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ScrapingBuddy
McDonald's Big Mac product imagery from the official menu
All use cases

RESTAURANT INTELLIGENCE / MANAGED DATA

McDonald's
menu data.

Understand the menu one restaurant at a time.

We collect McDonald's menu items, categories, sizes and restaurant-level prices. Structured observations for competitive pricing, assortment and location research.

Discuss your project Explore data points

FROM MENU DETAIL TO MARKET INSIGHT

Build a local view of a familiar menu.

A national menu does not tell you what each restaurant charges. ScrapingBuddy connects product and meal observations to the location, channel and time behind the price.

01

Compare local price positioning

Research the same product or meal across your target restaurants, with location and collection time retained.

02

Separate meals from items

Keep individual products, meal offers and size options distinct before calculating pricing differences.

03

Monitor menu changes

Follow observed assortment and category changes across locations without assuming a single national range.

WHAT WE COLLECT

The menu, the price and the place.

Choose the McDonald's data points your research needs. Each observation retains its source and location context; the final fields are agreed around your workflow.

01

Product identity

Brand, menu item and source product identifiers, kept together for repeat observations.

View field names
  • brand_name
  • item_id
  • item_name
02

Menu categories

Published category paths that keep the menu organized. The available depth depends on the source.

View field names
  • category
  • subcategory
03

Sizes & formats

Original size labels and format context, so distinct portions and offers stay separate.

View field names
  • size_label
04

Local menu prices

Observed product prices associated with their restaurant and size, rather than an assumed national price.

View field names
  • price
05

Restaurant locations

Store identifiers, addresses and geographic coordinates for location-level comparison and mapping.

View field names
  • store_id
  • store_number
  • address
  • city
  • state
  • postal_code
  • country
  • latitude
  • longitude
06

Channel & observation time

Ordering channel and collection time, retained so repeated observations can be interpreted correctly.

View field names
  • channel
  • observed_at

Representative delivery field names, not a fixed API response. Availability varies by source, location and collection scope.

Define your schema

CONTEXT IS PART OF THE DATA

Make like-for-like comparisons.

An individual item and a meal are different offers. Keep their product identity, size, restaurant and ordering channel together before comparing prices.

Preserve product distinctions
A size, preparation or meal format can change the offer. We preserve original names and labels before agreeing any cross-product mapping.
Keep location and channel attached
A local menu price is not a national price. Direct ordering and delivery-platform observations stay distinguishable.
Separate observation from inference
Missing items are not automatically discontinued. Collection time, source availability and validation results determine how to interpret a change.

BUILT AROUND YOUR RESEARCH BRIEF

From target locations
to a maintained feed.

We handle the source-specific collection and prepare data for your workflow. Scope, validation and delivery come before a scale commitment.

  1. 01 / DEFINE

    Choose your market

    Agree brands, locations, fields and refresh frequency. Define the ordering channel, market and any collection-window requirements.

  2. 02 / VALIDATE

    Review the data together

    Check representative records, price context, identifiers and missing fields. Agree matching rules and how collection issues are reported.

  3. 03 / DELIVER

    Connect your pipeline

    Receive an agreed CSV, JSON or Parquet feed, or a scoped API integration, with monitoring and maintenance defined for the project.

Need content from a few public pages?

Our self-service Scraping API collects accessible public content with optional AI analysis. It does not bypass CAPTCHA or login, or automatically return these restaurant datasets.

Explore Scraping API

BEFORE YOU BUILD ON THE DATA

The details that
shape your feed.

Can the feed show a single national price?

We collect restaurant-level observations. A national summary can be calculated from an agreed store sample, but should not be presented as a price charged by every restaurant.

Are direct and DoorDash prices interchangeable?

No. We retain the ordering channel. A cross-channel comparison needs matched locations and equivalent products; delivery fees, promotions and cart totals are separate from menu prices.

Do displayed prices include taxes, delivery fees and promotions?

Not necessarily. We preserve the observed menu price and its location and channel. Taxes, service fees, delivery fees, coupons and checkout totals are different fields and require a separately agreed scope. Currency and price units are confirmed in the delivery schema.

How are refresh frequency and project pricing decided?

We scope the brands, markets, locations, data streams and collection frequency together. After validating a sample, we agree the schema, delivery method and recurring price. A wider store set or more frequent collection changes the work involved.

What happens when a collection fails or a field disappears?

We agree freshness and completeness checks for the feed. Failed or incomplete collection is reported separately from a genuine menu change. Missing values are not silently turned into zero prices, closed restaurants or discontinued products.

Can the feed connect to our existing data pipeline?

Yes. We can scope CSV, JSON or Parquet delivery, or a project-specific API integration. We agree field names, identifiers, timestamp conventions and missing-value handling before delivery. This managed dataset is separate from the self-service Scraping API.

EXTEND YOUR RESTAURANT RESEARCH

YOUR MARKET. YOUR DATA REQUIREMENTS.

Build your
McDonald's
data feed.

Share the brands, locations and fields you need. We will review access and scope a sample before agreeing delivery.

  • Brands, locations and ordering channels
  • Menu, price and other required fields
  • Refresh schedule and delivery format
Talk through your project

Up to 5,000 characters.

Projects are accepted individually, subject to feasibility and available capacity. An enquiry does not reserve a solution or confirm delivery. Pricing and terms are agreed directly with our team.

A real person reviews your brief and follows up about scope and delivery.

ScrapingBuddy is an independent data service, not affiliated with or endorsed by McDonald's. Access, coverage and delivery commitments are agreed per project.

Product imagery: McDonald's official website. Imagery does not represent a collected record.