Most people choose where to live with a fraction of the information that's actually available about the places they're considering. The data exists, collected at taxpayer expense by federal agencies and supplemented by industry sources, but it has historically been spread across dozens of websites, file formats, and reporting intervals. hearthmap pulls it into one map.
What hearthmap is
hearthmap is an interactive map of the United States that shades every state, county, town, ZIP code, and census tract by whichever data point you choose. Pick “median home price” and the country renders as a gradient from low to high. Pick “percent proficient in math” and the map redraws around school performance. You can zoom from the national view down to individual tracts inside a single city.
The underlying data comes from the Census Bureau, the Bureau of Labor Statistics, the EPA, the CDC, the FBI, the National Center for Education Statistics, FEMA, NOAA, the USDA, HUD, and the USGS, plus Zillow and Redfin for housing market metrics. Nothing is scraped from listings or crowdsourced. The values are the same ones used by researchers, journalists, and government analysts.
Match Score: combining what you actually care about
Looking at one variable at a time only goes so far. Most housing decisions involve multiple factors that have to be weighed against each other. Match Score lets you assign weights to the data points that matter to you, set thresholds where they apply (for example, capping median home price at a number you can afford), and combine them into a single 0-to-100 score for every region in the country. The map then shades by that composite, so the places that fit your criteria stand out.
The output is not a recommendation. It is a way of seeing, at a national or local scale, where your specific combination of priorities lines up with the underlying data.
Common use cases
Relocating for a job
When buyers move to an unfamiliar metro, they typically rely on a small number of sources: a recruiter, a few coworkers, a weekend visit, and online forums. Those sources tend to surface the same handful of well-known neighborhoods and miss areas that may fit better.
The data-first approach is to load the destination metro, weight the factors that matter (school performance, commute distance, price ceiling, crime rate, transit access), and let the map identify the ZIP codes or towns where those factors converge. That narrows a 50-neighborhood field to a handful worth visiting in person, before anyone gets on a plane.
Moving across your own metro
Most residential moves are local rather than long-distance. A family with a child starting kindergarten, a household whose lease is ending, or a buyer planning to right-size after retirement is usually choosing among neighborhoods within an hour of where they already live.
Local reputations tend to lag actual conditions by years or decades. School performance, property tax rates, crime rates, and demographic mix all change more quickly than common perceptions of them do. Looking at current numbers side by side, shaded across a familiar map, often reveals that the assumed ranking of nearby towns is out of date.
Retirement and second-home searches
Retirement-stage buyers tend to weight a different set of factors than first-time buyers do: walkability, hospital quality (life expectancy and CDC health metrics serve as useful proxies), climate and sunny days per year, FEMA disaster risk, cost of living, and proximity to family rather than to schools or jobs. Match Score lets those weights be set explicitly, so the map reflects retirement priorities rather than generic “best places” rankings that assume a young-family use case.
Understanding the place you already live
Even residents who have lived in a town for decades often have only a rough sense of how it compares to neighboring towns or to state and national averages. hearthmap can be used as a benchmark: how does the local PM2.5 reading compare to the county next door, how have crime rates changed over the past 20 years, where does the school district sit in state rankings. The use case is informational rather than transactional, but it is one of the most common ways people interact with the map.
What the map is not
hearthmap is not a recommendation engine and does not produce rankings of “best places to live.” Such rankings always embed someone else's weighting of what matters. The map shows the underlying data and lets the user supply the weights. Two users with different priorities will see two different shaded maps from the same dataset, and that is the point.
The data also has limits. Public datasets are released on different schedules; some are annual, some five-year averages, some monthly. Small geographies sometimes have suppressed values for privacy reasons. Where this matters, the data point definition on the map indicates the source and the reporting period.
Why this matters
Residential location influences household finances, school access, commute time, air and water exposure, and long-term home equity. The data relevant to those outcomes is public, but it has historically been difficult to assemble in one view. hearthmap is an attempt to make that view straightforward to use, without inserting an opinion about what the right answer is.