Geo-fencing is a game-changer in the shopping center business – an industry constantly challenged to increase shopper visit share in the face of online competitors, store closings, aging assets and a rapidly evolving customer. With this relatively new methodology, owners/operators can precisely define trade areas, perform competitive visit share analysis and pre-acquisition studies, compare center vs. competitor shopper profiles, make the case for retailer locations/re-locations, track shopper visit patterns over the course of the year – down to days and dayparts – and even examine shopper traffic concentrations within a center.
Instead of drawing the usual 3-5-7 mile circles around a property and pulling demographics, industry professionals can map market penetration and frequency-weighted trade areas that reflect true market shopper dynamics.
How it Works
The geo-fencing process (Fig. 1) begins with creating a “shape file,” in which the subject center is digitally outlined. The shape file is transmitted to a data provider (in this case a digital ad exchange typified by companies like DoubleClick, OpenX, etc.) which, in turn, transmits the GPS signal data they have harvested over a set period of time. In most cases, signal data goes back to 2014 and extends to the present date.
Fig. 2 visually depicts the geo-fencing process (disguised) and a resultant micro-grid map of the center’s trade area – based on frequency-weighted signals. These data sets break out shopper visits by days and dayparts and are aggregated at monthly levels to foster shopping pattern analysis.
As an example (Fig. 3 left; rolling 12-month data), in a Florida center, we see a traditional rise in November/holiday traffic because this center has a strong local TA draw that is exhibiting “typical” shopping patterns. We also see how this center tails off a bit post-Christmas, but then begins its upward visit-generation trending as “snowbirds” return in-force to the market. Because the GPS device signals are traceable back to their source, demographic and lifestyle, etc. data can be appended and are thus reflective of the center’s shoppers as opposed to traditional “market” data.
