23 September New ACS Median Income Endpoints for the Zip Code API September 23, 2026 By Ricardo Rangel Developer Solutions, Product Notifications ACS median income API, median household income by ZIP code Introducing a simpler way to access current and historical median household income data by ZIP Code. Understanding the economic characteristics of a geographic area is essential for market research, customer segmentation, site selection, real estate analysis, and many other location-based applications. To make this type of information easier to use, the Metadapi Zip Code API now includes two new endpoints for accessing American Community Survey (ACS) median household income data for ZIP Code Tabulation Areas (ZCTAs). The new endpoints are: /zipc/v2/zipcodes/{zipcode}/acs/income — returns the latest available ACS median household income estimate for a ZIP Code, with the option to request a specific release year. /zipc/v2/zipcodes/{zipcode}/acs/income/history — returns the available historical ACS median household income estimates for the ZIP Code. The Zip Code API already combines ZIP Code information from authoritative sources including USPS, the U.S. Census Bureau, ANSI geographic standards, and IRS statistical data. These new ACS endpoints add another useful layer of socioeconomic information to that geographic data. What Is ACS Median Household Income? The American Community Survey (ACS) is a U.S. Census Bureau survey that produces demographic, social, economic, and housing statistics for communities across the United States. For the new Zip Code API endpoints, the income measure comes from ACS 5-Year Estimates, Table B19013. The API uses the ACS 5-year estimate for median household income at the ZIP Code Tabulation Area (ZCTA) level. The API documentation specifies the 5-year dataset because it provides coverage across ZCTAs rather than being limited to larger areas. Median household income is different from average or mean household income. The median is the middle value when household incomes are ordered from lowest to highest. In practical terms, approximately half of households have income below the median and approximately half have income above it. This makes median income a useful way to describe the typical income level of households in an area without allowing a small number of extremely high incomes to pull the result upward as strongly as an average can. The API returns the median household income as a dollar amount and also provides statistical information that helps developers understand the precision and reliability of the estimate. What the New Income Endpoint Returns The single-year endpoint /zipc/v2/zipcodes/{zipcode}/acs/income is designed for applications that need the current or a specific ACS income estimate for one ZIP Code. For example: GET /zipc/v2/zipcodes/33967/acs/income By default, the endpoint returns the most recent release available for that ZIP Code. A specific ACS release year can also be requested using the year parameter. The documentation indicates that the requested year must be one of the years listed in meta.availableReleaseYears. A typical response includes fields such as: zipCode — the five-digit ZIP Code. acsReleaseYear — the ACS release year for the estimate. estimateType — the API uses the ACS 5-Year estimate. medianHouseholdIncome — the median household income in whole dollars. marginOfError — the Census Bureau's 90 percent margin of error. relativeMarginOfError — the margin of error expressed as a percentage of the estimate. confidenceInterval — the 90 percent confidence interval around the estimate. reliability — a high, medium, or low reliability classification. zctaVintage — identifies the Census boundary generation used for the ZCTA. This additional statistical context is important. An income value should not always be treated as an exact measurement. The margin of error, confidence interval, and reliability fields allow an application to understand how much uncertainty is associated with the published estimate. Why the Margin of Error Matters ACS estimates are based on survey data, so they contain statistical uncertainty. Two ZIP Codes might have different published median incomes while the difference between those estimates is small relative to their margins of error. The new endpoint exposes the marginOfError and relativeMarginOfError instead of requiring developers to obtain and interpret those values separately. The API also provides a 90 percent confidence interval. For example, the documentation's sample for ZIP Code 90210 reports a median household income of $187,801, a margin of error of $18,411, and a 90 percent confidence interval from $169,390 to $206,212. The API's reliability classification is derived from the coefficient of variation. The documentation describes high reliability as a coefficient of variation below 15 percent, medium as 15 percent to under 30 percent, and low as 30 percent or more. This gives applications a practical way to incorporate data quality into downstream analysis. Handling ZIP Codes Without an Estimate Not every ZIP Code has a published ACS income estimate for every release. The API documentation notes that roughly 10 