How to Extract Restaurant Data from Google Maps with TypeScript

Finding reliable, structured restaurant information from Google Maps often means tedious manual research or the frustration of external APIs with restrictive usage limits. Developers and technical teams must also contend with the challenges of authentication, bot-detection mechanisms, and inconsistent or incomplete datasets.

This Airtop automation tackles these challenges seamlessly using TypeScript. Leverage real browser sessions for reliable scraping, handle complex login scenarios effortlessly (OAuth, Captcha, 2FA), and receive organized JSON output. Get clean, structured restaurant data from Google Maps quickly, allowing your team to build robust services and applications with confidence.

Who is this Automation for?

• Web Developers

• Automation Engineers

• Data Analysts

• Technical SEO Specialists

Key Benefits

• Real browser sessions for accurate data scraping

• Structured JSON data output

• Reliable handling of authentication (OAuth, 2FA, Captcha)

• Highly customizable TypeScript automation scripts

Use Cases

• Creating local dining guides and directories

• Competitor research for hospitality and food businesses

• Enriching restaurant databases in mobile or web apps

• Streamlining meal-planning services and delivery apps

Getting Started with the Extract Restaurant Data from Google Maps Automation

Follow these simple steps to implement automated extraction of structured restaurant data using Google Maps and Airtop with TypeScript.

How the Extract Restaurant Data from Google Maps Automation Works

This automation initiates a browser session with Airtop to access Google Maps directly, handling dynamic page interactions reliably with TypeScript. Authentication barriers including OAuth logins or Captchas are neatly bypassed to ensure uninterrupted scraping. Restaurant data, such as name, location, reviews, opening hours, and ratings, is meticulously extracted and returned in structured JSON, ideal for downstream integration into your platforms or databases.

What You'll Need

• Airtop Account

• Node.js and TypeScript installed

• Google Maps URLs to scrape

• (Optional) Google account credentials if scraping authenticated content

Setting Up the Automation

1. Sign in to your Airtop account and create a new automation task.

2. Clone or download the pre-built TypeScript automation template provided for Google Maps extraction.

3. Configure your scraping targets by editing URL parameters or queries in the TypeScript configuration file.

4. Deploy your automation script locally or via your preferred TypeScript-supported hosting.

5. Execute your automation and start receiving structured restaurant data formatted as JSON immediately.

Customize the Automation

Easily tailor this Google Maps extraction automation directly in TypeScript, empowering you to adapt it to your team's exact specifications:

• Extract additional data points, such as menu items or pricing information.

• Adjust scraping frequency and handle larger-scale data collection with concurrency settings.

• Integrate data directly into third-party applications or database services automatically.

• Incorporate notification systems to alert your team upon successful or failed scraping tasks.

Automation Best Practices

• Respect Google's Terms of Service and robots.txt guidelines in your scraping strategy.

• Include error handling logic in your TypeScript code to gracefully manage unexpected data format changes.

• Maintain updated browser headers and implement realistic delays to avoid scraping detection.

• Regularly validate scraped data accuracy and completeness to ensure reliability of downstream automation.