Business Intelligence is the process of identifying user’s behavior with the help of data analyzer. Data analyzer usually goes with the Data Mining process which is easy and understandable to explain for business analyst who makes online business. Since Data Mining collects information about the users who perform in online purchasing. It is easy for online users to find their required products at a certain period without any problem. In our paper mining is based on top-k high utility item sets (top-k HUIs). Which means that we specify k as number of desired item sets that is recommended for calculation (need not to specify minimum utility threshold) we can extract the transactional data through the transactional table which contains user’s number of purchases. Our algorithm makes a compact tree based structure named Utility Pattern (UP) Tree to maintain the information of transaction and utilities of item sets. We generate Potential Top-k High Utility Item sets(PKHUIs) from this we identify Top-k High Utility Item sets (top-k HUIs). Based on the tree structure we come to know about highly extracted products item to the users for purchase. According to the extracted product we stock more products for the user’s convenience. © 2017, Institute of Advanced Scientific Research, Inc. All rights reserved.