In the last decade, purchasing dynamics have shifted dramatically. Before the rise of e-commerce, consumers had no choice but to visit malls and department stores to buy household goods. As massive online marketplaces proliferate, consumers increasingly shop from the comfort of their homes.
As a result, foot traffic took a hit – and for department stores in particular, a reduction in foot traffic really hurts. Foot traffic is the main driver for revenue, even more than transaction size and conversion rate. Feeling the pinch, Kohl’s rolled out an initiative to increase foot traffic — they added an ‘Amazon Home’ section, and enabled Amazon products to be returned in-store.
The test markets would be Chicago and Los Angeles, as they had been underperforming the rest of the storebase across the U.S. If the Amazon concept worked, they’d roll it out nationwide. In October 2017, Kohl’s launched Amazon Home & Amazon in-store returns in 82 stores across Chicago and L.A.
Measurement & analytics.
How effective will the Amazon campaign be at driving visitation uplift? And how might it impact competitive dynamics?
Spectus’ data clean room. With custom location-based solutions in a privacy-focused environment, Spectus is designed to accurately measure footfall, benchmark against competitors, and attribute visitation uplift to campaign effectiveness. Location data lends itself well to analyzing foot traffic trends in retail environments.
The result? Spectus showed that footfall performance in the stores with the Amazon concept shops picked up immediately relative to the rest of the stores in the US.
- YoY change in performance
- YoY change in daily visits
- YoY change in monthly visits
- Change of share of store visits
Spectus’ measurement solution helps brands visualize complex foot traffic patterns at scale – but measuring footfall is only one of many location-based solutions that Spectus offers.
How does the data clean room work?
Spectus can produce any level of foot traffic analysis by converting raw device-level data into upleveled privacy-safe insights. Spectus converts billions of pings from millions of devices into actionable metrics such as Stops, Trajectories, and Demographics.
The data clean room ameliorates data providers’ concerns about user privacy because privacy protection is baked into the Spectus platform by design. In addition, Spectus filters out Sensitive Points of Interest (SPOIs) such as locations related to health services, religious facilities, and locations with vulnerable populations to ensure that data is handled responsibly and not exploited for unethical purposes.