Enhanced recency, frequency, and monetary method with purchase timing for analysing customer purchasing behaviour - Lim, Ken Tak (2024)
The research focuses on advancing the traditional RFM (Recency, Frequency, Monetary) model by introducing a novel metric—Timing—to form the Enhanced RFMT model. This addition aims to provide a deeper understanding of customer purchasing behaviors by accounting for the temporal intervals between transactions. Using this model, the study addresses key questions regarding the effectiveness of integrating Timing into the classic RFM model and its impact on customer segmentation and marketing strategies. The study utilizes primary data collected from online retail transactions to simulate real-world scenarios and test the practical applications of the enhanced model. The results show that incorporating Timing improves the predictive accuracy of consumer behavior models, enabling retailers to better anticipate customer needs and preferences. It also highlights the benefits of using the RFMT model for more accurate segmentation and improved decision-making in inventory control, marketing communication, and customer retention. Overall, the enhanced model allows businesses to optimize their strategies and adapt more effectively to the dynamic retail landscape.