DETERMINING BUNDLING SERVICES FOR SALON ADMINISTRATORS USING APRIORI ALGORITHM

Abstract

Optimizing customer pleasure and experience is crucial in the world of service companies. The difficulties salon administrators experience in coming up with efficient service bundling techniques are addressed in this project. The goal of this study is to improve the decision-making process for developing service bundles that are in line with

consumer preferences and corporate goals by utilizing the Apriori algorithm, a well- known association rule mining tool. The suggested method entails gathering and

analyzing past transaction data from client interactions at the salon. The Apriori algorithm can be used to identify frequently occurring services, exposing hidden patterns in client preferences. Then, based on these patterns, service bundles are created to meet the various needs of clients and encourage cross-selling. This project contributes to the automation and optimization of service bundling decisions through the use of the Apriori algorithm. Offering customized and pertinent service packages improves the overall customer experience while also streamlining the process for salon administrators. The findings of this study offer useful information about service bundling tactics that promote customer loyalty and increase business income.