Predicting e-commerce sales trends using big data analysis

E-commerce and big data are products of rapid technological advances. Big data plays a vital role in e-commerce companies’ ability to manage and analyze the enormous amounts of data generated and can become a source of competitive advantage. This study aims to determine product trends and make predictions. This study uses big data predictive analytics to process and analyze transaction data from e-commerce site XYZ.com. The results show that this type of analysis yields substantial amounts of information about what categories will potentially become trends as well as the minimum stock levels required. Five products with potential to rise in the following months were identified: doughnut lip gloss, fuchsia pen lipstick, red retro spot jumbo bag, pink polka dot jumbo bag, and Keep Calm travelcard wallet. This study provides new insights into inventory planning and how sales can be adequately understood and predicted. The findings of this study can be used by managers of e-commerce companies to formulate effective inventory strategies for reducing operational and opportunity cost.