ZoneSavvy taps big data to help SMBs find best sites for businesses
- by 7wData
Location, location, location: As the old joke goes, those are the three keys to business success. Now, with big data analysis, corporations can be smarter than ever before about where to open up new offices or businesses.
But what if you run a mom-and-pop shop, or you're dreaming of quitting your corporate job and opening a boutique? Even medium-size businesses do not have the money to spend on the sort of systems and analysis teams that corporate behemoths use to locate new businesses.
This is where ZoneSavvy, a new website created by software engineer Mike Wertheim, could help. The site is straightforward: You enter a business type, the ZIP code of the general area where you want to locate the business, and the distance from that ZIP code you are willing to consider. ZoneSavvy then gives you suggestions for which nearby neighborhoods would be the best locations for your business.
ZoneSavvy does this by sifting through and cross-referencing demographic, real estate, and economic information. It looks at the age and income of people living in your target area, the price of commercial real estate, and what types of businesses are located there. By comparing that information with data from other areas, it determines which types of businesses are popular in similar neighborhoods and under-represented in the area you're interested in.
For example, if you're thinking of opening up a dance club in New York City within a 10-mile radius of midtown Manhattan, ZoneSavvy will look at neighborhoods with the same profile as your target area. It will then tell you which neighborhoods in the vicinity of your target ZIP code have no dance clubs, but are similar to areas where dance clubs are clustered. In this way, you can not only identify the types of neighborhoods where dance clubs prosper, but also which neighborhoods of that type currently offer no competition.
ZoneSavvy also lets commercial property owners and real estate agents do the reverse: enter an address of a property for which they are trying to find a tenant.
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