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⇱ Starbucks Scraper · Apify

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Starbucks Scraper

Starbucks Scraper. Structured data export for lead generation, enrichment, and competitive research.

Pricing

from $3.50 / 1,000 results

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0.0

(0)

Developer

👁 Fortuitous Pirate

Fortuitous Pirate

Maintained by Community

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6

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1

Monthly active users

a month ago

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Starbucks Store & Menu Scraper

Scrapes Starbucks store locations and menu items with prices and nutritional info.

API Source

Input Parameters

ParameterTypeDefaultDescription
modeenum"stores"What to scrape: "stores", "menu", or "both"
locationstring"Seattle, WA"City, ZIP code, or address for store search
radiusinteger10Search radius in miles (1-100)
menuCategoryenum""Menu category: "" (all), "drinks", "food", "at-home-coffee", "merchandise"
limitinteger50Maximum number of items to return (max 500)
proxyConfigurationobject{ useApifyProxy: true }Proxy settings

Example Input

{
"mode":"stores",
"location":"New York, NY",
"radius":5,
"limit":100
}
{
"mode":"menu",
"menuCategory":"drinks",
"limit":200
}
{
"mode":"both",
"location":"Los Angeles, CA",
"radius":10,
"menuCategory":"food",
"limit":50
}

Output

Store Output Fields

FieldTypeDescription
typestringAlways "store"
storeNumberstringUnique store identifier
namestringStore name
address.streetstringStreet address line 1
address.street2stringStreet address line 2
address.citystringCity
address.statestringState/province code
address.postalCodestringZIP/postal code
address.countrystringCountry code
coordinates.latnumberLatitude
coordinates.lngnumberLongitude
phonestringPhone number
hoursstring/objectOperating hours
featuresarrayStore features (e.g., Mobile Order, Drive Thru)
mobileOrderEnabledbooleanMobile ordering available
driveThrubooleanHas drive-thru
wifibooleanHas WiFi
distancenumberDistance from search location
scrapedAtstringISO timestamp of scrape

Example Store Output

{
"type":"store",
"storeNumber":"12345-67890",
"name":"Pike Place",
"address":{
"street":"1912 Pike Place",
"street2":null,
"city":"Seattle",
"state":"WA",
"postalCode":"98101",
"country":"US"
},
"coordinates":{
"lat":47.6097,
"lng":-122.3422
},
"phone":"(206) 448-8762",
"hours":"Open 24 Hours",
"features":["Mobile Order","WiFi","Drive Thru"],
"mobileOrderEnabled":true,
"driveThru":true,
"wifi":true,
"distance":0.5,
"scrapedAt":"2026-01-25T12:00:00.000Z"
}

Menu Item Output Fields

FieldTypeDescription
typestringAlways "menu_item"
namestringItem name
pricestringPrice (numeric value)
caloriesstringCalorie count
imagestringImage URL
urlstringProduct page URL
categorystringMenu category
scrapedAtstringISO timestamp of scrape

Example Menu Item Output

{
"type":"menu_item",
"name":"Caffe Latte",
"price":"5.45",
"calories":"190",
"image":"https://www.starbucks.com/weblx/images/products/caffe-latte.jpg",
"url":"https://www.starbucks.com/menu/product/407/hot",
"category":"drinks",
"scrapedAt":"2026-01-25T12:00:00.000Z"
}

Usage

Run on Apify

  1. Go to the actor page on Apify
  2. Configure input parameters
  3. Click "Run"
  4. Download results from the Dataset tab

Run Locally

# Install dependencies
npminstall
# Set input in storage/key_value_stores/default/INPUT.json
echo'{"mode": "stores", "location": "Seattle, WA"}'> storage/key_value_stores/default/INPUT.json
# Run
npm start

Tech Stack

  • Node.js 18+
  • Apify SDK 3.x
  • Crawlee 3.x
  • Playwright (for menu scraping)

Notes

  • Store locations use the Starbucks BFF API with geocoding via OpenStreetMap Nominatim
  • Menu scraping uses Playwright to render the React-based menu pages
  • Residential proxies recommended for reliable scraping
  • Rate limiting is built-in with random delays between requests

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