Glovo Scraper

Pull store listings and full menus from Glovo across every city the platform operates in — restaurants, grocery stores, pharmacies, and retail shops, complete with ratings, delivery fees, ETAs, promotions, and per-item prices. Built for food-delivery market analysts, q-commerce competitive-intelligence teams, and restaurant-supply lead generators who need fresh Glovo catalog and pricing data without collecting it merchant by merchant.

Why This Scraper?

• 4 store verticals in one actor — restaurants, groceries, pharmacy & beauty, and retail shops, all reachable from a single city + vertical picker. No raw category paths to memorize.
• Full menu and catalog extraction — every product on a store comes back with name, description, numeric price, display price, currency, image URL, and the menu section it sits in, each linked to its parent store.
• Store economics most scrapers skip — base and effective delivery fee, a free-delivery flag, delivery ETA, distance, rating percentage, vote count, and live open/closed availability on every store row.
• Top-rated and new-store badges — isTopRated and isNew flags plus active promotions (type, benefit, description), so you can spot rising merchants and live deals at a glance.
• 9 interface languages — English, Spanish, Portuguese, Italian, French, German, Polish, Ukrainian, and Romanian for localized store and product names that match the local market.
• Cuisine and sub-type filtering — narrow a vertical to a niche like burgers, pizza, or sushi to build a focused competitor set instead of the whole city.
• Direct store-link mode — paste specific Glovo store links and the actor scrapes exactly those merchants, products included, for precise competitor tracking.
• Grocery deep-catalog drilldown — walks subcategory aisles to pull thousands of items from large supermarkets, sampling the top aisles up to roughly 3,000 products per store to keep runs predictable.

Use Cases

Market Research

• Map every restaurant, grocer, and pharmacy operating in a Glovo city
• Compare delivery-fee structures and ETAs across an entire vertical
• Track which merchants carry top-rated or new-store badges in a market

Competitive Intelligence

• Watch a named competitor's full menu and prices with direct store links
• Benchmark a chain's offering across multiple cities and languages
• Detect new entrants in a vertical from the isNew badge

Price Monitoring

• Track item-level prices over time for a basket of grocery products
• Compare the same dish or product across competing stores in one city
• Flag delivery-fee or free-delivery-threshold changes between runs

Menu & Catalog Aggregation

• Build a unified product feed across dozens of stores in a vertical
• Power a price-comparison or aggregator site with structured catalog rows
• Localize the same catalog into 9 languages for multi-market listings

Lead Generation for Restaurant Suppliers

• Build outreach lists of restaurants by cuisine sub-type and city
• Prioritize prospects by rating, vote count, and promotion activity
• Enrich a target list with store links, ETAs, and delivery economics

Getting Started

Discover a Vertical in One City

The simplest run — all restaurants in Barcelona, store listings only:

{
    "city": "Barcelona",
    "storeCategory": "food",
    "maxStores": 50
}

Filter to a Cuisine, Localized

Narrow Madrid restaurants to burger spots and return Spanish names:

{
    "city": "Madrid",
    "storeCategory": "food",
    "categoryFilters": ["burgers"],
    "language": "es",
    "maxStores": 30
}

Specific Stores With Full Menus

Paste exact store links and pull every product for each:

{
    "storeUrls": [
        "https://glovoapp.com/en/es/barcelona/stores/vicio-barcelona"
    ],
    "includeProducts": true
}

Full Vertical Sweep With Products

Scrape every grocery store in a city and collect each catalog:

{
    "city": "Lisbon",
    "storeCategory": "groceries",
    "includeProducts": true,
    "maxStores": 20,
    "language": "pt"
}

Input Reference

What to Scrape

Parameter	Type	Default	Description
city	string	"Barcelona"	The Glovo city to scrape, by name (e.g. Barcelona, Lisbon, Madrid, Warsaw). Used to find the right country and stores. Leave the store links empty to discover stores in this city.
storeCategory	string	"all"	Which kind of stores to collect: All verticals, Food & Restaurants, Groceries, Pharmacy & Beauty, or Shops. "All verticals" covers everything Glovo offers in the city.
categoryFilters	string[]	[]	Optionally narrow a vertical to specific cuisines or sub-types, one per line (e.g. burgers, pizza, sushi). Leave empty to scrape the whole vertical.
storeUrls	string[]	[]	Paste specific Glovo store links to scrape exactly those stores, one per line. Products are always collected for these. Leave empty to discover stores from the city and vertical above.

Options

Parameter	Type	Default	Description
includeProducts	boolean	false	Also collect the full product or menu list for each store. Restaurants and normal stores return their whole menu in full. Very large grocery and quick-commerce stores are sampled — the actor walks their top aisles to a safe depth and stops at roughly 3,000 products per store — so a big hypermarket's catalog may be partial.
maxStores	integer	50	How many stores to keep from this run. Each vertical returns up to about 50 stores (Glovo's public listing limit), so a single vertical can't exceed ~50 no matter what you set here. To collect more, choose All verticals (each vertical adds its own ~50) or add several Sub-type Filters (each filter pulls its own set). Setting 0 removes our cap but not the ~50-per-vertical source limit. Start with 20–50 to test; if you turn on products, each store can add many extra rows.
language	string	"en"	Language for store and product names and descriptions: English, Spanish, Portuguese, Italian, French, German, Polish, Ukrainian, or Romanian.

Output

Every row carries a recordType field — store or product — so you can filter the dataset cleanly. Product rows are present only when Include products is enabled or when store links are supplied.

