Starbucks Store Locator Scraper

Extract Starbucks store locations from the public store locator with normalized retail-location fields.

Who this is for

• Retail analysts
• Location intelligence teams
• Competitor monitoring teams

What it helps you do

• Collect Starbucks locations by place or search area
• Build store footprint datasets
• Compare addresses, coordinates, amenities, and opening hours

Inputs you can use

• Search place or coordinates
• Maximum stores

Data you get

• store name
• address
• city
• region
• postal code
• country
• coordinates
• opening hours
• amenities

How to get better results

• Start with a narrow, specific query or a small list of source URLs.
• Use realistic limits for the first run, then increase the volume once the output looks right.
• Keep source URLs, dates, and location context when you need repeatable market monitoring.
• Review a few sample records before connecting the dataset to a larger workflow.

Notes

• Results depend on what the public source exposes at run time.
• Some pages may hide, delay, rename, or remove fields, so individual records can have partial data.
• Use the built-in output table to inspect results before exporting to spreadsheets, dashboards, or automation tools.

Support

If a run returns unexpected data, open an issue from the Actor page with the input used, the run ID, and the result you expected.