Data catalog

American Community Survey (5-year)

U.S. Census Bureau

Publisher site
population
statistic

In a RepVector build, this dataset sizes the addressable population behind a territory.

Sample of the actual data
1 rows captured for Los Angeles County, California on 2026-09-02. Showing the first 1.
CountyFIPSTotal populationMedian ageMedian household incomeMedian home value
Los Angeles County060379,848,40637.9$87,760$783,300

What this dataset is

Population, age, income, housing, employment and education estimates for every county, tract and ZIP-code tabulation area in the United States. The general-purpose baseline for understanding who lives in a place and what their economic circumstances are. It is published by U.S. Census Bureau and can be queried at county, tract, zcta and state level, refreshed annual (5-year rolling estimates). Each row is an aggregate statistic for a geography, so results describe a market as a whole rather than a single account.

Why it is useful

  • Turns a place name into a denominator, so counts from other datasets become rates you can compare across markets.
  • Separates markets that look busy because they are large from markets that are genuinely underserved.
  • Supports age, income and household splits that shape which offering fits a territory.

Questions it helps answer

  • How many people actually live inside this territory?
  • Is demand here driven by population size or by unusually high per-capita need?
  • Which nearby counties are large enough to justify a second visit each month?

How different verticals use it

RepVector is vertical-agnostic: this dataset is selected by what your question asks for, not by industry. These are common ways teams put it to work.

Healthcare & life sciences

Converts patient volumes into per-capita rates so a small county with high need outranks a large one with low need.

Retail & consumer

Sizes catchment areas and household mix before committing to a site or a route.

Financial services

Segments a territory by income and household composition to match product to market.

Education & workforce

Projects the school-age and working-age base a programme would serve.

How RepVector uses it

  1. You describe a market in plain language. The geography resolver turns the place you named into the exact identifiers this dataset needs — city to county to state, plus DMA where relevant — so a query at county runs without you knowing any codes.
  2. The planner selects American Community Survey (5-year) only when your question matches what it actually reports. It is never included to pad a result.
  3. Returned rows are normalised into the shared metric layer, so figures from U.S. Census Bureau line up with every other source in the same dashboard instead of sitting in an isolated table.
  4. Quality checks score coverage and recency. If U.S. Census Bureau suppresses or omits a value for your geography, the gap is reported as a gap — nothing is estimated or filled in.
  5. The result renders as charts, KPIs and, where the rows are entities, prioritised targets you can export to PDF, Excel, CSV or JSON.

What it does not tell you

  • Describes people, not buyers — pair it with provider or facility data before building a call list.
At a glance
How this dataset can be queried and how current it stays.
Publisher
U.S. Census Bureau
Geographic grain
county
tract
zcta
state
Refresh cadence
Annual (5-year rolling estimates)
Row represents
statistic
Topics
population
demographics
income
age
households
housing
education
employment
poverty
median income
market size
consumers
Available fields
The columns this dataset returns in a RepVector build.
FieldKeyType
Countynamestring
FIPSgeoidgeo
Total populationpopulationnumber
Median agemedianAgenumber
Median household incomemedianHouseholdIncomecurrency
Median home valuemedianHomeValuecurrency
Householdshouseholdsnumber
Employed (16+)employednumber
Unemployed (16+)unemployednumber
Bachelor's degreebachelorsnumber
Unemployment rateunemploymentRatepercent

How it fits with the rest of the catalog

Population figures become decision-grade once divided into provider counts and facility capacity for the same geography. RepVector queries every selected dataset against the same resolved geography and time window, then normalises the results into one metric layer so they can be charted side by side. These datasets are the most common companions to American Community Survey (5-year):

Browse all datasets

Common questions

What does American Community Survey (5-year) contain?

Population, age, income, housing, employment and education estimates for every county, tract and ZIP-code tabulation area in the United States. The general-purpose baseline for understanding who lives in a place and what their economic circumstances are. It is published by U.S. Census Bureau at county, census tract, zcta and state grain.

How often is it refreshed?

U.S. Census Bureau publishes on a annual (5-year rolling estimates) cycle. RepVector re-reads the source on that cadence and keeps every prior capture, so you can see what changed.

Do I need an account to use it?

No. Browsing the catalog and the free lookup tools needs no account. Running a full market build across every county in a territory is the paid product.

Put American Community Survey (5-year) to work in your market
Describe the market and the customer you want in plain language. RepVector resolves the geography, selects the datasets that actually answer it — including this one when it fits — and builds the dashboard, targets and exports.

Build the list for one county and see whether the names are right.

Ask in plain language. RepVector finds the universe, enriches each target from its own website, scores it 0–100, and hands you a ranked call list with phones, addresses and named contacts.

Build a target list free

3 free runs — no card required.