Retail Site Selection & Location Planning
Expansion, real estate and network-planning teams use ComFinData geospatial datasets to score candidate sites on observed foot traffic, competitive density and trade-area demographics — before signing a ten-year lease on a hunch.
A lease is a decade-long forecast
Site selection is one of the few decisions in retail that can't be iterated: once signed, a bad location loses money for years. Yet many expansion decisions still rest on drive-bys, broker narratives and census tables that describe residents but not visitors.
The risk isn't a lack of instinct — it's that instinct can't see foot-traffic patterns, competitor saturation or how a candidate site's trade area overlaps the existing network.
The location data stack for network planners
ComFinData's geospatial catalog assembles the site-selection evidence base: mobile location signals for observed foot traffic and trade-area mapping, global POI data for competitive and complementary density, retail store location databases for network and tenant-mix analysis, postal-code boundaries for clean catchment geometry, and consumer demographics to profile who actually lives and shops in the catchment.
All layers are GIS-ready and schema-documented, so they drop into the mapping stack planners already use.
Scoring a pipeline of candidate sites
A typical workflow: define trade areas around each candidate with boundary and drive-time geometry, score them on foot traffic, demographic fit and competitive gap, then rank the pipeline and model cannibalization against existing stores.
The same layers keep working after opening day — monitoring trade-area shifts and validating the model against actual store performance.
Key applications
- Candidate site scoring with observed foot traffic
- Trade-area definition and catchment demographics
- Competitive density and white-space mapping
- Franchise territory design and expansion sequencing
- Cannibalization analysis across the existing network
Datasets for Retail Site Selection & Location Planning
Retail Store Location Database
Complete database of 5M+ retail store locations across 40+ countries with brand, category, hours, and contact information.
Mobile Device Location Signals
Privacy-compliant mobile device location signals with foot traffic patterns, dwell times, and visit frequency for 1M+ venues.
Commercial Real Estate Listings
Active and historical commercial property listings with asking prices, cap rates, square footage, and zoning information.
Global Points of Interest (POI) Data
15M+ points of interest worldwide including restaurants, hotels, shops, and landmarks with precise coordinates and categories.
Global Postal Code Boundaries
Complete postal/ZIP code boundary polygons for 60+ countries with demographic overlays and administrative hierarchies.
US Consumer Demographic Profiles
Detailed demographic profiles for 250M+ US consumers with age, gender, income brackets, and purchasing preferences.
Frequently asked questions
Do these datasets work in ArcGIS or QGIS?
Yes — boundary, POI and location datasets are delivered in GIS-friendly formats with standard geographic identifiers, and CSV/Parquet delivery loads directly into spatial databases. The schema on each product page lists the geometry and join keys.
Can I get foot-traffic history for sites I'm evaluating now?
Yes — location-signal datasets include historical windows, so a candidate site's traffic pattern (including seasonality) can be studied before you commit. Scope the lookback and geography on the discovery call.
Can't find the exact data you need for Retail Site Selection & Location Planning?
Tell us what you're looking for — coverage, attributes, cadence — and we'll scope it with you on a short discovery call.
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