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Optimizing customer engagement content strategy in retail and E-tail: Available on online product review videos

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  • Agrawal, Shiv Ratan
  • Mittal, Divya

Abstract

The present study attempts to examine how the various emotions expressed in customer engagement content available on online product review videos reflect purchase intentions. The study identified 97 popular review videos of different technical products on YouTube, with a total of 93,181 comments posted between January 2018 and June 2021. After filtering, the final set of data consisted of 18,452 comments. The paper employed both Poisson and negative binomial regression to test the hypotheses and strengthen the findings. The study explores new insights for predicting purchase intentions of potential customers with the help of a four-factor model based on customer engagement content available on online product review videos. Thus, this research supports the applicability of MRT, CET and SOR theories in the existing literature on retailing and e-tailing by developing a four-factor model. A wide range of consumer responses, both quantitative and qualitative, have been taken into account to predict purchase intentions using sentiment analysis, which makes this study unique and robust. Additionally, the paper entails several significant managerial implications for retailing and e-tailing firms to reformulate their marketing strategies.

Suggested Citation

  • Agrawal, Shiv Ratan & Mittal, Divya, 2022. "Optimizing customer engagement content strategy in retail and E-tail: Available on online product review videos," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    • Handle: RePEc:eee:joreco:v:67:y:2022:i:c:s0969698922000595
    DOI: 10.1016/j.jretconser.2022.102966
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