ADA derives insights for a Japanese departmental store with location & data analytics
- The client gained a firm understanding on the type of consumers who are seen in the malls.
- A comprehensive report on each of the 10 outlets was produced to show the mall profile, demographics, willingness of visitors to travel, footfall density and more, allowing the client to profile potential consumers that they could win over from competitors and gauge the largely contributing tenants in different outlets.
Although the Singapore economy is slated for recovery due to local vaccination efforts, factors such as continued social distancing measures, reduced footfall traffic, and low volume of visitor arrivals continue to dampen the recovery of the retail industry.
The client turned to ADA by leveraging XACT, ADA’s proprietary data management platform (DMP) and AI-driven solution to uncover data-driven insights on customers in their existing store locations, the locations of their primary competitors, as well as the demographics of selected locations with the goal of increasing customer acquisition.
We identified our target audience, competing malls, and potential malls to open new departmental stores. We geofenced 10 mall outlets to extract profiles of visitors, either by mapping the whole mall, or a section of the mall to best capture the audience for our analysis.
The IFAs of devices seen within the geofenced locations were extracted. Then they were run through our XACT database for consumer profiling.
The identified data sets were analysed, with a focus on the following areas: Cross-visitation patterns, Willingness to travel, Footfall traffic, Catchment heatmap, and more to offer competitive insights.
The target audience for each brand / mall were mapped out. Colour gradients were used to showcase least to most concentration catchment areas. The distance travelled by the target audience to arrive at the identified malls is tracked from their home / work locations.
The movement of the target audience was tracked by day of the week and were categorised for footfall analysis by Weekdays and Weekends. Age group, gender, persona, and behaviours were derived and supplemented using XACT. Affluence is derived from condition-based attributes. The device price tiers and home property price tiers were then segmented.
