Abstract

Sudden changes in life and work patterns due to COVID-19 have affected customer requirements for the products. Under these circumstances, companies can achieve high profitability and customer satisfaction when they can efficiently identify and respond quickly to changing customer preferences caused by COVID-19. This article presents empirical research on dynamic changes in customer responses for product features caused by the spread of COVID-19 through sentiment analysis based on online reviews. A case study is conducted using new and refurbished smartphone reviews to investigate the dynamic changes in customer sentiment before/during COVID-19. The importance of the result is shown by comparing it to the actual market data.

Issue Section:
Technical Brief
Keywords:
data-driven design, online customer analysis
Topics:
Batteries, Data collection, Design, Feature extraction, Preferences, Profitability, Product design

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