Supervised multilabel classification techniques for categorising customer requirements during the conceptual phase in the new product development

Abstract

Abstract The research aims to provide the decision-maker with a framework for determining customer requirements during product development. The proposed framework is based on sentiment analysis and supervised multilabel classification techniques. Therefore, the proposed technique can categorise customer reviews based on the “product design criteria” label and the “sentiment of the review” label. To achieve the research goal, the research presented in this article uses the existing product development framework presented in the literature. The modification is conducted especially in the conceptual stage of product development, in which the voice of the customer or a customer review is obtained from the scraping, and a multilabel classification technique is performed to categorise customer reviews. The proposed framework is tested by using the set data on women’s clothing reviews from an e-commerce site downloaded from www.kaggle.com based on data by Agarap (2018). The result shows that the proposed framework can categorise customer reviews. The research presented in this paper has contributed by proposing a technique based on sentiment analysis and multilabel classification that can be used to categorise customers during product development. The research presented in this paper answers one of the concerns in the categorisation of needs raised by Shabestari et al. (2019), namely, the unclear rules or main attributes of a requirement that make these needs fall into certain categories. Categorising customer requirements allows decision-makers to determine the direction of product development to meet customer needs.