percent of ZIP Codes have no estimate in the current release because the Census Bureau suppresses figures for areas with insufficient sample size. Importantly, the income endpoint handles this situation as a valid response rather than treating it as an API failure. The request returns 200 OK with dataAvailable: false and a reason explaining why an estimate is unavailable. A 404 indicates that the ZIP Code itself does not exist. This distinction can make application development easier because a missing statistical estimate can be handled separately from an invalid or nonexistent ZIP Code. Explore Income Trends with the History Endpoint The second new endpoint, /zipc/v2/zipcodes/{zipcode}/acs/income/history, is designed for applications that need more than the latest number. GET /zipc/v2/zipcodes/33967/acs/income/history The history endpoint returns the available release years for the ZIP Code. The API documentation currently provides historical releases back to 2011 for the example data, while also exposing the actual available years in meta.availableReleaseYears. Applications should use that field rather than assuming that every ZIP Code has the same range of historical data. The history response also includes comparability guidance. ACS releases are expressed in their own year's dollars, so values from different release years should be adjusted for inflation before making monetary trend comparisons. The documentation also notes that Census top-code thresholds can change between releases and that ZCTA boundaries were redrawn for the 2020 Census. These details are especially important when building charts, trend models, rankings, or year-over-year comparisons. Historical data is valuable, but it should be interpreted with the statistical and geographic context supplied by the API. This history endpoint is available on the Basic and Professional tiers of the API. Use Cases for ACS Median Income by ZIP Code 1. Location-Based Marketing Marketing platforms can use median household income to add economic context to geographic targeting. For example, a campaign can segment ZIP Codes according to income ranges and combine those segments with existing geographic or demographic criteria. This can be useful for local advertising, direct mail, retail promotions, service-area campaigns, and audience analysis. 2. Customer and Market Segmentation Businesses can enrich customer or prospect records with ZIP Code-level income information. A company could use the data as one variable in a broader segmentation model, alongside geography, population, household characteristics, or other business data. 3. Retail Site Selection Companies evaluating potential retail locations can use median household income as one indicator of the economic characteristics of surrounding ZIP Codes. When combined with population, distance, MSA, and other geographic data, income can help create a more complete picture of a potential market. 4. Real Estate Market Analysis Real estate applications can use ZIP Code income data to add socioeconomic context to property and market datasets. Historical ACS income data can also be incorporated into market research where analysts need to understand how an area's reported income levels have changed over time. 5. Territory and Service-Area Planning Businesses that operate across geographic territories can combine income information with ZIP Code radius and distance data. For example, an organization could identify ZIP Codes within a service area and then examine the income characteristics of those areas. 6. Financial and Insurance Market Analysis Financial services, insurance, and other businesses can use ZIP Code-level income as one geographic variable in market research and portfolio analysis. The data can help identify differences in the economic characteristics of markets without requiring household-level income information. 7. Geographic Data Enrichment Developers can use the endpoint to enrich existing datasets that contain ZIP Codes. Instead of maintaining a separate ACS lookup process, an application can retrieve the income estimate and its statistical metadata through the same API architecture used for other ZIP Code data. Build More Useful ZIP Code Profiles Median household income becomes especially useful when it is combined with other geographic attributes. The Zip Code API already provides capabilities such as ZIP Code details, distance calculations, radius searches, MSA information, and IRS Statistics of Income data. This makes it possible to build richer geographic profiles. For example, an application could identify ZIP Codes within a defined radius, retrieve their geographic information, and then add ACS median household income to each ZIP Code. A market analysis application could then use those attributes together rather than relying on a single data point. ACS Income Data in an API-Friendly Format One of the goals of the new endpoints is to make Census income information practical for software applications. Instead of downloading a large dataset and building a custom lookup process, developers can request income information for a specific ZIP Code and receive a structured JSON response. The response