Shopping Centers

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The Market Leader in North American Retail Real Estate Intelligence

For over two decades, Competitive Analytics Professionals (CAP) has been the go-to source for the most comprehensive and accurate shopping center data in the U.S. and Canada. With over 46,000 shopping centers, more than 5.69 billion square feet of gross leasable area (GLA), and 1.25 million actively tracked tenants, CAP Shopping Centers is the definitive dataset for understanding and navigating the retail real estate landscape.

Our data powers solutions for a wide range of clients including Fortune 500 retailers, QSR and full-service restaurant chains, national real estate developers, investment firms, REITs, location intelligence platforms, and logistics companies. CAP’s deep, structured data and precision mapping are trusted to guide decisions around site selection, competitive analysis, portfolio strategy, marketing intelligence, and supply chain optimization.

Precision That Sets the Industry Standard

At CAP, data accuracy is not an option—it’s our foundation. We leverage a proprietary multi-stage geocoding approach that combines multiple geospatial providers with a layer of manual rooftop verification. Over 90% of our geocodes are human-reviewed, ensuring rooftop-level precision critical for applications in GIS, mobile analytics, and trade area modeling.

Beyond coordinates, each shopping center record includes up to 42 detailed attributes, including center type, square footage, tenant lists, leasing status, anchor identification, and ownership structure. This level of detail makes CAP a versatile resource for organizations requiring granular control and consistency in their retail datasets.

Features

Explore the key features for the CAP Shopping Centers Dataset

Continuous Updating

With thousands of sources being tracked our datasets are constantly updated, giving our API subscribers the most current view of the Shopping Center market.

Multi-Staged Geocoding

Our proprietary multi-provider multi-staged geocoding system coupled with human verifications ensures verified rooftop geocode accuracy. More than 90% of our geocodes are manually reviewed and adjusted.

STATE-OF-THE-ART Processing

Built from the ground up! From Proprietary Address Parsing to ML Record Deduplication algorithms, our dedicated QA Team has all the right tools to produce and validate the most accurate Shopping Center Dataset on the market.

Quick Facts

46,587

Total number of shopping centers

45,863

Total number of Geofences

1.25M

Total number of tenants

42

Total number of available attributes

Column Name	Data Type	Length	Can be null	Description	Definition
PropertyID	INT <PRIMARY KEY>		N	CAP Unique Property Identifier	The primary key of the Shopping Center File. The propertyID is unique and indicates the id of the shopping center.
PropertyName	VARCHAR	200	N	Name of Shopping Center	The Shopping Center Name or the Market Name.
PropertyURL	VARCHAR	200	Y	Web Address for Shopping Center	Web Site URL
DeveloperID	INT		Y	CAP Developer Identifier	CAP's Unique Identifier for individual developers of the property
DeveloperName	VARCHAR	200	Y	Name of Shopping Center Developer	Property Developer that either built or has taken ownership of the property
CAP_CategoryID	INT		N	Shopping Center Classification Identifier	CAP's Unique Classification Identifier (See attached worksheet: CAP_Master_Classification.xlsx)
CAP_ClassName	VARCHAR	200	N	Shopping Center Classification Name	Designates the Shopping Center Type. The CAP_ClassName attribute is linked with the CAP_CategoryID attribute. (See attached worksheet: CAP_Master_Classification.xlsx)
Year_Opened	VARCHAR	100	Y	Shopping Center Year Opened	The Year the shopping center was originally opened
Year_Remodeled	VARCHAR	100	Y	Year Shopping Center was Remodeled	The last year the center was remodeled
GLA	INT		N	Shopping Center’s GLA	Total Gross Leasable Area (measured in square footage)
GLA_Source	VARCHAR	2	N	GLA Source ‐ The Source where GLA was derived	A=Actual (from developer) E=Estimated (by CAP) X=SC Class Average N=NULL
Parking_Count	INT		N	Number of Parking Spots	Total parking count of Shopping Center
Parking_Source	VARCHAR	2	N	The source where Parking Count was derived	A=Actual (from developer) E=Estimated (byCAP) X=SC Class Average N=NULL
Unit_Count	INT		N	Number of Tenant Units	Total number of tenants within the center
Units_Source	VARCHAR	2	N	The source where Tenant Units was derived	A=Actual (from developer) E=Estimated (byCAP) X=SC Class Average N=NULL
Address1	VARCHAR	200	N	Shopping Center Address	The street address of the Shopping Center
City	VARCHAR	200	N	City	City
StateProvince	VARCHAR	2	N	US State or Canadian Province Abbreviation	US State or Canadian Province Abbreviation (see attached State Province Lookup Table)
StateProvince_Code	INT		N	US State Code \ Canadian Province Code	US State Code \ Canadian Province Code (see attached State Province Lookup Table)
ZipPostal_Code	VARCHAR	6	Y	Zip or Postal Code	US ZIP Code or Canadian Postal Code
Zip4	VARCHAR	4	Y	Zip4	ZIP Code Extension
Country	VARCHAR	100	N	Country	Country (see attached State Province Lookup Table)
PhoneNumber	VARCHAR	15	Y	Phone Number	Phone Number
FaxNumber	VARCHAR	15	Y	Fax Number	Fax Number
Latitude	DOUBLE		Y	Geocode Latitude	Geocode Latitude
Longitude	DOUBLE		Y	Geocode Longitude	Geocode Longitude
GeocodeLevelID	INT		N	Geocode Level ID	The unique identifier for the level of geocoding. (see attached Geocode Level Lookup Table)
GeocodeLevel	VARCHAR	100	N	Geocode Level	The level/quality at which geocoding was performed. (see attached Geocode Level Lookup Table)
BG	VARCHAR	15	Y	Census Block Group	A census block group is a geographical unit used by the United States Census Bureau
County_Code	INT		Y	County Code	The FIPS county code is a five-digit Federal Information Processing Standard (FIPS) code (FIPS 6-4) which uniquely identifies counties and county equivalents in the United States
County_Name	VARCHAR	100	Y	County Name	Actual Name of County
DMA_Code	INT		Y	DMA Code	Designated Market Area Code - market is a region where the population can receive the same (or similar) television and radio station offerings, and may also include other types of media including newspapers and Internet content
DMA_Name	VARCHAR	100	Y	DMA Name	Designated Market Area Name
CBSA_Code	INT		Y	CBSA Code	Core Based Statistical Area is the official term for a functional region based around an urban center of at least 10,000 people
CBSA_Name	VARCHAR	100	Y	CBSA Name	Core Based Statistical Area Name
Linked_Unit_Count	INT		N	Linked Unit Count	The number of records that were matched to CAP’s Retail and Restaurant files as tenants or anchors of the Shopping Center.

