

Businesses pick the best location for stores with Smart Mapping. The same technology also works to find unregistered voters.
Most maps just show locations on a maps. Smart mapping does much more. It enables better decision making by considering location AND other factors including demographic data like age, income, race, gender and much more.
How can voting right groups find the most promising areas to focus their efforts? How can smart mapping help? How can costly ways of voter registering like blanketing an area with postcards be supplemented with more cost-effective solutions?
First, map existing voters in an area such a bloc, county or district using data from a voter file. Next use smart mapping to reveal how many people of voting age and other selected criteria live in that area. The difference between the two shows the number of potentially unregistered voters in that area. This information is then used to find mailing address for people living in those areas.
For example, a prospect-rich area for voter registration might be one where the Voter File shows 600 registered voters, but smart mapping indicates there are are 1,000 potential voters.
This blog explains:
- How businesses use smart mapping to increase sales
- What is Smart Mapping?
- How is information about people collected and displayed
- How it can be applied to locate areas with a high probability of finding unregistered voters
- Case study of potential unregistered voters in Appling County, Georgia
How businesses use Smart Mapping


Firms like McDonalds choose store locations based on areas with high densities of of potential customers. They understand who their most likley customers are and then use smart mapping to find areas with such people. This analysis factors age, income, family size of residents as well as nearby employers and traffic patterns. Smart mapping removes much of the guesswork and expense of trying to pick locations manually. This map shows McDonalds stores around Baxley, in Appling County Georgia. You can be sure that McDonalds picked these locations carefully to maximize their sales.
What is Smart Mapping?


Most maps show the locations on a map such as a store, a park or a voter. Smart Maps on the other hand combine several factors (called data layers) for better decision making. This allows planners to ask questions such as:
- Which areas have people making under $50,000?
- Where do people between 18-25 tend to live?
- Where do families with small children live?
- Which communities are predominantly African American?
- Which areas have meet all the above conditions?
Smart mapping eliminates the guesswork and the wasted expenditure of guessing where to focus your efforts.
Smart Mapping software
DemLabs uses ArcGIS Online for Smart Mapping projects with data from Living Atlas. An annual non-profit license for both products costs about $150.
These solutions are from Esri whose software is deployed in more than 350,000 organizations, including the world’s largest cities and most national governments. Esri has 49 offices worldwide, employees from 73 countries and 11 dedicated research centers. (Full disclosure: DemLabs has no financial relationship with esri. I just think they make amazing software that more people should know about).
Finding areas with unregistered voters
Smart Mapping finds likely areas with unregistered voters in a similar manner. Voting advocacy groups first find areas such as a bloc, county or district or county with residents over 18. They can then use the Smart Mapping app to include additional demographic criteria (such as race, income, gender) that they would like to include when encouraging residents to register to vote. Existing voters in the area from the Voter File are mapped to see how calculate the number of unregistered voters. Once this analysis is done, other data sources are used to get lists of the addresses for residents in that area to contact or canvas.
Smart mapping provides organizers a wide variety of criteria to choose from to refine their search including:
- Age (in a number of ranges)
- Gender
- Income
- Race, ethnic origin
- Family size
- Do they rent or own their house


Searching for unregistered voters
This proof of concept map was created with help from Reclaim Our Vote, Greyson Harris and Julia Bayer.
- First 612 existing voters were exported from the Voter File.
- The latitude and longitude for each voter's addresses was calculated with the free(mium) version of GeoCod.io
- Every voter record is represented as a black dot and clicking on it reveals details on the voter.
- Next all the census tracts are overlaid on the map with details of the number of how many residents are over 18 years old.
- The color of a census tract corresponds to the number of residents in it. A darker shade indicates more residents.
Areas with the most unregistered voters are found by comparing the number of existing voters to the total number of potential eligible voters (aged over 18) in a tract. The search can be further refined by mapping down to the bloc level and adding other demographic criteria (such as race, ethnicity or gender) the search criteria. The street addresses for the areas with the most likely unregistered voters can then be obtained through another data service.


Where does mapping data come from?
These map layers rely on census data and subject to sampling variability shown as a margin of error. Learn more at Accuracy of the Data. The layers are updated automatically when the most current American Community Survey (ACS) data is released each year and contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.
County and district boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles.