TY - GEN
T1 - Mining online reviews to uncover consumer brand engagement
AU - Kulkarni, Uday
AU - Deokar, Amit V.
AU - Ajjan, Haya
PY - 2020/1/1
Y1 - 2020/1/1
N2 - We build on the theoretical foundations of consumer engagement from the marketing literature to propose a novel way to measure consumer brand engagement (CBE) using machine learning and natural language processing of consumer-generated online content. We conceptualize customer-written product reviews as more than just eWOM influencing purchase decisions, but as indicators of CBE. Our method is operationalized through a general-purpose artifact that allows continuous, time-variant, and flexible measurement of CBE. We demonstrate the feasibility of our approach through a large dataset of product reviews of multiple brands of a Fortune 500 garment retailer. Our contribution has implications for research, in that, it creates an opportunity to investigate the antecedent and consequent relationships between CBE and other critical marketing constructs such as intention to purchase and customer loyalty. Further, the ability to measure the time-variant nature of CBE allows for testing leading and lagging relationships between CBE and other key business indicators.
AB - We build on the theoretical foundations of consumer engagement from the marketing literature to propose a novel way to measure consumer brand engagement (CBE) using machine learning and natural language processing of consumer-generated online content. We conceptualize customer-written product reviews as more than just eWOM influencing purchase decisions, but as indicators of CBE. Our method is operationalized through a general-purpose artifact that allows continuous, time-variant, and flexible measurement of CBE. We demonstrate the feasibility of our approach through a large dataset of product reviews of multiple brands of a Fortune 500 garment retailer. Our contribution has implications for research, in that, it creates an opportunity to investigate the antecedent and consequent relationships between CBE and other critical marketing constructs such as intention to purchase and customer loyalty. Further, the ability to measure the time-variant nature of CBE allows for testing leading and lagging relationships between CBE and other key business indicators.
KW - Consumer brand engagement
KW - Natural language processing
KW - Product reviews
KW - Text mining
UR - http://www.scopus.com/inward/record.url?scp=85082294834&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85082294834&partnerID=8YFLogxK
M3 - Conference contribution
T3 - 40th International Conference on Information Systems, ICIS 2019
BT - 40th International Conference on Information Systems, ICIS 2019
PB - Association for Information Systems
T2 - 40th International Conference on Information Systems, ICIS 2019
Y2 - 15 December 2019 through 18 December 2019
ER -