also includes metadata describing the release years, source dataset, estimate availability, statistical uncertainty, and reliability. This gives developers more information than simply returning a single income number. Current and Historical Income Data in One API The two new endpoints serve complementary purposes: Use /acs/income when an application needs the latest available median household income, or a specific ACS release year. Use /acs/income/history when an application needs the available historical series for a ZIP Code. Together, they provide a straightforward way to add ACS median household income to ZIP Code-based applications while preserving important information about the estimate's uncertainty, reliability, release year, and geographic vintage. Start Using the New ACS Income Endpoints If your application already works with the Metadapi Zip Code API, the new endpoints provide an additional way to enrich ZIP Code data with Census ACS income information. You can start using the endpint right awa. Visit the Metadapi Zip Code API product page to learn more about the API, available plans, and access to the documentation. The ACS income data is sourced from the U.S. Census Bureau American Community Survey 5-Year Estimates, Table B19013. The API documentation identifies the Census Bureau as the provider and exposes the source information in the response metadata. Related Posts The Power of Zip Code Statistics: Leveraging IRS Data for Targeted Market Analysis This blog post introduces the immense potential of zip code statistics for business analysis, highlighting how leveraging IRS data through an API can enable smarter, targeted marketing decisions. MSA Codes by Zip Code for Targeted Data Insights In the dynamic landscape of data analysis, harnessing the power of Micro Statistical Area (MSA) codes linked to zip codes opens a myriad of possibilities for insightful exploration. From market research and demographic profiling to targeted marketing strategies, this unique correlation facilitates precision in data analysis. This article delves into the expansive realm of MSA by zip code, shedding light on its diverse applications and how businesses and researchers alike can leverage this invaluable data set for strategic advantage. Famous ZIP Codes in the United States: What a ZIP Code Is and Why It Exists Learn what a ZIP Code is, why ZIP Codes were created, and discover the most famous ZIP Code in every U.S. state—from Beverly Hills 90210 to Manhattan 10001. Unlocking Local Insights: Income by Zip Code This blog article explores the value of analyzing income by ZIP code for marketers, real estate professionals, and analysts. It outlines how localized income data can drive smarter decisions in targeting, expansion, and performance benchmarking. The post also features a sample Python script that takes a ZIP code, radius, and income threshold as inputs, then identifies nearby ZIP codes with higher-than-threshold average incomes using IRS data. Practical use cases and ideas for extending the script are included to help teams turn raw data into strategic insights. Getting Income Statistics by Zip Code Understanding the income statistics of specific areas can be incredibly valuable for businesses, researchers, and policymakers. In this blog post, we'll explore how to obtain income statistics by zip code using the Zip Code API, highlight some sample use cases, and delve into one detailed use case to illustrate its practical application. Mapping IRS 1040 Tax Data with the Zip Code API: A Complete Guide Understanding how income and demographic data align across geographic regions is key to building smarter insights — and that’s exactly what the Zip Code API delivers. In this guide, we explain how the API connects directly to publicly available IRS 1040 tax return data, providing a clear mapping between individual return fields and zip code–level metrics Please enable JavaScript to view the comments powered by Disqus. blog comments powered by Disqus
Introducing a simpler way to access current and historical median household income data by ZIP Code. Understanding the economic characteristics of a geographic area is essential for market research, customer segmentation, site selection, real estate analysis, and many other location-based applications. To make this type of information easier to use, the Metadapi Zip Code API now includes two new endpoints for accessing American Community Survey (ACS) median household income data for ZIP Code Tabulation Areas (ZCTAs). The new endpoints are: /zipc/v2/zipcodes/{zipcode}/acs/income — returns the latest available ACS median household income estimate for a ZIP Code, with the option to request a specific release year. /zipc/v2/zipcodes/{zipcode}/acs/income/history — returns the available historical ACS median household income estimates for the ZIP Code. The Zip Code API already combines ZIP Code information from authoritative sources including USPS, the U.S. Census Bureau, ANSI geographic standards, and IRS statistical data. These new ACS endpoints add another useful layer of socioeconomic information to that geographic data. What Is ACS Median Household Income? The American