TY - JOUR
T1 - Big Data and consumer behavior
T2 - imminent opportunities
AU - Hofacker, Charles F.
AU - Malthouse, Edward Carl
AU - Sultan, Fareena
N1 - Publisher Copyright:
© 2016, © Emerald Group Publishing Limited.
PY - 2016/3/21
Y1 - 2016/3/21
N2 - Purpose – The purpose of this paper is to assess how the study of consumer behavior can benefit from the presence of Big Data. Design/methodology/approach – This paper offers a conceptual overview of potential opportunities and changes to the study of consumer behavior that Big Data will likely bring. Findings – Big Data have the potential to further our understanding of each stage in the consumer decision-making process. While the field has traditionally moved forward using a priori theory followed by experimentation, it now seems that the nature of the feedback loop between theory and results may shift under the weight of Big Data. Research limitations/implications – A new data culture is now represented in marketing practice. The new group advocates inductive data mining and A/B testing rather than human intuition harnessed for deduction. The group brings with it interest in numerous secondary data sources. However, Big Data may be limited by poor quality, unrepresentativeness and volatility, among other problems. Practical implications – Managers who need to understand consumer behavior will need a workforce with different skill sets than in the past, such as Big Data consumer analytics. Originality/value – To the authors' knowledge, this is one of the first articles to assess how the study of consumer behavior can evolve in the context of the Big Data revolution.
AB - Purpose – The purpose of this paper is to assess how the study of consumer behavior can benefit from the presence of Big Data. Design/methodology/approach – This paper offers a conceptual overview of potential opportunities and changes to the study of consumer behavior that Big Data will likely bring. Findings – Big Data have the potential to further our understanding of each stage in the consumer decision-making process. While the field has traditionally moved forward using a priori theory followed by experimentation, it now seems that the nature of the feedback loop between theory and results may shift under the weight of Big Data. Research limitations/implications – A new data culture is now represented in marketing practice. The new group advocates inductive data mining and A/B testing rather than human intuition harnessed for deduction. The group brings with it interest in numerous secondary data sources. However, Big Data may be limited by poor quality, unrepresentativeness and volatility, among other problems. Practical implications – Managers who need to understand consumer behavior will need a workforce with different skill sets than in the past, such as Big Data consumer analytics. Originality/value – To the authors' knowledge, this is one of the first articles to assess how the study of consumer behavior can evolve in the context of the Big Data revolution.
KW - Big Data
KW - Consumer behavior
KW - Marketing analytics
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U2 - 10.1108/JCM-04-2015-1399
DO - 10.1108/JCM-04-2015-1399
M3 - Article
AN - SCOPUS:84961626098
SN - 0736-3761
VL - 33
SP - 89
EP - 97
JO - Journal of Consumer Marketing
JF - Journal of Consumer Marketing
IS - 2
ER -