Big Data consumer analytics and the transformation of marketing

By Sunil Erevelles, Nobuyuki Fukawa, L. Swayne. 2016

1,172 citations recorded by the source corpus.

Subfields: Management Information Systems, Sociology and Political Science, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/6f0af225c3aa849c2083d7257b4ff9ed4b4eb042

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Citations in the corpus

Mining customer requirements from online reviews: A product improvement perspective (2016, background): “The emergence of big data, the unprecedented volume, velocity, and variety of data available from individual consumers, has changed the ways that businesses understand consumer behavior, including how businesses make decisions [67].”
Digital transformation as a springboard for product, process and business model innovation (2021, background): “For example, Erevelles et al. (2016) explored the impact of big data on various marketing activities.”
Customer relationship management and big data enabled: Personalization & customization of services (2019, background): “Unfortunately the fact is only 8% of the marketers have comprehensive and effective solutions in collecting and analysing those data [26].”
Big data analytics capabilities: a systematic literature review and research agenda (2017, background): “These studies show that a BDA capability can be directed towards strengthening both operational (Chae et al. 2014) and dynamic (Erevelles et al. 2016) capabilities of a ﬁrm.”
The Effects of Digital Transformation on Firm Performance: Evidence from China’s Manufacturing Sector (2021, background): “By collecting massive user data online and profiling users based on big data analysis, companies will be able to understand and even predict user needs and preferences, and then perform precise product or service recommendations [37,54,55].”
Sport Brands: Brand Relationships and Consumer Behavior (2020, positive): “While existing research has mainly investigated psychometric outcomes, the increased availability of actual behavioral data opens opportunities to employ advanced quantitative econometric methods (Erevelles, Fukawa, & Swayne, 2016).”
Research trends on Big Data in Marketing: A text mining and topic modeling based literature analysis (2018, background): “Recent studies conﬁrmed that while some work has been done for ﬁlling such gap, the size of the gap is increasing at the velocity of the inﬂation of Big Data availability (e.g., Erevelles, Fukawa, & Swayne, 2016).”
Examining the impact of luxury brand's social media marketing on customer engagement: Using big data analytics and natural language processing (2019, methodology): “Therefore, future researchers need to combine big data with traditional consumer information collected through behavioral experiments, surveys, or a firm's customer relationship management (CRM) system to gain a more holistic understanding of customer engagement (Erevelles et al., 2016).”
Resource management in big data initiatives: Processes and dynamic capabilities (2017, background): “Others recognize big data affects organizational culture, as decisionmaking becomes more evidence-based (Erevelles et al., 2016; Irani, 2010).”
Assessing the impact of big data on firm innovation performance: Big data is not always better data (2020, background): “In this example, Ford facilitated product innovation by capturing large volumes of data about its customers without waiting to obtain insights from traditional marketing research, such as surveys and focus groups (Erevelles et al., 2016).”
Achieving superior organizational performance via big data predictive analytics: A dynamic capability view (2019, neutral): ““data capture, storage, transfer & sharing (system architecture), search, analysis and visualization (data analytics)” (Chen et al., 2012; Duan & Xiong, 2015; Erevelles et al., 2016).”