Customer satisfaction with a named entity recognition (NER) store-based management system using computer-mediated communication

With the rise of the popularity of e-commerce, it is evident that the service retail industries aim to reduce inventory and increase sales and profit margins. To achieve this, it is of paramount importance to establish excellent and effective interaction between customers and customer support. When a customer orders a product online, it is essential that the store demonstrates whether the products are in stock and the nearest stores to where the customers are. Currently, the needs of the customers are unlikely to be effectively met. Hence, the stores are unlikely to provide desirable products to customers even with high inventory. This paper investigates this issue at a typical and popular retail store in Vietnam. The authors present an investigation of this issue through two main stages. Corpus analysis for a set of collected text messages posted on the stores' websites for customer support was first carried out to explore the lexical patterns that indicate the customers' needs. This analysis revealed the frequency of customers' requests for the stores' locations where they can buy the goods and/or whether they are in stock. In the second stage of the investigation, the valuable findings from the corpus analysis were used for data extraction based on Named Entity Recognition (NER) software. The NER recognizes entities, including locations and names.