Store (recordType: "store")

{
    "recordType": "store",
    "title": "VICIO",
    "slug": "vicio-barcelona",
    "url": "https://glovoapp.com/en/es/barcelona/stores/vicio-barcelona",
    "rating": 93,
    "votes": "500+",
    "deliveryFeeBase": 1.99,
    "deliveryFeeEffective": 0,
    "isFreeDelivery": true,
    "currency": "EUR",
    "eta": "30-40 min",
    "distance": "1.2 km",
    "availability": "OPEN",
    "promotions": [
        { "type": "FREE_DELIVERY", "benefit": "Free delivery", "description": "Free delivery on orders over 15€" }
    ],
    "tag": "Burgers",
    "isTopRated": true,
    "isNew": false,
    "category": "food_1",
    "city": "Barcelona"
}

Core Fields

Field	Type	Description
recordType	string	Always "store"
title	string	Store display name
slug	string	URL-friendly store identifier
url	string	Full Glovo store page link
tag	string	Store category tag (e.g. Burgers, Sushi)
category	string	The vertical the store was found under
city	string	City the store belongs to

Delivery & Economics

Field	Type	Description
rating	number	Rating percentage (e.g. 93)
votes	string	Number of ratings (e.g. "500+" or "396")
deliveryFeeBase	number	Base delivery fee before discounts
deliveryFeeEffective	number	Effective fee after discounts (0 when free)
isFreeDelivery	boolean	True when delivery is free
currency	string	Currency code for fees (EUR, PLN, etc.)
eta	string	Estimated delivery time (e.g. "30-40 min")
distance	string	Distance from the city location

Status & Badges

Field	Type	Description
availability	string	"OPEN" or "CLOSED"
promotions	object[]	Active promotions, each { type, benefit, description }
isTopRated	boolean	Top-rated badge
isNew	boolean	New-store badge

Product (recordType: "product")

{
    "recordType": "product",
    "storeSlug": "vicio-barcelona",
    "storeName": "VICIO",
    "name": "Doble Bacon",
    "description": "Two smashed patties, bacon, cheddar and house sauce",
    "price": 11.5,
    "currency": "EUR",
    "priceDisplay": "11,50 €",
    "productId": "1234567",
    "categoryName": "Burgers",
    "imageUrl": "https://images.glovoapp.com/...",
    "city": "Barcelona"
}

Field	Type	Description
recordType	string	Always "product"
storeSlug	string	Parent store identifier (join key to its store row)
storeName	string	Parent store display name
name	string	Product or menu item name
description	string	Product description
price	number	Numeric price
currency	string	Currency code (EUR, etc.)
priceDisplay	string	Formatted price (e.g. "11,50 €")
productId	string	Glovo product identifier
categoryName	string	Menu section the product sits in
imageUrl	string	Direct product image link
city	string	City context

Tips for Best Results

• Maximize store coverage with breadth, not a bigger maxStores. A single vertical returns up to about 50 stores — that's Glovo's public listing limit, so raising maxStores past 50 on one vertical won't add more. To collect more of a city, choose All verticals (each vertical adds its own ~50) or add several cuisine / sub-type filters (each filter pulls its own set of stores).
• Expect a sample, not a full catalog, on the biggest grocery stores. Restaurants and normal shops return their complete menu. Very large grocery and quick-commerce stores are sampled across their top aisles up to about 3,000 products per store, so a hypermarket's catalog may be partial — that keeps runs fast and predictable.
• Leave products off when you only need store listings. Both store rows and product rows count toward your results — includeProducts can multiply a run many times over, especially for grocery stores. Keep it off for a fast, cheap store census, and turn it on only when you need item-level data.
• Control cost with maxStores. When products are on, set a modest cap (10–30) so a single large grocery catalog doesn't balloon the result count. A grocery store can add several thousand product rows on its own.
• Use store-link mode for precise competitor tracking. Paste exact store links to scrape just the merchants you care about — products are always collected for those, so you get full menus without sweeping a whole vertical.
• Match the language to the local market. Set language to the country's language (e.g. es for Spain, pt for Portugal) so product names, descriptions, and menu sections read the way local customers see them.
• Narrow with cuisine filters. Adding categoryFilters like burgers or sushi trims a busy vertical down to a focused, comparable set of competitors.
• Start small to validate. Run 20–50 stores first to confirm the city, vertical, and language are right before scaling up to a full sweep.
• Filter by recordType downstream. Split the dataset into a clean store table and a product table using the recordType field, then join products back to stores on storeSlug.

Pricing

$2.00 per 1,000 results — flat pay-per-result. No compute charges — you only pay per result returned.

Results	Estimated Cost
100	$0.20
1,000	$2.00
10,000	$20.00
100,000	$200.00

A "result" is any row in the output dataset — a store or a product. Turning on full menu and catalog extraction adds product rows (many per store), so use maxStores and the products toggle to keep your result count where you want it.

Integrations

Export data in JSON, CSV, Excel, XML, or RSS. Connect to 1,500+ apps via:

• Zapier / Make / n8n — Workflow automation
• Google Sheets — Direct spreadsheet export
• Slack / Email — Notifications on new results
• Webhooks — Trigger custom workflows on run completion
• Apify API — Full programmatic access

Legal & Ethical Use

This actor is designed for legitimate market research, competitive intelligence, price monitoring, and lead generation. You are responsible for complying with applicable laws and Glovo's terms of service, including making reasonable-rate requests and respecting how the data may be used. Do not use extracted data for spam, harassment, or any illegal purpose.