Community Survey (ACS) is a U.S. Census Bureau survey that produces demographic, social, economic, and housing statistics for communities across the United States. For the new Zip Code API endpoints, the income measure comes from ACS 5-Year Estimates, Table B19013. The API uses the ACS 5-year estimate for median household income at the ZIP Code Tabulation Area (ZCTA) level. The API documentation specifies the 5-year dataset because it provides coverage across ZCTAs rather than being limited to larger areas. Median household income is different from average or mean household income. The median is the middle value when household incomes are ordered from lowest to highest. In practical terms, approximately half of households have income below the median and approximately half have income above it. This makes median income a useful way to describe the typical income level of households in an area without allowing a small number of extremely high incomes to pull the result upward as strongly as an average can. The API returns the median household income as a dollar amount and also provides statistical information that helps developers understand the precision and reliability of the estimate. What the New Income Endpoint Returns The single-year endpoint /zipc/v2/zipcodes/{zipcode}/acs/income is designed for applications that need the current or a specific ACS income estimate for one ZIP Code. For example: GET /zipc/v2/zipcodes/33967/acs/income By default, the endpoint returns the most recent release available for that ZIP Code. A specific ACS release year can also be requested using the year parameter. The documentation indicates that the requested year must be one of the years listed in meta.availableReleaseYears. A typical response includes fields such as: zipCode — the five-digit ZIP Code. acsReleaseYear — the ACS release year for the estimate. estimateType — the API uses the ACS 5-Year estimate. medianHouseholdIncome — the median household income in whole dollars. marginOfError — the Census Bureau's 90 percent margin of error. relativeMarginOfError — the margin of error expressed as a percentage of the estimate. confidenceInterval — the 90 percent confidence interval around the estimate. reliability — a high, medium, or low reliability classification. zctaVintage — identifies the Census boundary generation used for the ZCTA. This additional statistical context is important. An income value should not always be treated as an exact measurement. The margin of error, confidence interval, and reliability fields allow an application to understand how much uncertainty is associated with the published estimate. Why the Margin of Error Matters ACS estimates are based on survey data, so they contain statistical uncertainty. Two ZIP Codes might have different published median incomes while the difference between those estimates is small relative to their margins of error. The new endpoint exposes the marginOfError and relativeMarginOfError instead of requiring developers to obtain and interpret those values separately. The API also provides a 90 percent confidence interval. For example, the documentation's sample for ZIP Code 90210 reports a median household income of $187,801, a margin of error of $18,411, and a 90 percent confidence interval from $169,390 to $206,212. The API's reliability classification is derived from the coefficient of variation. The documentation describes high reliability as a coefficient of variation below 15 percent, medium as 15 percent to under 30 percent, and low as 30 percent or more. This gives applications a practical way to incorporate data quality into downstream analysis. Handling ZIP Codes Without an Estimate Not every ZIP Code has a published ACS income estimate for every release. The API documentation notes that roughly 10 percent of ZIP Codes have no estimate in the current release because the Census Bureau suppresses figures for areas with insufficient sample size. Importantly, the income endpoint handles this situation as a valid response rather than treating it as an API failure. The request returns 200 OK with dataAvailable: false and a reason explaining why an estimate is unavailable. A 404 indicates that the ZIP Code itself does not exist. This distinction can make application development easier because a missing statistical estimate can be handled separately from an invalid or nonexistent ZIP Code. Explore Income Trends with the History Endpoint The second new endpoint, /zipc/v2/zipcodes/{zipcode}/acs/income/history, is designed for applications that need more than the latest number. GET /zipc/v2/zipcodes/33967/acs/income/history The history endpoint returns the available release years for the ZIP Code. The API documentation currently provides historical releases back to 2011 for the example data, while also exposing the actual available years in meta.availableReleaseYears. Applications should use that field rather than assuming that every ZIP Code has the same range of historical data. The history response also includes comparability guidance. ACS releases are expressed in their own year's dollars, so values from different release years should be adjusted for inflation before making