Documentation

This document provides details on the categories of data returned in the ZIP Code API.

zipcode

The 5-digit ZIP Code is the core identifier for each location in the database. It provides the primary means to request and integrate ZIP Code data into applications.

The ZIP Code format is standardized by the US Postal Service and provides a recognizable geographic shorthand for consumers and businesses alike. ZIP Codes identify delivery areas and can facilitate postal logistics. They also act as proxies for neighborhoods and sub-regions within a city.

Key use cases for ZIP Code data:

• Geocoding addresses and locations to a ZIP Code for spatial analysis
• Linking databases and records together by ZIP Code
• Segmenting and aggregating data for analysis and visualization by ZIP Code
• Targeting marketing campaigns, real estate analysis, or expansion efforts to specific ZIP Codes
• Modeling drive time trade areas for retail sites based on surrounding ZIP Codes

geographical

The geographical data provides precise coordinates and supplemental spatial attributes for mapping, location analysis, and geographic modeling.

Key attributes such as latitude/longitude, land area, and elevation allow ZIP Code boundaries, centroids, and terrain to be visualized on a map. This supports trade area analysis based on drive time or distance. Linkages to higher level geographies help roll up ZIP Codes for regional views.

Use cases for geographical data:

• Pinpointing ZIP Code locations on digital maps and dashboards
• Conducting drive time and distance calculations for retail trade areas
• Analyzing regional trends by rolling up ZIP Codes into CBSA, County, etc
• Modeling geography-based risks for insurance or credit purposes
• Planning optimal locations for new sites, offices, or facilities

population

Population metrics provide critical demographic intelligence for market segmentation, consumer profiling, and opportunity analysis.

Granular population breakdowns by age, gender, and race/ethnicity allow highly targeted marketing and product development. Trend analysis reveals shifting consumer demand. Comparison across ZIP Codes highlights geographic variances.

Use cases for population data:

• Sizing overall market potential for products and services
• Targeting campaigns to neighborhoods with desired age, income, and ethnicity
• Tailoring products and messaging to match diverse consumer segment preferences
• Comparing trends across ZIP Codes to optimize resource allocation
• Maximizing census participation with targeted community outreach

demographics

Key demographic attributes provide additional data for developing consumer personas andProto personas. Segmenting ZIP Codes by household size, age distribution, and life stage allows more relevant engagement.

Comparing median ages and household sizes across ZIP Codes reveals Youthful urbSuburban familyan neighborhoods versus mature suburban and rural areas with empty nesters. Age and household data inform product preferences.

Use cases for demographic data:

• Connecting age, household, and income data into rich consumer lifestyle profiles
• Quantifying market demand for products suited to different lifestages
• Clustering ZIP Codes into neighborhood segments for targeted campaigns
• Tailoring real estate development to match the housing needs of local demographics
• Forecasting future demand based on emerging demographic shifts

economic

Economic and business metrics provide vital intelligence on growth, spending, and workforce trends. These data help identify potential opportunities while quantifying market health.

Comparison of income, real estate values, and business statistics across ZIP Codes highlights economic disparities. Changes over time reveal growth areas. Labor force numbers quantify talent availability.

Use cases for economic data:

• Evaluating the relative affluence and consumer spending power of trading areas
• Estimating demand for products and services based on local economic conditions
• Identifying growing areas for potential expansion or investment
• Assessing real estate markets for new development or facilities
• Connecting talent availability to hiring and workforce planning

postal

Postal data gives intelligence on delivery logistics and marketing reach. Delivery statistics help plan optimal distribution and direct mail campaigns. PO Box and address counts provide mail market sizing.

This data integrates directly with USPS systems for address validation, presorts, and bulk mail planning. Flags denote mailing preferences and services for each ZIP Code.

Use cases for postal data:

• Building delivery-optimized mail lists and marketing campaigns
• Planning deadlines and logistics for package shipping
• Quantifying mail market size and opportunity
• Integrating with USPS validation, tracking, and folder-sequencer tools
• Designing the optimal facility footprint to serve surrounding ZIP Codes

statisticalarea

Statistical area codes link ZIP Codes to metropolitan and regional geos. This allows roll-ups for broader analysis and mapping.

Comparing trends across metros and regions reveals macro economic and population shifts. Statistical area delineations anchor ZIP Codes in a geographic hierarchy.

Use cases for statistical area data:

• Aggregating ZIP Codes into metros, divisions, and regions for macro analysis
• Adding geographic context and hierarchy to ZIP Code data
• Visualizing and analyzing broader geographic trends beyond the local ZIP Code
• Grouping metros and regions into territories for sales or market planning
• Modeling the effect of regional economic factors on local ZIP Codes

time

Time attributes provide temporal context on ZIP Code development and history. By denoting when ZIP Codes were established, time data anchors them to eras of growth and development.

Analysis of ZIP Code change over time can reveal demographic and economic shifts as neighborhoods evolve. The combination of date and location creates unique timestamps to study change.

Use cases for time data:

• Linking ZIP Code origin to historical development patterns
• Identifying when neighborhoods were established through ZIP Code introduction
• Modeling demographic change in maturing ZIP Codes over time
• Comparing new ZIP Code introduction across metros as a growth indicator
• Tagging other databases and records with contemporaneous ZIP Code attributes

specialty

These codes provide technical linkages across datasets along with flags for special cases. FIPS codes join ZIP data to federal information systems for integrated analysis.

Flags identify unique ZIP Codes, multiline geometries, and specific USPS services. This technical metadata enables advanced modeling and systems integration.

Use cases for specialty codes:

• Linking ZIP Code data to other federal datasets via FIPS identifiers
• Identifying complex ZIP Codes for special handling in analysis
• Integrating with USPS and other platforms using common identifiers
• Isolating ZIP Codes based on specific attributes like multiline status
• Tagging records for attention based on flags in later processing stages

medicare

Medicare geographic designations connect ZIP Codes to policy and planning systems. This enables analysis of healthcare access, outcomes, and services based on ZIP Code.

Medicare data integrates with CMS records for evaluation of treatments, costs, and populations served relative to location. ZIP Codes anchor the data to concrete communities.

Use cases for Medicare data:

• Linking CMS records to ZIP Codes for location-based healthcare analysis
• Planning public health outreach, clinics, and services based on local needs
• Assessing healthcare outcomes and costs by neighborhoods and demographics
• Modeling healthcare access and demand by geography to inform policy
• Optimizing provider networks and care facilities relative to populations served

congressional

Congressional districts and spatial boundaries provide political context and representation. ZIP Codes can be aggregated to analyze voting patterns, advocacy campaigns, and policy impacts by district.

Legislators utilize ZIP Code-level detail on their constituents to inform decisions and communications. Granular opinions and trends can be modeled across districts.

Use cases for congressional data:

• Connecting public opinion polling and survey results to legislative districts
• Advocating for policies relevant to specific ZIP Codes and communities
• Modeling election trends, donor contributions, and advertising by district
• Segmenting communications and outreach to congressional districts
• Analyzing policy impacts geographically based on local economic and population indicators