# Doordash Email Scraper (`scraper-engine/doordash-email-scraper`) Actor

DoorDash Email Scraper extracts publicly available restaurant email addresses from DoorDash listings. Build targeted contact lists by city or cuisine. Ideal for suppliers, marketers, and agencies running restaurant outreach campaigns.

- **URL**: https://apify.com/scraper-engine/doordash-email-scraper.md
- **Developed by:** [Scraper Engine](https://apify.com/scraper-engine) (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

$19.99/month + usage

To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period. You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#rental-actors

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

### **Social Media** Email Scraper 📱

The Doordash Email Scraper allows users to **extract** publicly available **contact** information referenced on Doordash pages. This includes email addresses found in the title and snippet text of indexed restaurant, merchant, and informational pages.

With this tool, you can retrieve public email addresses and other metadata to support your research or business needs. The scraper is designed to provide accurate and up-to-date information, ensuring the **data** is relevant and useful.

It is suitable for **extract**ing Doordash-related **contact**s and other related **data** for legitimate purposes. By automating the **data** collection process, the Doordash Email Scraper saves time and ensures consistency in **data** quality.

It is a reliable solution for businesses and individuals seeking to gather Doordash-related **data** efficiently and ethically.

Doordash Email Scraper is a powerful tool designed to help users extract publicly available contact information referenced on Doordash pages. This tool is ideal for those looking to streamline their marketing efforts or build targeted email lists efficiently.

With the Doordash Email Scraper, you can automate the process of gathering public emails, saving time and resources. It provides a reliable way to access and organize contact information without manual data entry.

This Doordash data extraction tool is designed to be user-friendly and highly customizable, catering to various business needs. It ensures accurate and up-to-date information, making it a valuable asset for any data-driven strategy.

### Support and feedback

- **Bug reports**: Open a ticket in the repository Issues section
- **Custom features**: Contact our enterprise support team
  *Email: dev.scraperengine@gmail.com*

### Extractable Data Table 📊

Each result row contains the following fields:

| Data Type | Description |
| --- | --- |
| network | Source platform (e.g. doordash.com). |
| keyword | The keyword that produced this result. |
| title | Title of the result (usually the page name). |
| description | Snippet text from the result, which may contain contact info. |
| url | Direct URL to the Doordash page. |
| email | Publicly available email address extracted from the result. |

### Key Features of **Social Media** Email Scraper

Here are the **standout features** that make the **Social Media** Email Scraper a **top-tier tool** for **marketers**, **agencies**, and **researchers**:

- ⭐ **Automated** email scraping for Doordash pages
- ⭐ **Accurate** and up-to-date data extraction capabilities
- ⭐ **Customizable** scraping parameters to target specific data
- ⭐ User-friendly interface for seamless operation
- ⭐ **Advanced** filtering options for refined data collection
- ⭐ Compliance with legal and ethical data scraping standards
- ⭐ Scalable solutions for businesses of all sizes
- ⭐ **Secure** and reliable data handling processes
- ⭐ Supports bulk email extraction for large-scale operations
- ⭐ Detailed reporting and export options for data management

### How to use **Social Media** Email Scraper 🚀

Follow this **simple, step-by-step guide** to start extracting **Social Media** emails today:

1. ✅ **Sign up** or **log in** to access the Doordash Email Scraper tool
2. ✅ Navigate to the dashboard and select the scraping parameters
3. ✅ Enter the target keywords for Doordash pages
4. ✅ Customize filters to refine the data extraction process
5. ✅ **Start** the scraping process and monitor progress in real-time
6. ✅ **Review** the extracted data on the dashboard for accuracy
7. ✅ **Export** the data in your preferred format such as CSV or JSON
8. ✅ **Integrate** the data into your CRM or email marketing platform

### Use Cases 🎯

Marketing Campaigns
🎯 Build targeted email lists for promotional campaigns
🎯 Enhance customer outreach with accurate contact information

Business Development
🎯 **Identify** potential partners or contacts referenced on Doordash
🎯 Gather contact details for lead generation and networking

Data Analysis
🎯 **Analyze** publicly referenced contact patterns on Doordash
🎯 Extract data for market research and trend analysis

Customer Support
🎯 Retrieve contact information to address customer inquiries
🎯 Build a comprehensive database for customer relationship management

### Why choose us? 💎

Choosing our Doordash Email Scraper ensures you gain access to a **reliable** and efficient tool for data extraction. Our software is designed with **advanced** scraping capabilities, ensuring accurate and up-to-date information.

