Abstract
E-commerce companies want to predict their future product sales from the current customers’ feedback to frame a better business strategy. However, the conventional way of analyzing rating activities or quality and sentiment of reviews, volume of sales, or product prices is not enough for establishing a strong regression between these parameters and future product sales. Most of the existing works ignore the heterogeneous positional and influential effects of individual customer reviews and ratings. For the realization of these effects, we use review network i.e., a bipartite network between customers and products based on the customers’ review activities. In this paper, we present a concept named Network Promoter Score (NePS) based on the reliability, positional influence of each customer in the network. In-depth experiments on online review datasets show that NePS emerges as a strong indicator of product sales and can be remarkably futuristic compared to the existing parameters. Furthermore, we propose a predictive modeling technique to estimate the product sales of a company based on NePS.
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Mandal, S., Maiti, A. Network promoter score (NePS): An indicator of product sales in E-commerce retailing sector. Electron Markets 32, 1327–1349 (2022). https://doi.org/10.1007/s12525-021-00503-1
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DOI: https://doi.org/10.1007/s12525-021-00503-1