Pizza Hut Scraper [$3.50/1K💰] | 18 Markets | Stores & Fees

Pizza Hut Store & Charges Scraper (18 Markets)

Collect normalized Pizza Hut store locations from 18 markets — addresses, coordinates, phone numbers, services, hours and status — plus a separate dataset of published store-level delivery fees and order minimums, for mapping, market research, competitor analysis and location-based apps.

This Apify Actor uses Pizza Hut's public locator APIs, XML feeds and server-rendered store pages. It does not open a browser, so runs are fast and inexpensive, and everything is available through the Apify API, scheduler, integrations and webhooks. It covers the US, UK, Canada, France, Germany, Poland, Czechia, Hungary, Spain, India, Taiwan, Saudi Arabia, the UAE, Bahrain, Jordan, Kuwait, Oman and Qatar.

Map & Analyze Pizza Hut Locations At Scale

• Restaurant and franchise mapping — plot every store with coordinates, address and market on a map.
• F&B market research — compare store density and coverage across 18 countries in one normalized shape.
• Delivery and service analysis — see delivery, collection, dine-in and online-ordering flags and published fees per store.
• Location-based applications — power store finders, delivery-zone tools and local SEO workflows.
• Directory monitoring — schedule daily or weekly runs to track new, closed or changed locations.

How It Works

Looking for a reliable Pizza Hut scraper or a practical Pizza Hut locator API alternative? Choose one or more of the 18 markets, optionally add a city, postcode, address, store number or locator URL, and run the Actor to get clean, normalized store records for store mapping, F&B market research and location-based products. Each record includes the store name, address, GPS coordinates, phone, timezone, services (delivery, collection, dine-in, online ordering), published hours and payments, store URLs, open/closed status and franchise data across the US, UK, Canada, France, Germany, Poland, Czechia, Hungary, Spain, India, Taiwan, Saudi Arabia, the UAE, Bahrain, Jordan, Kuwait, Oman and Qatar.

Use the dataset to map coverage, benchmark store density, compare delivery and collection availability, track new or closed locations over time, and feed store finders or GIS dashboards. Published delivery surcharges and order minimums go to a separate additionalCharges dataset. Export as JSON, CSV or Excel, or pull results through the Apify API. Markets that do not publish a field return null with an explanatory note instead of an invented value. Start with a small run, then pay from $3.50 per 1,000 stores.

Input Parameters

Field	Type	Required	Default	Notes
markets	array	No	All 18 markets	Multi-select market codes. Unknown codes are ignored; empty = all markets.
search	array	No	[]	City, postcode, address, store name/number, phone fragment, or Pizza Hut locator URL. Multiple entries use OR.
maxItems	integer	No	0	Max stores to output across all selected markets. 0 = everything.
includeAdditionalCharges	boolean	No	true	Write the separate additionalCharges dataset.
includeClosedStores	boolean	No	true	Keep stores the source marks closed.
forceRefresh	boolean	No	false	Ignore cached responses and fetch fresh data.

Search is applied after the selected directories are collected, so maxItems reduces the output but does not reduce upstream requests. Select only the markets you need for a faster, cheaper run. Supported market codes: US, UK, CA, FR, DE, PL, CZ, HU, ES, IN, TW, SA, AE, BH, JO, KW, OM, QA.

Output Fields

Store rows (default dataset): id, source, country, market, currency, store_number, name, store_type, store_types, address (structured with line1, city, region, postal_code, country_code, formatted), latitude, longitude, phone, timezone, services (delivery, collection, dine_in, online_ordering), hours, payments, urls, status, franchise, meta.

Additional-charge rows (additionalCharges dataset): id, store_id, country, market, store_number, store_name, store_type, store_address, currency, delivery_surcharge, delivery_fee, min_delivery_order, min_collection_order, max_cash_order, has_published_charges, note, source_url, scraped_at.

A market that does not publish a field returns null for it (it is not false), explained in the row or run summary instead of being invented.

Example Input

Several markets:

{
  "markets": ["DE", "ES", "TW", "SA"],
  "search": [],
  "maxItems": 0,
  "includeAdditionalCharges": true,
  "includeClosedStores": true,
  "forceRefresh": false
}

Search by city and postcode in the US:

{
  "markets": ["US"],
  "search": ["Philadelphia, PA", "19107"],
  "maxItems": 20
}

Example Output

Store row:

{
  "id": "de:112ebb29-0792-b9a8-b2dd-8ac6ee430fd6",
  "source": "pizzahut-de-tictuk",
  "country": "DE",
  "market": "DE",
  "currency": "EUR",
  "store_number": "112ebb29-0792-b9a8-b2dd-8ac6ee430fd6",
  "name": "Pizza Hut Bochum",
  "store_type": "restaurant",
  "store_types": ["takeaway", "dine_in"],
  "address": {
    "line1": "Am Einkaufszentrum 22",
    "city": "Bochum",
    "postal_code": null,
    "country_code": "DE",
    "formatted": "Am Einkaufszentrum 22, Bochum, NRW, DE"
  },
  "latitude": 51.49536193,
  "longitude": 7.27723384,
  "phone": "0234 232355",
  "timezone": "Europe/Berlin",
  "services": { "delivery": false, "collection": true, "dine_in": true, "online_ordering": true },
  "status": { "closed": false }
}