Column Name	Data Type	Length	Can be null	Definition
PropertyID	INT		N	The unique identifier of the Shopping Center (primary key of the Shopping Center File).
LocationID	INT		Y	CAP’s Unique Location Identifier used in CAP Retail and in CAP Restaurants.
TradeNameID	INT		Y	CAP’s Unique Trade Name Identifier
TradeName	VARCHAR	200	N	Trade Name \ Brand Name of the store
CompanyID	INT		Y	CAP’s Unique Company Identifier.
CompanyName	VARCHAR	200	Y	The Company Name that owns the store
ParentCompanyName	VARCHAR	200	Y	The Parent Company that owns the store
CAP_CategoryID	INT		Y	CAP’s Unique Store Classification ID. (See attached CAP Master Classification Table)
CAP_CategoryName	VARCHAR	200	Y	CAP’s Unique Store Classification Name. (See attached CAP Master Classification Table)
CAP_ClassName	VARCHAR	200	Y	CAP’s Unique Store Sub-Classification Name. (See attached CAP Master Classification Table)
SQFT	INT		Y	The store’s total square footage.
PhoneNumber	VARCHAR	15	Y	Store’s phone number

Shopping Center ID	TYPE OF SHOPPING CENTER	CONCEPT	SQUARE FEET (INCLUDING ANCHORS)
1	Super-Regional Center	Similar to regional center but has more variety and assortment	800,000+
2	Region Center	General merchandise; fashion (mall, typically enclosed)	400,000-800,000
3	Outlet Center	Manufacturers' outlet stores	50,000-400,000
4	Power Center	Category-dominant anchors; few small tenants	250,000-600,000
5	Lifestyle Center	Upscale national chain specialty stores; dining and entertainment in outdoor setting.	Typically 150,000-500,000 but can be smaller or larger
6	Community Center	General merchandise; convenience	100,000-350,000
7	Neighborhood Center	Grocery Anchored	30,000-150,000
9	Mixed Use	Mix of commercial office space and retail and service	10,000-150,000 but can be smaller or larger
13	Strip / Convenience	Convenience, restaurant, general merchandise and services	5,000-50,000 but can be smaller or larger
25	Festival / Entertainment	Leisure; tourist-oriented; retail and service	80,000-250,000
26	Airport	Mix of retail and restaurants located in airport terminals	5,000-100,000 depending of airport size

Hand Drawn

CAP Geofences are crafted with precision, utilizing a meticulous, hand-drawn process that ensures the utmost accuracy. Unlike many data providers that rely solely on automated, machine-drawn polygons limited to building footprints, CAP takes a more comprehensive and thoughtful approach. We understand that a shopping center is not just the structure or building itself but encompasses the entire ecosystem, including parking lots, outparcels, and any additional surrounding structures. This holistic perspective ensures that our geofences accurately represent the true footprint of a shopping center, delivering meaningful insights for our clients.

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