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Carrefour to Use Bluetooth Beacons to Track Carts, Baskets

The company will be the second retailer to pilot a solution from Proximus to identify the locations of carts and baskets moving around stores, providing analytics regarding shopper behavior.
By Claire Swedberg
Jul 21, 2014

Multinational retail chain operator Carrefour is planning to test Bluetooth beacons to track the movements of shopping carts at three of its Madrid stores this fall. The technology, provided by Proximus, is intended to allow the anonymous tracking of shoppers as they move through the stores, by identifying not an individual shopper himself but rather the shopping cart he is pushing. While in the long run, Proximus intends to offer the solution as part of a retailer's loyalty program that would track individuals via their mobile phones (as long as they opted in), the first step is merely to determine the carts' locations, rather than identify the shoppers using them, according to Jorge Garcia Bueno, a cofounder and the CEO of Proximus.

Bueno and the company's other two cofounders launched Proximus in September 2013, to develop and sell a technology-based product that would allow businesses to better connect with their customers in the way that online stores currently can. For instance, he says, online retailers can identify which products have been viewed and then tailor advertising to an individual based on that information, whereas brick-and-mortar stores do not have that option. Previously, Proximus' founders had started up a company known as beMee, which leveraged Wi-Fi technology for tracking carts' locations. In 2013, with the advent of iBeacons and Apple's release of the iOS 5 software development kit (SDK), they launched Proximus to focus on solutions leveraging battery-powered tags that transmit 2.4 GHz signals compliant with the Bluetooth Low Energy (BLE) standard.

Proximus' Jorge Garcia Bueno
The company, which is headquartered in Spain but also maintains an office in London, is now trialing and releasing its technology in phases. The first phase involves the system now being installed at three Carrefour stores; the solution consists of battery-powered Bluetooth beacons, each of which transmits a unique ID number via the BLE protocol, as well as sensors that receive those transmissions and forward the data to a cloud-based server via a Wi-Fi or wired connection. While the next step will include the use of mobile phones (customers would load an application enabling the phone to transmit BLE data), there are initially no phones being used in the system.

Proximus had the beacons and sensors manufactured by a third-party vendor, and created the cloud-based software to manage the collected data. Bueno says Proximus spent three months piloting the technology this spring at two small Nisa neighborhood food stores in London. The pilot was completed this month, and the company is now installing the system at three Carrefour supermarkets, with a go-live date set for fall 2014.

With the Nisa trial, some beacons were attached to shopping baskets, while approximately seven sensors were installed in each store's ceiling. The two sites have about 50 baskets apiece, Bueno says, though not all of them were equipped with the beacons. The beacons that were in use there, however, transmitted a signal at regular intervals that were received by the ceiling sensor devices, and the software employed the sensor-based data to determine each basket's movement as it passed through the store. The system deployed at the Nisa stores could pinpoint location to approximately 1.5 meters (4.9 feet), Bueno says, which provided sufficient granularity to know in which aisle an individual's basket was located. In this way, the software knew where the shopper went, where she paused, how long she was at the checkout area, and when the basket was returned to the storage area for another shopper's use, thereby indicating that the individual had left the store.

Such data, Bueno explains, provides the retailer with considerable information. For example, a store's manager could determine not only which products may be of most interest to shoppers, but also which aisles may be over-crowded and are causing bottlenecks. In addition, the software could identify when shopper traffic is highest and lowest, and which aisles experience less traffic than others.

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