Residential Information

Your business problems may require you to understand people — individuals, households, concentrations of people in one building. You may need to understand the characteristics of the people — their demographics. Or you may need to understand the buildings that they live in.

BuildingFootprintUSA™ data solutions can provide you the insight.

Choose from a number of categories of data that can make up a solution:

the household demographics of the building’s residents — population, income, age, wealth, and race
the ownership and valuation of the building — is the building owner-occupied, when was it last sold and for how much, what is the tax burden of the building?
the type of residence — is the building a single family home, a larger multi-dwelling unit complex, a two family flat, condominium, or townhouse?
the physical characteristics of the building — the building’s height, square footage, number of units, foundation type, roof type, and myriad other variables
the individual elements that can make up a residence — how many bedrooms, is there a swimming pool, does the building have a detached garage?

All of this is possible with BuildingFootprintUSA™ data solutions

When you need the highest level of detail you can use micro-demographics — demographic data down to the building level. If your company is hyper-targeting your product or service, if your cost of per customer marketing is high, if you are looking to capture similar customers that live right next door to your existing customers, or if you need to know the exact or best demographics for who is inside a building — all of these are indicators that building level demographics are appropriate.

Census Block Groups data portrays small areas with 500, 1000 or 2000 people as homogeneous. With building level demographics you can see the diverse mix of any demographic variable across the individual buildings within a Census Block Group.

You may need to understand a single variable for each building — for example, the patterns of construction in Santa Cruz, California, when each building was built. With building footprint-based residential information, you can easily analyze when the buildings were constructed. And using building footprints for visualization makes a better map when compared to parcel-based analysis and visualization.

Take the analysis a step further and use 3D to visualize two pieces of residential information. Do you want to see how the unimproved value of land is influenced by proximity to the ocean?