See it in action
What SkaldMaps actually does.
Open a state, color the map by any of 442 ZIP-level fields (and 417 county-level + 417 tract-level fields), filter down to ZIPs that fit, click into the details, compare candidates side by side, and turn your weights into a ranked list of every ZIP, county, or census tract to find your perfect place.
That's the whole loop. Five steps, one map, no spreadsheets.
An example
Finding an investment property in North Carolina.
Who doesn't dream about a cabin in the mountains?
01
Layer and filter
Pick a state and poke around our vast dataset.
SkaldMaps opens as a working map, not a generic dashboard. For buying a cabin for recreational use and short term rentals, you probably don't want it to be in the big city.
You can use SkaldMaps to see counties, ZIP codes, urban areas, natural features at a glance - and, for instance, overlay a choropleth of population density.
We can also overlay one of our custom attributes, Urbanicity Score, which combines various attributes to give us an idea how urban an area is.
02
Location, location, location
Add places you actually care about.
SkaldMaps lets you search places by address and add them to the map, use them for filters, map overlays, and ranking.
You probably don't want to be too far away from a place you mean to actually use. Say you live in Mount Holly, NC, just outside of Charlotte - we can add a filter for ZIP codes within 80 miles of there, so the potential cabin is in range for a weekend getaway.
We can also filter by other criteria - say you don't want to get too off grid, so you add a filter for an average of >85% broadband coverage.
03
Build a rating
Turn your priorities into a ranked location list.
Where SkaldMaps really shines, however, is in letting you build your own custom rating model.
We can add all the data we looked at earlier and add them to a custom rating model - and more!
We can use the preference for low urbanicity and high broadband access, but also rate the distance to Mount Holly highly, and make sure we have hospitals within 15 miles, for instance.
04
Inspect a location
Open the details behind a place before you trust it.
Click a location to see values, percentiles, descriptions, and source context. The detail view is for checking whether a promising area actually fits the story.
For instance, we can dig through the details of 28607, a ZIP code of Boone, NC, the county seat of Watauga County in the North Carolina High Country.
Here we can dig into all details, whether we filtered for them or not: For instance, Boone has a population of just under 40,000, a reasonably high household income, good broadband coverage, and great healthcare coverage, to pick but a few data points.
We can also explore historical weather data, voting pattern, school quality, and hundreds of other attributes, and compare them to the rest of the state.
05
Compare candidates
Put several locations side by side.
Shortlists get easier when competing locations are in one table. Compare affordability, access, schools, market pressure, and other signals without switching tabs.
For instance, we might want to compare Boone, NC to a few neighboring ZIP codes when analyzing the area.
SkaldMaps color codes the results, so you know you're not comparing apples to oranges.
06
View the results
Rank, refine, repeat.
You can see the result of your ranking as a table or on the map. The map is great for seeing where the top-ranked locations cluster and how they compare to each other and the rest of the state. The table is better for inspecting the specific criteria behind each ranked location.
Now that you have your first model, you can go digging deeper - add more criteria, change the weights, add filters, and see how the results change.
We currently have 473 fields overall, with hundreds available for weighting, which my accountant tells me is "a lot".
Try it yourself