H&M Store Locator Scraper
Pricing
from $7.00 / 1,000 results
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H&M Store Locator Scraper
Scrape H&M store locations by country with normalized retail-location fields, store names, addresses, postal codes, opening hours, and source metadata.
Pricing
from $7.00 / 1,000 results
Rating
0.0
(0)
Developer
scraping automation
Maintained by CommunityActor stats
1
Bookmarked
11
Total users
1
Monthly active users
6 days ago
Last modified
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Extract H&M store locations by country with normalized retail-location fields and source evidence.
Who this is for
- Retail analysts
- Location intelligence teams
- Competitor monitoring teams
What it helps you do
- Collect H&M store locations
- Build store footprint datasets
- Compare addresses, opening hours, and postal codes
Inputs you can use
- Country
- Maximum stores
- Optional custom start URLs
Data you get
- store name
- address
- city
- region
- postal code
- country
- opening hours
- phone
- coordinates
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.
