A fast, accurate, and flexible tool designed to pull email addresses directly from Doordash listings. It streamlines contact discovery for outreach, research, and growth-focused teams that need verified Doordash emails at scale.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for Doordash Email Scraper you've just found your team — Let’s Chat. 👆👆
This project automates the process of finding and extracting emails from Doordash restaurant and merchant listings based on custom keywords, locations, and email domains. It eliminates manual searching and helps marketers, analysts, and businesses quickly gather relevant contact data.
- Speeds up lead generation by automatically scanning targeted Doordash listings.
- Helps discover contacts that match specific keywords or business titles.
- Filters results by location for more precise targeting.
- Supports custom email-domain filtering to match outreach goals.
- Reduces rate-limit issues with optional proxy usage.
| Feature | Description |
|---|---|
| Keyword-Based Search | Finds email addresses from listings matching your chosen keywords. |
| Location Filtering | Narrows results to specific geographic areas for precise targeting. |
| Platform Selection | Exclusively processes Doordash listings for accuracy. |
| Custom Email Domains | Lets you filter results using domains like @gmail.com or others. |
| Proxy Support | Helps maintain stability and avoid rate limits during large crawls. |
| Field Name | Field Description |
|---|---|
| keyword | The keyword used to find the listing. |
| title | The business or merchant name associated with the discovered email. |
| description | A text snippet showing the extracted email in context. |
| url | Direct link to the Doordash listing. |
| The email address identified on the page. |
[
{
"keyword": "john",
"title": "John's Pizza & Grill",
"description": "Contact us at johnspizza@gmail.com",
"url": "https://www.doordash.com/store/johns-pizza",
"email": "johnspizza@gmail.com"
}
]
Doordash Email Scraper/
├── src/
│ ├── runner.py
│ ├── extractors/
│ │ ├── doordash_parser.py
│ │ └── email_utils.py
│ ├── outputs/
│ │ └── exporter.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── inputs.sample.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- Marketing teams use it to collect targeted emails for outreach, so they can launch campaigns faster.
- Business development reps use it to identify potential restaurant partners, helping them expand pipelines.
- Researchers use it to analyze business categories and communication patterns across regions.
- Agencies use it to automate data gathering for clients and reduce manual lookup work.
Does it only work with Doordash? Yes, this tool focuses solely on Doordash listings for high accuracy and consistent structure.
Can I use my own email domains? Absolutely. You can specify any number of custom domains such as @gmail.com or company-specific ones.
Do I need proxies? Not always. For high-volume scraping sessions, proxies help reduce the chance of temporary blocks.
What formats can I export data in? You can download results as JSON, CSV, or Excel depending on your workflow needs.
Primary Metric: Processes an average of 40–60 listings per minute, depending on proxy usage and keyword complexity.
Reliability Metric: Maintains over a 95% extraction success rate across repeated runs on typical datasets.
Efficiency Metric: Optimized to minimize unnecessary page loads, reducing bandwidth usage and improving throughput.
Quality Metric: Delivers high-precision email detection with contextual verification to avoid false positives.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
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"Exceptional results, clear communication, and flawless delivery. Syed
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