How it Works.
The GPS Geofence Research Process
GPS satellites monitor smartphone apps millions of times per day.
- Locating shoppers in-center/in-store – date and time stamped
- Identifying shopper home location longitude and latitude
- Enabling shopper demographic data appends
- Tagging each shopper record for visit-frequency counts.
August Partners procures massive raw data sets, applies its proprietary methodologies and generates usable, actionable deliverables.
Geofencing brings shopping pattern data and shopper profile data into sync.
Now, the industry can make vital decisions founded on facts.
Case Study: Will a third Target location be successful in an existing market?
Example Analytics: True Retailer Void Analysis
Subject property executives believed that a THIRD Target store in this high-density, affluent market would be successful. Target would need some convincing.
What We Found:
The geofenced shopper-frequency heat map (left) trade areas showed that there was a void in the brand’s market coverage.
The trade area-appended demo comps (below) showed that the potential Subject Property would deliver a more affluent shopper base for Target.
Case Study: Would an existing store/restaurant at Rosedale Center, gain significant shopper-base exposure with an additional location at Woodbury Lakes?
Example Analytics: Cross-Shopping/Exclusive Shopper Base
This is an example from the ICSC/J.T. Riordan School case study prepared by August Partners.
Geofence data can confirm or counter a retailer’s concern about second-location cannibalization. In this case, a Rosedale store or restaurant would gain significant exclusive shopper-base exposure with an additional location at Woodbury Lakes.
This exclusive methodology has proven to be one of the most valuable aspects of geofence research.
Case Study: How do our key shopper metrics compare to our competition? To our market?
Example Analysis: Core and Extended Trade Area Definition & Shopper Metrics Appends
Geofence research allows centers to accurately define trade areas based on measured shopping visit frequencies, over the course of time. This heat map is based on a trailing 12-month period. Zips and Zip + 4 boundaries can be overlaid for digital/social/streaming media targeting purposes. With appended shopper demos, this center can compare its shopper base metrics against its competitor and to the market at-large (the MSA in this example).
Case Study: Can we add additional food & beverage GLA to our center?
Example Analysis: Weekpart/Daypart Shopper Visit Pattern Composition
Geofence data is date and time-stamped, so venues and retailers can examine how a location functions on a day-to-day, hour-by-hour basis. This graph isolates lunch and dinner time periods for three distinct weekparts.
What We Found: In this center, the Thursday-Saturday “Dinner” period produces 12% of shopper visit composition – a number that is somewhat below the national norm.
Future Planning: This center should consider expanding its F&B GLA allocation and/or evaluating its current F&B tenant lineup.
