Authors - Shamsa AlNasri, Muna Ali AlShamsi, Mariam AlNuaimi, Hanae Ouahhabi, Gurdal Ertek Abstract - This study presents an analytics framework for analyzing and benchmarking sales transactions data of e-commerce products across multiple countries. The framework consists of an integrated multi-faceted application of a carefully selected portfolio of data analytics techniques. Specifically, the framework combines (a) statistical distribution fitting to well-known probability distributions (Gamma, Normal, Weibull, Lognormal), (b) box plot analysis followed by statistical hypothesis testing (Kruskal-Wallis and Dunn tests) and visualization of pairwise comparison results, and (c) text mining (Latent Dirichlet Allocation (LDA) and word clouds). Although many studies in the literature report on the analysis of e-commerce product sales, this is the first study that combines the mentioned techniques within a multi-faceted yet also unified approach. The results obtained for a case study on the Gulf Cooperation Council (GCC) countries reveal regional differences in consumer behavior, pricing, and preferences. The insights obtained can be used to improve the marketing and engagement of the selected case with the selected products and countries. However, more importantly, the primary contribution of the study is the generalizable analytics framework presented that can be adopted and applied to any product set and country selection with similar data attributes.
Open Zoom