The mobile personal shopping assistant was equipped with the self-learning Recommendation Engine from prudsys in order to further improve the service for the customer. The software from prudsys, an associate company of technology service provider Pironet NDH, is already being used in a number of leading online shops.
Since 2003, as part of the Future Store Initiative, METRO Group together with about 60 partners has been showcasing the technologies which will change the retail industry in the coming years. Among the goals of the initiative is the creation of new technological standards for the industry as well as the acceleration of the modernisation process in retail. The central focus here is the benefit of the customer. To this end, the Personal Shopping Assistant combines various offers in line with individual customer preferences in addition to enhanced services in the store. The device is attached to the shopping cart and provides product information, prices, notices about sales and advertising specials in addition to allowing for rapid check-out thanks to the integrated scanner. Pironet NDH supplies the PSA software as well as the technology for the customer information terminals, in addition to providing a central integration platform with pirobase Content Bus, which supplies the various different output devices with the appropriate content.
With its new Recommendation Engine, PSA is now in a position to generate dynamic product recommendations and to provide information as to which items best complement the products currently being scanned. One of the principles by which this technology operates states that “customers who buy product A have also bought product B”. In addition, the engine also compares the shopping cart in question with other carts and makes suggestions regarding complementary items based on the related products found. Moreover, the reaction of the customer can be recorded in real-time, and if necessary the offering can be modified dynamically. This allows for new cross-selling scenarios, and an increased average sales volume per shopping cart due to a greater number of spontaneous purchases.
Dr. Michael Thess, Technology Chairman at prudsys AG, sees the use of the self-learning Recommendation Engine on the PSA as a great leap forward in the application of this technology. “With the Recommendation Engine, the recommendation scenario which has been employed successfully in the Webshop for some time can now be directly applied in the store itself.” Michael Jasczyk, Chief Technology Officer at Pironet NDH, adds: “Following the introduction of our interactive coupon scale which we developed jointly with Mettler Toledo, we are now offering an additional intelligent solution to address the customer at the point of decision in a targeted fashion.”
Since 2003, as part of the Future Store Initiative, METRO Group together with about 60 partners has been showcasing the technologies which will change the retail industry in the coming years. Among the goals of the initiative is the creation of new technological standards for the industry as well as the acceleration of the modernisation process in retail. The central focus here is the benefit of the customer. To this end, the Personal Shopping Assistant combines various offers in line with individual customer preferences in addition to enhanced services in the store. The device is attached to the shopping cart and provides product information, prices, notices about sales and advertising specials in addition to allowing for rapid check-out thanks to the integrated scanner. Pironet NDH supplies the PSA software as well as the technology for the customer information terminals, in addition to providing a central integration platform with pirobase Content Bus, which supplies the various different output devices with the appropriate content.
With its new Recommendation Engine, PSA is now in a position to generate dynamic product recommendations and to provide information as to which items best complement the products currently being scanned. One of the principles by which this technology operates states that “customers who buy product A have also bought product B”. In addition, the engine also compares the shopping cart in question with other carts and makes suggestions regarding complementary items based on the related products found. Moreover, the reaction of the customer can be recorded in real-time, and if necessary the offering can be modified dynamically. This allows for new cross-selling scenarios, and an increased average sales volume per shopping cart due to a greater number of spontaneous purchases.
Dr. Michael Thess, Technology Chairman at prudsys AG, sees the use of the self-learning Recommendation Engine on the PSA as a great leap forward in the application of this technology. “With the Recommendation Engine, the recommendation scenario which has been employed successfully in the Webshop for some time can now be directly applied in the store itself.” Michael Jasczyk, Chief Technology Officer at Pironet NDH, adds: “Following the introduction of our interactive coupon scale which we developed jointly with Mettler Toledo, we are now offering an additional intelligent solution to address the customer at the point of decision in a targeted fashion.”
