MapVida®, the new data and predictive analysis company, has launched the only patent-pending technology that translates massive amounts of location data into meaningful comparisons to support data-driven business decisions.
Founded and headquartered in Denver, MapVida puts neighborhood data – such as demographics, environmental factors, and business atmosphere – into meaningful context to help business owners, investors, developers, marketers and others find their ideal neighborhoods or customers.
“Using MapVida, businesses can Moneyball their approach to marketing, investment, growth and development, with data-driven decisions,” said Mike Mauseth, Co-Founder of MapVida.
Instead of relying on a gut feeling or one-dimensional approach to evaluate a neighborhood (e.g. It looks like a high-traffic area), MapVida applies data science that uncovers how businesses and consumers fit within a community, providing specific, actionable look-a-like neighborhood types and comparisons across any city or around the country.
MapVida’s algorithms evaluate millions of data points to define the relative look and feel of a neighborhood based on six key factors:
- Who lives there (e.g. married vs. single, commuters vs. walkers, discretionary spending, etc.)
- Real estate types (e.g. single-family vs. multifamily, home size, property age, housing affordability)
- Businesses in the area (e.g. retail and restaurant types, employer size)
- Macro and infrastructure factors (e.g. crime data, school quality, transportation)
- Geospatial and environmental factors (e.g. parks, water quality, hiking access)
- More than 15-years of trending data (e.g. how much has the area changed over time.)
These factors are used to group neighborhoods across the country into types, meaning every neighborhood in each group shares similar qualities and characteristics across all six key factors.
Traditionally, use of data has not been intuitive and lacks a familiar context which has made market comparison analysis a challenge. MapVida’s approach, leveraging algorithms and cluster analysis, helps familiarize businesses with markets in order to make better informed decisions.
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