A Scientific Approach to Filling Center Vacancies

The best intelligence depends on having the best data. We have our own shopping center and retailer databases and detailed knowledge of the 860,000 retail districts in the United States, ranging from small areas with a few retailers to downtown Manhattan. These data form the basis of our property scoring logic in the TRP Site Analytics Platform for Brokers and Property Managers.

This unique scoring system gives the first scientific solution to a problem Retail Brokers, Tenant Reps and Property Managers face every day: identifying which retail chains will work best in your locations and generating reports to help recruit them. How is this possible? The Retail Planet created the "BrandScore" concept to solve this problem. Brandscore takes the five major site and trade area attributes that are used to forecast retail performance and pre-scores all 4,000,000 US retail locations for 1,100 major chains. This online database with 20 trillion scores allows you to immediate compare the potential of all major chains for a center or other retail location and identify the highest performing brands.

This time-tested logic for evaluating retail sites, developed by Dr. Richard Fenker and used by major chains to open over 100,000 current retail locations, is now available --- along with all of the data needed to make the forecasts --- in a friendly, low touch format. It can be installed in minutes on your office computers and comes with a full suite of powerful GIS tools delivered on a Google Maps platform.

Even better... once you see some top retailers that you think might fit your location, one click lets you produce a report, customized for your company, to help recruit them. How accurate is this system? Accurate enough to discriminate between the high potential locations for a brand and locations where the brand doesn't belong 90% of the time. What is priceless, however, is that is can take all major chains in s specific category such as "fast food burger" and by comparing scores identify the best ones for your site based on actual consumer preference data. Try this with any other analytics or demographics system --- you cannot do it.