Abstract

The shops of today mostly support the customer by offering him or her products based on basic relationships between products viewed or ordered by users with similar tastes. This common approach may fail in many cases especially when the user does not have sufficient knowledge about the market, or when he or she wants to build a set of products in more than one shop. New categories of smart shop services are proposed in order to execute such customer-oriented scenarios where recommended products do meet mutual dependencies with products previously ordered by the customer. An attempt is made to collect additional information about the behavior of users (from past and current contexts) and represent it in a targeted graph called the customer-oriented scenario. Four types of such scenarios are distinguished depending on how many shops have been visited by the user before buying the expected products and how many products the user wants to buy. Moreover, the proposed scenario model provides the possibility of showing which services had been used by the user before the selection was made. Customer-oriented scenarios may be created post factum based on event data logs or before the user will use the shop, which means that it can be arranged which information, knowledge sources (internal or external), products or categories should be suggested in some context of the user’s decision. The possibility of leveraging additional smart services into a traditional trading platform may help users, especially when they want to implement a complex scenario and order many products with mutual dependencies or in a situation when the user wants to understand the market before buying something. Using internal and external services allows creating a network for distributing knowledge focused on the actual customer context in a shop.

Citations

Authors (2)