Recommending Products and Services Belonging to Online Businesses Using Intelligent Agents

What is it about?

A sure method for a business organization to increase the revenue is to expand its customer base in order to sell more products. The authors propose a recommendation-based system composed of multiple online businesses that share information regarding customer purchases while taking into account the users’ privacy. The product and service recommendations depend on other users’ purchasing patterns and also on the different product types and quantities sold by the business organizations that are part of the system. A practical example is when somebody purchases a vacation. In this case, that customer can receive a recommendation from the other businesses in the system for a car rental service, a hotel, a restaurant or a travel guide pertaining to the location where he/she is going. The proposed solution can be easily put into practice especially if a correlation can be made between the products and the services that are offered by the different online businesses in the system. The insight for management: An increase in revenue and a better customer experience is achieved if businesses recommend each other’s products and services that are relevant to each user purchase.

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Why is it important?

There are two main advantages of the proposed solution for recommending products and services belonging to online businesses: - The purchasing patterns are determined by the agent located at the online business and no information which would violate the user’s privacy is shared with the system, - Each intelligent agent can make recommendations based on a product type association weighted graph which is dynamically updated each time a purchase is made and each time the user offers feedback