Leveraging big data analytics for targeted and predictive marketing in the South African retail sector

Abstract

This study investigates the impact of trust in data privacy regulations on the perceived value and adoption of big data analytics within the South African retail sector. As the retail industry increasingly relies on data-driven strategies for targeted and predictive marketing, understanding the role of regulatory trust becomes crucial. Anchored in the Technology Acceptance Model (TAM), this research explores how consumer and organizational trust in privacy frameworks, particularly the Protection of Personal Information Act (POPIA), influences the perceived usefulness and application of big data analytics tools. Adopting a positivist paradigm and a cross-sectional quantitative research design, the study utilized a structured online survey targeting marketing professionals and digital strategists in South Africa. Descriptive statistics and regression analysis were employed to examine the relationship between privacy trust and the perceived value of big data analytics. While four hypotheses were initially proposed, only one—concerning trust in data privacy—was statistically tested due to data constraints. Findings confirm that higher levels of trust in data privacy regulations significantly enhance the perceived value of big data analytics. Respondents who trusted regulatory protections were more likely to view big data tools as beneficial for marketing, decision-making, and customer engagement. Despite growing awareness of big data’s strategic benefits, privacy concerns, infrastructure challenges, and limited digital literacy remain notable barriers to broader adoption. The study contributes to the academic understanding of technology acceptance in emerging markets and offers practical insights for marketers and policymakers. It recommends the implementation of consumer-centric, ethically grounded data practices, alongside enhanced regulatory awareness and digital literacy initiatives. Future research should empirically explore big data’s effect on sales performance, behavioural adoption, and campaign outcomes across various sectors. Addressing these challenges will be key to unlocking the full potential of big data analytics in South Africa’s evolving digital economy. The proposed recommendations are that future research should focus on understanding marketers' perspectives on big data analytics in South Africa and empirically examining its impact on sales, customer engagement, and decision-making accuracy. Addressing challenges related to internet accessibility and privacy concerns is crucial for unlocking the full potential of big data analytics in South African marketing. In conclusion, while big data analytics offers significant opportunities for South African marketers, overcoming challenges related to infrastructure and privacy is essential for 3 its successful implementation. By addressing these challenges, marketers can harness the power of big data analytics to drive innovation, enhance customer engagement, and achieve sustainable competitive advantages in the dynamic South African market.