SalesAssist: A Sales Agent Recommender System Through Buying Patterns Analysis

The process of purchasing industrial items has always been a phone call away. Due to the intricate process of purchasing for the exact size of a flange up to the diameter of a pipe, it's more complex to create an e-commerce site for industrial companies. And because most industrial companies still rely on manual purchasing, sales agents have difficulty remembering every item in the product database, tampers with their performance. This study created a web-based recommendation system that acts as an e-commerce site solely catered to industrial companies. The system recommends products to clients based on past purchases, allowing sales agents to work more efficiently. As for clients, the recommendation system endorses items they have bought before and decreases the time they spend looking at each item in the store. An administrator manages all agent and client databases and the item database of the company. The developed system finished all testing and required user acceptance testing. The evaluation of the developed system shows positive results and acceptance by all stakeholders.