CBRE Puts Machine Learning To The Task Of Figuring Out Good Retail Locations
Chicago-based Forum Analytics, a CBRE subsidiary, has rolled out a data product it calls ShopoGraphics, the thrust of which is to help retailers identify solid markets for growth and maximum return on investment.
The technology employs machine learning, and Forum Analytics said it is a marked improvement over traditional, demographic-based segmentation systems. Those systems create distinct types, or "segments," to help marketers understand consumer likes, dislikes and purchase behaviors.
Machine learning is a subset of AI in which systems have the ability to improve based on experience, without being explicitly programmed. It is one of the branches of data science now being brought to bear on improving outcomes in commercial real estate.
ShopoGraphics is built from over 1.4 million data points categorized into zones of retail activity. The company said the resulting 37 distinct retail segments — with names like "Soccer Mom Pit Stop" and "Fast Food For Dinner" — help retailers, restaurant operators and consumer service providers identify the best markets for growth.
ShopoGraphics allows Forum Analytics to measure a client’s sales performance based on the types of commercial activity that exists around its locations, Forum Analytics Senior Managing Director Paul Sill said in a statement.
"We can identify the center types and activity clusters that correlate to their highest performers, then help them find other commercial corridors of like activity," he said.
ShopoGraphics' segmentation analysis is included for every new client that engages Forum Analytics for regression-based sales forecasting, or when existing clients renew their agreements for regression modeling.
The company's profiling can also be performed as an independent exercise to look for shopping centers with co-location businesses that drive revenue for particular retailers.