Triangulating Your Data Solution

Triangulating Your Data Solution

Which are the commercial buildings?

What are the heights of the buildings in the city?

What addresses are in the building?

Easy to answer questions, right?  As BuildingFootprintUSA creates high quality, richly attributed building footprint data, these are the questions that we hear.  On the surface, each of these questions sounds simple until you dig a little and find the intention behind each question. We find that the same question can actually be looking for different answers depending the intent  behind it; how the question is asked can lead to completely different solutions that will solve the problem.

Creating data solutions that answer questions such as these requires creativity.  Frequently, BuildingFootprintUSATM data solutions use not one, not two but as many as three different datasets.  We build data solutions for our customers that triangulate an answer from multiple data sources.

Let’s look at an example.

Which are the commercial buildings?

When someone asks us this question, we answer with a question.  Do you mean any commercial buildings? Do you mean retail? Do you want to identify any building that has any type of business, even a home-based business?  Do you mean zoned commercial?  

To develop data solutions that answer these questions (and more), we triangulate:

  • The foundation is business list data from Infogroup, which models all business activity across business classifications in the USA 
  • We use property usage and zoning codes that come from assessor data
  • U.S. Postal Service residential & business delivery indicators contextualize the activity associated with each address

With this stack of data (and other data that indicates commercial activity) we can answer virtually any question, or we can answer the same question – can you show me the commercial buildings? – in virtually any way.

Trusted Partners Triangulate Solutions

To solve these hard problems, why are we triangulating across datasets?  There are (of course!) three reasons why we do this.

3. No dataset is complete and up-to-date. Every data provider should be transparent about the completeness and currency of its data.  With that transparency, you will quickly see how every dataset has gaps. Triangulating among more than one dataset can help to fill those gaps.


2. Multiple datasets can each contribute to answering your question.  For example, you may ask a question that requires complex answers drawn from multiple datasets – “show me all buildings that have at least one business AND that the U.S. Postal Service believes have business-related addresses”


3. Multiple datasets can be cross-referenced to validate answers to important questions;  when your business is making big decisions using data solutions. It’s important to verify the results.  

 Need another example?

When someone asks “What are the heights of the buildings in the city?,” they could mean:

  • the number or floors or stories – they could be analyzing real estate valuation by floor
  • the physical height of the building – they could be planning 5G coverage and need to understand how building height impedes wireless signals
  • the building’s height above sea level – they are in emergency management and need to understand how a signal from a device translates to a location in the building

There isn’t a single data element that is going to answer all of these questions.  Even the datasets that can answer just one of these questions are not complete. For example, we use assessor data to determine numbers of floors; this data can be incomplete and can require supplemental sources such as height to model out the number of floors in buildings.

Picking the right data solutions company

Businesses are seeking better solutions for long-standing problems and striving to solve previously intractable solutions.  We have moved past the point where the majority of problems can be solved with simple data solutions. When your business analysis gets complex, what should you look for in a data solutions company?

A great data solutions company will:

  • make you aware of the ingredients that could be used to solve your problem
  • describe the limitations of these ingredients – completeness, currency, and fit for purpose
  • design a data solution working with you that blends different components together to solve your problem

BuildingFootprintUSA’s goal

Our goal is to be the company that is asking the right questions to fully understand your business problem.  We are building a shelf of data ingredients that we can blend and use in combination to solve your problem. We do this all in a manner that makes it easy to use our solutions – easy to license, easy to use, easy to get value.  Start a dialogue with us about how a new data solution can solve your challenging business problem.

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LightBox acquires industry leader BuildingFootprintUSA™

IRVINE, CA – February 1, 2021 – LightBox, a leading provider of commercial real estate data and workflow solutions, announced the acquisition of BuildingFootprintUSA™, the premier provider of building and structure boundaries for location analytics. With this acquisition, LightBox will immediately make building footprints available to its customers.

Connecting BuildingFootprintUSA datasets to LightBox data will create the industry’s only fully integrated parcel, building structure, and property attribute datasets for comprehensive location intelligence across the commercial real estate, telecommunications, routing & logistics, and insurance markets, as well as the broader geospatial ecosystem.

“This acquisition demonstrates our ongoing commitment to innovation that serves the commercial real estate ecosystem. We’re looking to replace existing information silos with industry standard linked datasets. Our parcels and property data will now be integrated with rooftop-level geocodes, addresses, and boundaries,” said LightBox CEO, Eric Frank. “We strongly believe the future is one of connected datasets and we want to drive this change for the commercial real estate industry in the US and Canada.”

BuildingFootprintUSA was founded in 2016 in Albany, New York. The company serves customers of all size within commercial real estate, telecommunications, insurance, and mapping solutions with high-accuracy location data to facilitate accurate site selection, routing, spatial analysis and data visualization. Customers leverage building geometry, height, and ground elevation data to assist in determining potential flood risks, expanding broadband connectivity, policy planning for safety and security, and broader geospatial analytics.

“Joining LightBox gives us an exciting opportunity to grow and deliver our data and solutions to a broader segment of the commercial real estate market in the US and Canada,” said Karl Urich, founder and president of BuildingFootprintUSA. “By combining our datasets with those of LightBox, we will be able to offer the most accurate boundary, address, and geocoding dataset available.”

To learn more about how you can begin leveraging solutions that combine the best of BuildingFootprintUSA and LightBox today, please visit

LightBox is building the world’s leading real estate information and technology platform. LightBox customers comprise all types of enterprises needing authoritative real estate data and workflow solutions, including brokers, developers, investors, lenders, insurers, environmental consultants, corporations, technology companies, and valuation professionals. LightBox is backed by Silver Lake and Battery Ventures.

Learn More About LightBox at

At BFUSA LightBox, we develop next-generation geolocation data centered on the built environment — where people live, work, shop, and play. Our hyper-accurate building and address data helps customers make critical decisions that are highly dependent on location. Learn more about BFUSA.

Learn More About BFUSA