & SEO optimization - ๐Ÿงญ **Location-driven dealer email harvesting:** Tailor a **car dealership prospecting email scraper** workflow by city so your **B2B car dealer email leads** stay relevant. - ๐Ÿ’พ **Structured output for analysis:** Fields like `avg_rating`, `total_reviews`, and `full_address` make this **vehicle dealer email list** easier to analyze and segment. - ๐Ÿ” **Proxy support for scale:** Use `proxyConfiguration.proxy support` to keep scraping stable for larger **dealer email list scraper** runs. - ๐Ÿ“ง **Email-first dataset rows:** When emails are found, the dataset flattens results so each row contains `email_found`โ€”a big win for import into outreach tools. *** ### Best use cases - ๐Ÿ“ˆ **Sales teams building a car dealership email list:** Generate outreach-ready contacts for multiple dealers in a chosen city. - ๐Ÿค **B2B prospecting for automotive services:** Find dealer contact emails to pitch lead-gen, CRM, advertising, or compliance services. - ๐Ÿงช **Market research & competitor mapping:** Combine dealership identity fields (address, rating, reviews) with contact emails for analysis and scoring. - ๐Ÿ—‚๏ธ **Data enrichment pipelines:** Feed a **car dealership email harvesting tool** output into your database, dedupe by `place_id`, and keep records current. - ๐Ÿงพ **Lead list generation for agencies:** Create segmented lists (by city/state) for multi-client campaigns with consistent structured fields. - ๐Ÿง‘โ€๐Ÿ’ป **Analysts creating prospect datasets:** Use `pages_scraped`, `emails_found`, and scraped social/phone arrays to evaluate data completeness. *** ### Technical specifications - **Supported Input Formats** - โœ… `googleMapsSearchTerm` as a string (search niche like `Car Dealer`) - โœ… `googleMapsLocation` as an array of locations (e.g. `["New York"]`) - โœ… `proxyConfiguration` object with `proxy support` - **Proxy Support** - โœ… `proxyConfiguration.proxy support` enabled by default in the provided input schema - **Retry Mechanism** - โœ… Includes retries and fallbacks for resilience during website scraping (high-level resilience) - **Dataset Structure** - โœ… Dataset fields follow the **Dealerships with Contact Information** schema - โœ… Typically **one dataset row per email** when emails are found (`email_found` is set per row) - **Rate Limits & Performance** - โœ… Performance is optimized for concurrent website scraping while respecting runtime limits - **Limitations** - โŒ If a business has no website, the actor cannot scrape emails and records status accordingly - โŒ Results are limited by your `maxBusinesses` target (the actor stops when reached) *** ### FAQ #### Does Car Dealer Email Scraper require login to run? โœ… No special login beyond Apify Console access is required. You provide inputs in the **INPUT** panel and the actor runs, saving results to its dataset. #### What data does Car Dealer Email Scraper extract? โœ… It extracts dealership contact information including `email_found` (email address per dataset row), `phone`, `scraped_phones`, and `scraped_social_media`, plus dealership context fields like `full_address`, `avg_rating`, and `total_reviews`. #### Can I control how many results I get? โœ… Yes. Use `maxBusinesses` to set the target number of businesses with emails. You can also control whether the limit is applied per location using `scrapeMaxBusinessesPerLocation`. #### Is there a way to prioritize only dealerships that have emails? โœ… Yes. The actor includes an **email-only mode** concept during website scraping, intended to save businesses with emails when enabled. #### What happens if a dealership has no website? โŒ If no website is available, the actor records a non-success `scrape_status` (such as `no_website`), and emails/phones/social links are left empty for that record. #### How does proxy configuration work? โœ… You can set `proxyConfiguration.proxy support` to `true` to enable Apify Proxy as part of the scraping configuration, which is recommended for larger-scale runs. #### Where can I export the results? โœ… Open the actorโ€™s dataset after execution in Apify Console and export as JSON or CSV for use in your outreach, CRM, or analysis workflow. #### Is this tool legal and privacy-compliant to use? โœ… The actor works with **publicly accessible sources**. Itโ€™s your responsibility to comply with applicable laws and platform policies (for example GDPR/CCPA and anti-spam regulations) and use the results appropriately. *** ### Support & feature requests If youโ€™re using **Car Dealer Email Scraper** for a car dealer email scraper workflow and want improvements, weโ€™d love to hear from you. - ๐Ÿ’ก **Feature Requests:** Ideas like CSV export formatting tweaks, additional fields for CRM imports, or custom output structuring are welcome. - ๐Ÿ“ง **Contact:** Email us at . Your feedback helps shape the roadmap for this car dealership prospecting email scraper. *** ### Car Dealer Email Scraper ๐Ÿ“ฌ โ€” Final thoughts *If you need the most comprehensive and SEO-optimized Car Dealer Email Scraper for dealer email lead generation, this is built to help you move from targets to outreach-ready datasets quickly.* # Actor input Schema ## `googleMapsSearchTerm` (type: `string`): Enter the business type or niche for email scraper (e.g., 'car dealer', 'auto dealership'). ## `googleMapsLocation` (type: `array`): Target geographic location for the email scraper (e.g., 'Miami, Florida'). ## `maxBusinesses` (type: `integer`): Target number of emails 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": "Car Dealer", "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": "Car Dealer", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/car-dealer-email-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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": "Car Dealer", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/car-dealer-email-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "googleMapsSearchTerm": "Car Dealer", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call solid-scraper/car-dealer-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/car-dealer-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Car Dealer Email Scraper", "description": "๐Ÿ“ง Car Dealer Email Scraper finds verified car dealership contacts fastโ€”by location, keywords, and niche. Perfect for lead gen, sales teams, and agencies to boost outreach and conversions instantly.", "version": "1.0", "x-build-id": "fQWeIy3b8pKM4eC5F" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~car-dealer-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-car-dealer-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~car-dealer-email-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-car-dealer-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~car-dealer-email-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-car-dealer-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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., 'car dealer', 'auto dealership').", "default": "Car Dealer" }, "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 emails 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 } } } } } } } } } } ```