Artificial Intelligence: Creating a Hyper-personalization Artifact - Murugasu, Umapathy Sivan G; Subbarao, Anusuyah (Society of Visual Informatics, 2025)
This research aimed at synthesizing an artifact that could hyper-personalize customers’ needs using a design science framework. Artificial intelligence (AI) was applied to enable telecommunication (Telco) businesses to offer hyper-personalized products and services, based on a database of customers’ digital demography. A digital demographic database was created using data collected on attributes derived from a systematic literature review. The proof of concept (POC) was developed using the Waikato Environment for Knowledge Analysis (WEKA) software. A systematic literature review was conducted to identify documents used in creating a cross-tabulation of attributes through thematic analysis. This analysis resulted in 32 attributes. The Delphi method for consensus reaching by 10 industry experts was used to reduce to 12 attributes in 2 stages. These attributes were structured into a Google Form to collect customer usage data. Outlier data were removed using multivariable outlier detection by Mahalanobis distance available via SPSS version 21. Using the updated database, several procedures were conducted to determine the best artificial intelligence algorithm for subsequent analysis. Using the Logistic Model Tree algorithm and the customer digital demography, the Telco offering for the customers was predicted with 97.6% accuracy. The artifact created was named Hypersona. The theoretical contribution lies in the applicability of real-time identification of client requirements, targeted client classification, and the ability to offer hyper-personalized products. Implications for Further Research: This research highlights the potential of AI-driven hyper-personalization in the telecommunications sector. Future studies could explore scaling the artifact across diverse businesses.