Charge row:

{
  "id": "de:112ebb29-0792-b9a8-b2dd-8ac6ee430fd6:charges",
  "store_id": "de:112ebb29-0792-b9a8-b2dd-8ac6ee430fd6",
  "market": "DE",
  "currency": "EUR",
  "delivery_surcharge": null,
  "delivery_fee": null,
  "min_delivery_order": null,
  "min_collection_order": null,
  "max_cash_order": null,
  "has_published_charges": false,
  "note": "Pizza Hut Germany does not publish store-level delivery fees or minimum order values in its public store locator data."
}

Download the dataset as JSON, HTML, CSV or Excel. The OUTPUT key-value record contains per-market counts, dataset IDs, per-source status, cache settings and limitations.

Automate Store Monitoring With Schedules & Webhooks

• Schedule daily or weekly runs to track new, closed or changed Pizza Hut locations across markets.
• Use search for ad-hoc checks on a city, postcode or store number without re-pulling every market.
• Send results to Google Sheets, Zapier, Make or your own webhook for franchise dashboards and coverage alerts.
• Read both datasets via the Apify REST API to power a store finder or market-analysis tool.

Related Actors

• Pizza Hut Store Locator (alternative) — an alternative Pizza Hut locator covering US, CA, UK, FR, DE, ES, IN and AU.
• DoorDash Scraper — restaurant and menu data from a major delivery platform.
• Uber Eats Scraper — restaurant listings and menus for delivery-market analysis.
• Deliveroo Scraper — UK/EU restaurant and menu data for F&B research.
• OpenTable Scraper — restaurant reservations, ratings and metadata.

Frequently Asked Questions

Why use this Actor instead of the official Pizza Hut API?

Pizza Hut does not offer a public store-locator API for third parties. Each market publishes locations through its own locator API, XML feed or server-rendered pages. This Actor unifies all of them into one input schema and one normalized store shape, so you do not write a separate integration per country.

What are alternatives to scraping Pizza Hut?

Alternatives include a general restaurant-data actor, a single-market locator tool, or OpenStreetMap-based business data. This Actor covers 18 markets at $0.0035 per store, and it also emits a separate dataset of published delivery fees and order minimums — the practical differentiator versus single-market locators.

How many stores and markets are covered?

18 markets. Verified snapshot sizes include 508 UK, 619 Canada, 108 France, 1009 India, 72 Germany, 145 Poland, 13 Czechia, 29 Hungary, 14 live Spain pickup stores, 331 Taiwan, and 279 Middle East stores. The US count is dynamic and depends on the source's current saved filter.

Why are many charge values null?

Most Pizza Hut markets do not publish store-level delivery fees or minimum order values in their public locator data. The Actor still emits a row for every store and sets has_published_charges: false with an explanatory note.

Why are some hours or coordinates missing?

Full weekly schedules are available for the US, Germany, Poland, Czechia and Hungary; other markets expose only the current day or no complete schedule. Middle East locators do not publish latitude/longitude, so those fields are null.

Can I scrape every market in one run?

Yes, but a full run is the most expensive because the scraper collects each selected market's complete directory before applying search and maxItems. Select only the markets you need.

For AI Agents & LLM Apps

Purpose: return normalized Pizza Hut store locations (and optionally published delivery charges) for selected markets and search terms.

Minimal working input:

{ "markets": ["DE"] }

Search variant:

{ "markets": ["US"], "search": ["Philadelphia, PA"], "maxItems": 20 }

Output fields (stores): id, source, country, market, currency, store_number, name, store_type, store_types, address, latitude, longitude, phone, timezone, services, hours, payments, urls, status, franchise, meta.

Output fields (charges): id, store_id, country, market, store_number, store_name, store_type, store_address, currency, delivery_surcharge, delivery_fee, min_delivery_order, min_collection_order, max_cash_order, has_published_charges, note, source_url, scraped_at.

Behaviors an agent should know:

• An empty markets array means all 18 markets — bound cost by selecting only the markets you need.
• maxItems (default 0 = unlimited) caps output store rows but does not reduce upstream requests; the full directory of each selected market is fetched first.
• The separate additionalCharges dataset is written by default (includeAdditionalCharges: true) and is billed per row.
• includeClosedStores defaults to true; forceRefresh (default false) forces a fresh fetch instead of the 6-hour cache.
• A market that does not publish a field returns null, not false.
• Billing: pay-per-event — each result store is $0.0035, each additional_charges row is $0.001, plus a symbolic $0.00005 Actor-start event.

Legal & Compliance Disclaimer

This is an independent Actor. It is not affiliated with, endorsed by, or sponsored by Pizza Hut. It accesses only publicly available Pizza Hut store-locator APIs, XML feeds and server-rendered store pages — no login is required, no CAPTCHA solving is performed, and no access controls are used. Note that Pizza Hut's US Terms of Use limit use of its Services to personal, noncommercial purposes and restrict copying and distribution. Users are responsible for complying with Pizza Hut's terms of service, applicable data-protection law and the Apify platform rules when using or redistributing the data; this Actor is intended for legitimate research and automation use cases.

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