monetary trend comparisons. The documentation also notes that Census top-code thresholds can change between releases and that ZCTA boundaries were redrawn for the 2020 Census. These details are especially important when building charts, trend models, rankings, or year-over-year comparisons. Historical data is valuable, but it should be interpreted with the statistical and geographic context supplied by the API. This history endpoint is available on the Basic and Professional tiers of the API. Use Cases for ACS Median Income by ZIP Code 1. Location-Based Marketing Marketing platforms can use median household income to add economic context to geographic targeting. For example, a campaign can segment ZIP Codes according to income ranges and combine those segments with existing geographic or demographic criteria. This can be useful for local advertising, direct mail, retail promotions, service-area campaigns, and audience analysis. 2. Customer and Market Segmentation Businesses can enrich customer or prospect records with ZIP Code-level income information. A company could use the data as one variable in a broader segmentation model, alongside geography, population, household characteristics, or other business data. 3. Retail Site Selection Companies evaluating potential retail locations can use median household income as one indicator of the economic characteristics of surrounding ZIP Codes. When combined with population, distance, MSA, and other geographic data, income can help create a more complete picture of a potential market. 4. Real Estate Market Analysis Real estate applications can use ZIP Code income data to add socioeconomic context to property and market datasets. Historical ACS income data can also be incorporated into market research where analysts need to understand how an area's reported income levels have changed over time. 5. Territory and Service-Area Planning Businesses that operate across geographic territories can combine income information with ZIP Code radius and distance data. For example, an organization could identify ZIP Codes within a service area and then examine the income characteristics of those areas. 6. Financial and Insurance Market Analysis Financial services, insurance, and other businesses can use ZIP Code-level income as one geographic variable in market research and portfolio analysis. The data can help identify differences in the economic characteristics of markets without requiring household-level income information. 7. Geographic Data Enrichment Developers can use the endpoint to enrich existing datasets that contain ZIP Codes. Instead of maintaining a separate ACS lookup process, an application can retrieve the income estimate and its statistical metadata through the same API architecture used for other ZIP Code data. Build More Useful ZIP Code Profiles Median household income becomes especially useful when it is combined with other geographic attributes. The Zip Code API already provides capabilities such as ZIP Code details, distance calculations, radius searches, MSA information, and IRS Statistics of Income data. This makes it possible to build richer geographic profiles. For example, an application could identify ZIP Codes within a defined radius, retrieve their geographic information, and then add ACS median household income to each ZIP Code. A market analysis application could then use those attributes together rather than relying on a single data point. ACS Income Data in an API-Friendly Format One of the goals of the new endpoints is to make Census income information practical for software applications. Instead of downloading a large dataset and building a custom lookup process, developers can request income information for a specific ZIP Code and receive a structured JSON response. The response also includes metadata describing the release years, source dataset, estimate availability, statistical uncertainty, and reliability. This gives developers more information than simply returning a single income number. Current and Historical Income Data in One API The two new endpoints serve complementary purposes: Use /acs/income when an application needs the latest available median household income, or a specific ACS release year. Use /acs/income/history when an application needs the available historical series for a ZIP Code. Together, they provide a straightforward way to add ACS median household income to ZIP Code-based applications while preserving important information about the estimate's uncertainty, reliability, release year, and geographic vintage. Start Using the New ACS Income Endpoints If your application already works with the Metadapi Zip Code API, the new endpoints provide an additional way to enrich ZIP Code data with Census ACS income information. You can start using the endpint right awa. Visit the Metadapi Zip Code API product page to learn more about the API, available plans, and access to the documentation. The ACS income data is sourced from the U.S. Census Bureau American Community Survey 5-Year Estimates, Table B19013. The API documentation identifies the Census Bureau as the provider and exposes the source information in the response metadata.