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It’s not uncommon for busy shoppers to lose their place – and valuable time – amid the dizzying array of products and retail store layouts. And retailers – in the midst of the business of shopping – often let marketing and customer-service opportunities slip through their fingers. But this is an opportunity they cannot afford to squander: The competition to attract and retain customers is a growing challenge, so retailers must find ways to establish stronger customer ties and improve the shopping experience.
Many companies now use loyalty card programs that offer discounts to repeat customers and gather data about their buying habits. The success of such programs relies on how companies use and manage that data. Many have spent years gathering information with few practical applications, hoping that technology would one day catch up with their needs and offer a way to turn data into dollars.
That day is here. IBM Global Business Services, IBM Research and IBM Retail Store Solutions teamed with Cuesol, an IBM Business Partner, to find a way to help turn customer information into useful, profitable action for a large retail grocery chain. With more than 345 stores in the northeastern United States, the company was seeking to solidify its customer base and trigger incremental sales.
Although the grocer already had an existing loyalty card program, it wanted a more precise, cost-effective way to reach customers – not after they made their purchases, but during the decision-making process. The company sought a solution that would allow customers to better manage their time in the store, help them navigate the aisles quickly and reduce wait times. The grocer also wanted to hone its marketing efforts to reach shoppers with relevant, targeted promotions as they traversed the aisles.
The solution was the IBM Personal Shopping Assistant called Shopping Buddy, which consists of a data management system, Wi-Fi network, infrared technology and Bluetooth transmissions centered around touch-screen computers mounted on shopping cart handles. It uses IBM Store Integration Framework, IBM WebSphereŽ Application Server, IBM WebSphere MQ messaging software, IBM TivoliŽ management software, IBM Mobile Tablet for Retail, as well as Cuesol’s Cart CompanionŽ browser software.
IBM Research teamed with IBM’s Retail Store Solution division to assist in prototyping various aspects of the IBM Personal Shopping Assistant for the Store Integration Framework. An in-store retail commerce server prototype was created, which integrated the Shopping Buddies, the location service and the point-of-sale terminal controller. The service-oriented architecture adopted by the in-store server provided the basis for the prototyping of various store services, such as data replications, offer presentations and gift registry. The in-store server also served as the test environment for the development of the Shopping Buddy prototype.
In practice, customers scan in their loyalty cards to activate a familiar, Web-style screen with a variety of display options, such as sale items or a list of products shoppers buy most frequently. A location-tracking system monitored through ceiling-mounted beacons enables the retailer to pinpoint shoppers’ locations and deliver relevant real-time information as they move through the store.
The system integrates with the company’s backend systems, so buying histories and favorite items can be displayed on the screen as a constant reminder of products to buy. The device also lets shoppers order cold cuts from the deli, sending an alert when the order is ready. An attached imaging scanner invites consumers to scan items as they place them in the cart, keeping a running total (of expenses and savings) along the way and completing their transaction using IBM self-checkout systems.
Based on the success of the initial engagement, the company plans to extend the technology to as many as 150 locations.
Meanwhile, IBM Research is exploring ways to refine Personal Shopping Assistant technology with customer-sensitive features, such as suggesting a wine to go with a meal or providing dietary guidance on specific items. Researchers see Shopping Buddy as a prime candidate for moving Web technology closer to the physical world, with, for example, ads targeted to individual consumers, based on prior purchases, in the precise environment where they are primed to make a purchase – just as camera ads show up on your computer screen when you query your search engine for camera. IBM researchers also say the technology could be extended to other retailers and retail sectors.
IBM Personal Shopping Assistant puts technology at shoppers’ fingertips, giving them better control over their shopping experience, and provides retailers with a practical on demand solution.
For more information on IBM Personal Shopping Assistant and to explore other ways to enhance retail commerce, contact On Demand Innovation Services today.
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