What do consumers want? A methodological framework to identify determinant product attributes from consumers’ online questions

Angeline Gautami Fernando and Eugene Cheng-Xi Aw

Journal of Retailing and Consumer Services, 2023, vol. 73, issue C

Abstract: Determinant attributes play an important role in consumers’ purchase decisions. Firms rely on them to differentiate their products. Determinant attributes are typically identified using direct methods or indirect methods. However, the voice of the customer online can also provide key insights regarding attributes that are part of the consumers’ pre-purchase search process. The purpose of this study is to propose a framework to identify determinant attributes from online consumer questions. Our method uses semi-supervised Latent Dirichlet Allocation to identify product attributes initially. This is followed by the application of sequence pattern mining to identify temporal sequences of determinant attributes. Finally, hierarchical time series is used to forecast consumer interest in determinant attributes over time. The results show that our study can be used to identify determinant attributes of competing brands and can also be used to forecast consumer interest in these attributes. Brands can use this framework to have a pulse on what consumers look for before purchase. This will aid their decisions related to promotion as well as product development processes.

Keywords: Determinant attributes; seeded LDA; Sequence pattern mining; Hierarchical timeseries; Social media; marketing intelligence; Consumer questions; Q&A features (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:73:y:2023:i:c:s0969698923000826

DOI: 10.1016/j.jretconser.2023.103335

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