Retail Location Intelligence Bundle

Monitor store footprints, openings, closures, competitor locations, and local expansion signals in one structured retail intelligence workflow.

What it helps you do

• Track where a brand operates stores by city, country, or market
• Compare competitors' physical retail footprint
• Collect evidence for openings, closures, flagship stores, and local expansion
• Prepare location datasets for spreadsheets, dashboards, CRM enrichment, and AI analysis

Best for

• Retail strategy and expansion teams
• Real estate analysts
• Competitive intelligence teams
• Market research teams tracking store networks
• Automation workflows that need clean retail-location records

Example use case

Monitor Dior locations and competitor signals in Paris.

Start with a known store or a small market sample, then expand to competitor and web-discovery monitoring once the first dataset looks correct.

Inputs you can use

• Brand or competitor names
• City, country, and market
• Known store locations or source URLs
• Optional discovery keywords
• Maximum number of records to keep runs predictable

Data you get

• Brand and competitor name
• Store or location name
• Address, city, region, country, and postal code
• Phone, opening hours, and coordinates when available
• Source URL and canonical URL
• Summary of the signal
• Matched keywords
• Relevance and priority scores
• Review status for quality control
• Collection timestamp

Dataset views

• Locations: clean store and address records for mapping or spreadsheets
• Signals: scored expansion, competitor, and footprint records
• Evidence: source URLs, matched keywords, and review status

How to get better results

• Start with a specific brand and market instead of a broad worldwide query.
• Use known locations for the first run when you need a predictable sample.
• Add competitors after the base brand output has been checked.
• Keep result limits small for the first run, then increase volume gradually.
• Review source URLs and review status before using the data in reporting.

Limitations

Public store pages can move, return partial addresses, or hide metadata. Web discovery can also return pages that mention a brand without being an actual store page. Always review source URLs and status fields before relying on the dataset for business decisions.

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.