We prioritize user experience, offering a **user-friendly** interface and customizable features to meet diverse needs. Our tool complies with all legal and ethical guidelines, providing peace of mind for businesses and developers.

Whether you're building a Doordash email database or automating your email list generation, our tool delivers exceptional performance. We also offer robust customer support to assist you at every step of the process.

By choosing us, you can save time, reduce manual effort, and focus on leveraging data for your business growth. Our **scalable** solutions cater to businesses of all sizes, ensuring that you can adapt the tool to your specific requirements.

Trust our Doordash data extraction tool to deliver **reliable** results and enhance your data-driven strategies.

### **Social Media** Email Scraper Scalability 📈

The Doordash Email Scraper is designed to handle projects of any size, making it a scalable solution for businesses and developers. Whether you're a small business owner or a large enterprise, our tool adapts to your data extraction needs.

It supports bulk email scraping, allowing you to gather large volumes of data **efficient**ly. With **advanced** filtering options, you can target specific pages or data points, ensuring relevance and accuracy.

Our software is built to handle high-demand operations without compromising performance. As your business grows, the Doordash Email Scraper grows with you, offering flexible solutions for data management.

Its robust infrastructure ensures **seamless** operation, even during **large-scale** scraping tasks. Trust our tool to deliver consistent results, regardless of the scope of your project.

### **Social Media** Email Scraper Legal Guidelines ⚖️

**Yes**—scraping **Social Media** is **legal** as long as you follow **ethical** and **compliant** practices. The **Social Media** Email Scraper extracts only **publicly available** information from **public** **Social Media** pages, making it **safe** and **compliant** for **research**, **marketing**, and **analysis**.

#### Legal & Ethical Guidelines

⚖️ **Ensure** compliance with Doordash's terms of service before using the scraper
⚖️ **Do not** use the tool for unauthorized or malicious purposes
⚖️ **Obtain** user consent where required before extracting personal data
⚖️ **Avoid** scraping sensitive or confidential information from pages
⚖️ **Use** the tool only for legitimate business or research purposes
⚖️ **Do not** resell or distribute extracted data without proper authorization
⚖️ Follow all applicable data protection and privacy laws in your region
⚖️ Regularly review updates to Doordash's policies to ensure compliance

### Input Parameters 🧩

📦 Example Input (JSON)

```json
{
  "keywords": ["restaurant partner"],
  "platform": "Doordash",
  "location": "",
  "emailDomains": ["@gmail.com", "@outlook.com"],
  "maxEmails": 10,
  "engine": "legacy",
  "proxyConfiguration": { "useApifyProxy": false }
}
```

### Input Table

| Field | Type | Required | Description |
| --- | --- | --- | --- |
| keywords | array | ✅ Yes | Keywords used to find relevant Doordash pages. One or more. |
| platform | string | No | Platform to scrape. Currently `Doordash`. |
| location | string | No | Optional location filter. Empty = global. |
| emailDomains | array | No | Keep only emails from these domains (e.g. `@gmail.com`). Custom/business domains supported. Empty = all domains. |
| maxEmails | integer | No | Max emails to collect per keyword (default `10`, range 1–100000). |
| engine | string | No | Processing engine. Currently `legacy`. |
| proxyConfiguration | object | No | Proxy settings. Empty = the actor auto-selects the best proxy (recommended). |

> ℹ️ Emails are sourced from publicly available information only. Yield depends on how many pages publicly expose a contact email. Broaden `keywords`/`emailDomains` and raise `maxEmails` for more results.

### Output Format 📤

📝 Example Output (JSON)

```json
[
  {
    "network": "doordash.com",
    "keyword": "restaurant partner",
    "title": "Get Started as a Doordash Merchant",
    "description": "Questions about becoming a partner? Reach our team at partners@example-restaurantgroup.com",
    "url": "https://www.doordash.com/business/example-restaurant-group",
    "email": "partners@example-restaurantgroup.com"
  }
]
```

### Output Table

| Data Type | Description |
| --- | --- |
| network | Source platform (doordash.com) |
| keyword | Keyword that triggered the result |
| title | Result title (usually the page name) |
| description | Public snippet, may contain contact info |
| url | Direct Doordash page link |
| email | Extracted email address |

### FAQ ❓

#### What is the Doordash **Email Scraper**?

The Doordash Email Scraper is a tool designed to extract publicly available email addresses and other contact information referenced on Doordash pages.

