Approx. US locations
~16,900
US stores (company-operated and licensed), per Starbucks Corporation Q3 fiscal 2026 results, as of the end of Q3 fiscal 2026
Panel refresh
Daily
Signal type
Dwell-confirmed visits
How GSDSI covers Starbucks
GSDSI's privacy-safe mobility panel captures dwell-confirmed visits to Starbucks cafés across urban, suburban, drive-thru, and airport-concourse formats. The POI catalog resolves stores to polygons with category and brand metadata, and the daily refresh cadence lets analysts track week-over-week and year-over-year visitation shape: the reads CPG brand teams, equity analysts, and CRE investors already expect from a production mobility panel.
Typical use cases
- Sell-side equity analysts sanity-checking Starbucks visitation before SBUX earnings
- Competitive benchmarking vs. Dunkin, Dutch Bros, and third-wave independents
- CRE site-selection teams evaluating trade-area overlap for new real-estate acquisitions
- CPG partnership teams modeling in-store promotion reach against footfall
Underlying GSDSI products and research
Location & Mobility Data Feed: Foot Traffic, O-D
Daily location and mobility data with a US and Canada feed and country-specific coverage. Origin-destination flows, dwell and visit attribution, consent-based.
Enterprise POI Polygons & Geofencing Data Feed
Global POI inventory and geofence-ready polygons for foot-traffic and site selection. Deduped, polygon-quality validated, refreshed on a per-dataset schedule.
Competitive Benchmarking Data (Foot Traffic)
Foot traffic, market share, and transaction trends across retail, CPG, and restaurant categories. Track share-of-visit vs. competitors with daily-fresh data.
Alternative Data for Finance (Tickerized Signals)
Tickerized consumer signals for fundamental research and quant strategies. Foot-traffic, card, web-intent, and ACR mapped to public equity tickers. Quant-ready.
Geofencing Best Practices: Polygons vs. Radius
Why radius geofences over- and under-count store visits, and how polygon geofences fix it, including sample SQL patterns, tuning notes, and POI quality checks.
How CRE Investors Use Origin-Destination Data
Worked examples of how origin-destination mobility data sharpens site-selection underwriting, tenant-mix planning, and lease-negotiation decisions in CRE.