Remark Holdings, Inc. announced that following the successful openings of CP Lotus's Xuzhou University Road store and the Junsheng store in the Jiangsu Province, Remark's KanKan was once again chosen by CP Lotus to transform one of their traditional supermarkets into a "smart" store by applying their award winning AI technologies in facial recognition, object recognition, and behavior recognition. During the market opening, CP Lotus's Xishan store in Wuxi saw significant customer participation, with over 80% of the visitors entering the store accounted for by Remark KanKan virtual membership archives, while generating coupon distribution and redemption rates as high as 93%. Remark's KanKan applies its AI technology by digitizing the incoming store traffic and linking it to Lotus Supermarket's CRM data, providing the equivalent analytical tools that online retailers have enjoyed in understanding their customer's browsing and purchasing habits. The software allows a store manager to refine store operations to better serve their customers and enhance their shopping experiences while analyzing the customer flow via a traffic heat map. Remark's KanKan has created a digital, user-friendly retail experience to encourage customer participation to capture essential shopping patterns and habits. Whereas previous data was often fragmented and did not provide meaningful insight, Remark's KanKan AI analytics identify customer needs and wants through understanding prior shopping habits, guiding staff to respond quickly to improve the shopping experience. Combined with services, product recommendations, and the training of Lotus's CRM system, a better customer profile is created, which leads to a higher average purchase transaction and repurchase rate. The "smart" retail management system combines in-store traffic flow data and user interaction data, to analyze customer purchase correlation data in real time, diagnose store operating conditions, and improve the response efficiency of the supply chain, replacing sold-out goods on a timely basis. Interactive behavioral data as well as coupon distribution and redemption records are analyzed to continuously optimize and improve the precision of the shopping recommendation system, responding on a real time basis to customer needs, thus improving the customer experience.