#### Is the Doordash **Email Scraper** **legal** to use?

**Yes**, it is legal to use as long as you comply with Doordash's terms of service and applicable data protection laws.

#### What data can I **extract** with this tool?

You can extract publicly available email addresses along with the result title, snippet, and page URL for each match.

#### Can I customize the scraping parameters?

**Yes**, the tool allows you to customize filters and parameters for targeted data extraction.

#### Is the tool suitable for **large-scale** data scraping?

**Yes**, the Doordash Email Scraper is scalable and supports bulk email extraction.

#### How do I **export** the **extract**ed data?

You can export the data in various formats such as **CSV** or **JSON** for easy integration.

#### Does the tool comply with data privacy regulations?

**Yes**, it is designed to comply with data protection and privacy laws when used responsibly.

#### What are the system requirements for using this tool?

The tool is web-based and requires a stable internet connection and a modern browser.

#### Can I scrape sensitive information with this tool?

**No**, the tool is not intended for scraping sensitive or confidential information.

#### Is **customer support** available?

**Yes**, we offer robust customer support to assist you with any issues or questions.

#### How often is the data updated?

The tool ensures that the extracted data is accurate and up-to-date at the time of scraping.

#### Can I use this tool for personal projects?

**Yes**, the tool can be used for personal or business projects, provided it complies with legal guidelines.

#### What happens if Doordash updates its platform?

Our team regularly updates the scraper to ensure compatibility with Doordash's platform changes.

#### Is there a **limit** to the amount of data I can scrape?

The tool supports scalable operations, and limits depend on your subscription plan.

#### Can I automate the scraping process?

**Yes**, the tool allows for automation to streamline data extraction tasks.

# Actor input Schema

## `keywords` (type: `array`):

🎯 The words that power your search! Add one or more keywords (e.g. \['restaurant partner']) and the actor finds public Doordash pages matching them, then 📧 extracts any email addresses it finds. 💡 Tip: more specific keywords = more targeted leads.

## `platform` (type: `string`):

📱 The site to scrape. Currently locked to Doordash — more platforms coming soon! 🚀

## `location` (type: `string`):

🗺️ Optional geo-targeting! Add a city or region (e.g. 'London' 🇬🇧, 'New York' 🗽, 'Dubai' 🏙️) to narrow results to pages mentioning that place. ✨ Leave empty to search the whole globe 🌍.

## `emailDomains` (type: `array`):

🎛️ Keep only emails from the domains you care about — type as many as you like! ✍️ Popular picks: 📮 @gmail.com · 📨 @outlook.com · 💌 @hotmail.com · 💜 @yahoo.com · ☁️ @icloud.com · 📬 @aol.com · 🔒 @protonmail.com · 📥 @live.com · 📧 @gmx.com · 🟡 @yandex.com · 📗 @zoho.com. 🏢 Custom/business domains work too — e.g. @yourcompany.com. 🕳️ Leave empty to collect emails from ALL domains. 💡 Adding a domain also sharpens the search 🎯.

## `maxEmails` (type: `integer`):

🎚️ How many emails to collect per keyword before moving on. ⚡ Higher = more leads but longer runs. Default is 10 ✅ (range 1 – 100,000).

## `engine` (type: `string`):

🔧 The processing engine. Currently 'legacy' 🛡️ — a reliable, battle-tested extraction pipeline. More engines on the roadmap! 🚧

## `proxyConfiguration` (type: `object`):

🌐 Control how the actor connects to the internet. 🆓 Leave it empty and the actor auto-selects the best proxy for reliable results. 🔄 On any failed response it rotates the connection and retries up to 3× automatically. 🧠 Advanced users can plug in custom proxies here.

## Actor input object example

```json
{
  "keywords": [
    "restaurant partner"
  ],
  "platform": "Doordash",
  "location": "",
  "emailDomains": [
    "@gmail.com"
  ],
  "maxEmails": 10,
  "engine": "legacy",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "restaurant partner"
    ],
    "emailDomains": [
        "@gmail.com"
    ],
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("scraper-engine/doordash-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "keywords": ["restaurant partner"],
    "emailDomains": ["@gmail.com"],
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("scraper-engine/doordash-email-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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": [
    "restaurant partner"
  ],
  "emailDomains": [
    "@gmail.com"
  ],
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call scraper-engine/doordash-email-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scraper-engine/doordash-email-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/dFz9bZjJuVdB0BswT/builds/4PebWdcWYzsNnyN1g/openapi.json