A4 Refereed article in a conference publication
Big Data – Driven Marketing
(konferenssiabstrakti)
Authors: Samppa Suoniemi, Lars Meyer-Waarden, Andreas Munzel
Editors: Nina Krey, Patricia Rossi
Conference name: Academy of Marketing Science Annual Conference
Publication year: 2018
Book title : Back to the Future: Using Marketing Basics to Provide Customer Value
Series title: » Developments in Marketing Science: Proceedings of the Academy of Marketing Science
First page : 141
Last page: 142
Number of pages: 2
ISBN: 978-3-319-66022-6
eISBN: 978-3-319-66023-3
ISSN: 2363-6165
DOI: https://doi.org/10.1007/978-3-319-66023-3_53
Customer information plays a key role in managing successful
relationships with valuable customers. Big data customer analytics use (BD
use), i.e., the extent to which customer information derived from big data
analytics guides marketing decisions, helps firms better meet customer needs
for competitive advantage.
This study addresses three research questions:
1. What
are the key antecedents of big data customer analytics use?
2. How,
and to what extent, does big data customer analytics use influence firm
performance?
3. Is
competitive advantage, if any, achieved through big data customer analytics use
contingent upon its prevalence within an industry?
Drawing primarily from market information use theory, we
advance a theoretical framework to examine how informational and organizational
factors act to enhance big data customer analytics use, which in turn
influences customer relationship and financial performance. More specifically,
we identify and show how information quality (IQ), big data analytics culture,
and customer orientation act as key antecedents of big data customer analytics
use, which in turn is the critical mechanism to achieve superior CRM outcomes.
Finally, we investigate whether the performance implications of big data
customer analytics use vary depending on the prevalence of big data customer
analytics use in the firm’s industry.
Empirical findings from a survey of 301 senior marketing
executives, representing large US-based firms in B2C industries, support our
conceptualization of the performance outcomes and antecedents of BD use. First,
the results highlight that the characteristics of the customer information (IQ)
and the characteristics of the user organization (customer orientation and big
data analytics culture) strongly predict BD use. The findings also reveal the
relative importance of different customer information characteristics to
marketing decision-makers. Second, the results confirm BD use as a key
predictor of firm performance, and more specifically, that big data customer
analytics use primarily influences financial performance indirectly via
customer relationship performance. Third, this study suggests that the
performance impacts of BD use are highly contingent on its prevalence among
industry rivals.