Can data save small businesses? Benefits and challenges of data analytics adoption among small-sized retailers

Naeun (Lauren) Kim, Terry Haekyung Kim and Jinsu Park
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Naeun (Lauren) Kim: Assistant professor, University of Minnesota, USA
Terry Haekyung Kim: Doctoral student, University of Minnesota, USA
Jinsu Park: Doctoral student, University of Minnesota, USA

Applied Marketing Analytics: The Peer-Reviewed Journal, 2023, vol. 9, issue 3, 236-248

Abstract: Small businesses were recently hit hard by the COVID-19 pandemic, and there has been a crucial need for them to meet changing consumer behaviour and industry trends through data analytics. The purpose of this study is to understand the status of the adoption and utilisation of data analytics among small-sized retailers. Through in-depth interviews with US small business owners in the retail industry, the findings provide an overview of data analytics implementation status among small businesses. With regard to technological factors, the advantages of data analytics utilisation were identified (ie a better understanding of customers, strategic decision making, optimisation of marketing tools and accurate sales/trends forecast). Technological difficulties in understanding data and data analytics tools appeared as challenges. With regard to organisational factors, the small size of the firm and top management support were identified to be influential factors in the data analytics adoption process. However, lack of time, training resources and human resources were identified as major organisational challenges. As for environmental factors, macroeconomic contexts such as the COVID-19 pandemic and dynamic market trends influenced small businesses to adopt data analytics. Based on the technology-organisation-environment framework, the findings contribute to SME research and become a stepping stone to deriving a new framework.

Keywords: SME; data analytics; technology-organisation-environment framework; COVID-19; social media data (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2023
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