Glovo Scraper

Glovo Scraper is an Apify actor that extracts restaurant data, category listings, and product information from the Glovo platform. This data extraction includes restaurant details, delivery fees, promotions, categories, and menus, making it an ideal tool for anyone researching Glovo’s marketplace.

Why scrape Glovo?

Glovo is a leading food delivery service with a broad range of restaurant options and localized promotions. Scraping Glovo data can provide valuable insights for market analysis, competitor research, and price tracking. Here are some use cases:

• Monitor promotions across categories or specific restaurants.
• Compare delivery fees in different locations.
• Track restaurant ratings and popularity over time.

Features

• Scrapes detailed restaurant information, including name, address, phone number, and promotions.
• Extracts restaurant listings from Glovo categories.
• Stores data in separate named datasets for easy access:
  • category-restaurants: Contains restaurant listings found in categories.
  • restaurant-products: Contains detailed product information for each scraped restaurant.
• The default dataset contains a summary record. No combined data is pushed into the default dataset by default.

How much will it cost to scrape Glovo?

The access to the scraper itself costs $20/month.

Apify provides $5 free usage credits every month on the Free plan. This means you can scrape a limited number of restaurants or categories for free each month. For higher-volume scraping, consider upgrading to an Apify subscription. The Starter plan at $49/month allows you to scrape more data, while the Scale plan offers higher quotas for professional use cases.

Usage

Input Parameters

The actor accepts the following input parameters:

• location (Required): A city name (e.g., Lisbon) where the scraper will look for restaurants.
• categories (Optional): An array of categories to scrape, such as "burger" or "pizza."
• detailed (Optional): A boolean, if set to true, it will scrape detailed information for each restaurant in the selected categories.
• restaurants (Optional): A list of specific restaurants to scrape, either by URL or slug.

Notes:

• This scraper utilizes Residential Proxies for all requests to ensure reliable data extraction.
• Detailed scraping increases runtime as it fetches additional information from each restaurant's page. Avoid setting a timeout for large or detailed scrapes.

Example Input

1{
2    "location": "Lisbon",
3    "categories": [
4        "burger",
5        "pizza"
6    ],
7    "detailed": true,
8    "restaurants": [
9        "https://example-glovo-store-url.com",
10        "the-wall-burger"
11    ]
12}

Running the Actor

You can run the actor directly from the Apify platform or via API. Ensure you provide the necessary input parameters as specified above.

Output

The actor outputs data in three datasets:

1. Default Dataset: Contains a summary record at the end of the run.
2. Named Datasets:
   • category-restaurants Dataset: Contains restaurant listings from category pages.
   • restaurant-products Dataset: Contains detailed product listings for each scraped restaurant.
   • Accessible in the Storage section under Datasets.
   • Data is organized and separated for easier analysis.

Data Fields

Category Restaurants Dataset (category-restaurants):

• name: Restaurant name.
• slug: Restaurant slug for Glovo.
• address: Full address of the restaurant.
• phoneNumber: Contact number.
• rating.percentage: Rating percentage (e.g., 92%).
• rating.count: Number of ratings.
• open: Boolean indicating if the restaurant is open.
• deliveryFee: Delivery fee for the restaurant.
• promotions: Array of promotions with title, description, and type.
• category: Category of the restaurant (e.g., "burger").

Restaurant Products Dataset (restaurant-products):

• restaurantSlug: The slug or URL of the restaurant.
• name: Product name.
• description: Product description.
• price: Product price.

NOTE: Apify datasets support multiple export formats including JSON, CSV, and XLSX, so you can easily integrate scraped Glovo data into your workflows.

Limitations and Constraints

• Glovo's website may employ region-specific structures, which can result in incomplete data for unsupported locations or categories.
• IMPORTANT: Ensure the location matches a valid city name supported by Glovo. Invalid locations will result in no data.

Is it legal to scrape Glovo?

Scraping data from Glovo must comply with local and international data protection regulations. Avoid scraping personal data, and ensure you have a legitimate purpose for your activities. Consult legal counsel if you have concerns about the legality of your scraping.