Faculty of Commerce, Law and Management (ETDs)
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Item Machine learning in marketing strategy: A socio-technical approach in South Africa(University of the Witwatersrand, Johannesburg, 2024) Govender, Aleasha; Quaye, EmmanuelThe purpose of this research study was to determine whether the existing market segmentation, targeting and positioning (STP) approaches are optimal for marketing strategy in South Africa, and to what extent AI and machine learning are being used to improve marketing strategy in South Africa. The methods used have drawn on qualitative data research and document analysis. There were 10 participants in the study, the industries include Banking, Telecommunication and Medical Insurance. The methods used have drawn on qualitative data research and document analysis. The key results of the research have determined that Machine Learning is in its inception phase in terms of being used in marketing strategy in corporate South Africa. The research further finds that there are factors that are slowing the development in this field that are aligned with both hard and soft capabilities, for example, along with infrastructural capabilities like software integration, strategic capabilities like interdepartmental alignment are required for effective deployment of these technologies. Further, the research finds that the current segmentation, targeting and positioning methods used in isolation are not optimally contributing to marketing strategy, rather a blended approach including insights from customer data will provide a more accurate STP strategy. This research supports marketeers, technologists, business structures, researchers in South Africa, as well as strategists who deal with mass consumer bases, because market segmentation, targeting and positioning underpin how marketing strategy is rolled out throughout corporate South Africa and AI and Machine Learning are emerging technologies that are highly topical and are only at the inception phase of optimal utilisationItem Marketing strategy and business profitability in the South African FMCG industry(University of the Witwatersrand, Johannesburg, 2023) Lephoko, Thembelihle Philladelphia; Quaye, EmmanuelThis paper reviews the lay of the land of the FMCG Industry and identified technological challenges, intense competitor rivalry, and evolving consumer needs and demands as contributors that need to be considered during decision-making and marketing strategy development; an important force behind companies delivering profits. Big data analytics has gained widespread recognition as a revolutionary technology in both the academic and business arenas. With more companies launching initiatives dedicated to its implementation, there is still a lot of doubt regarding its potential to transform its operations. Through a literature review, the study revealed key factors of big data analytics and marketing strategy that influence profitability for South African FMCG companies, and it was furthe underpinned by a conceptual framework to test the relationship between the identified factors and profitability, all in the effort to implement the identified factors and constructs effectively. A cross-sectional quantitative study was executed to establish whether big data analytics has a significant relationship to profitability, furthermore, the study tested the usefulness of big data on marketing strategy as well as the rate at which it impacts profitability. The study was conducted on 150 individuals, with 88.1% of them being marketing professionals. SPSS was used as a statistical tool to test the hypotheses that were identified through the literature review. The key findings of this study recommends that FMCG companies focus their efforts on adopting an organizational culture that supports the usage and adoption of big data in decision-making, underpinned by the right technical and managerial skills to extrapolate actionable insights from the data, and forming them part of the marketing strategy process. The findings of the study will open South African FMCG companies’ eyes to the capabilities and benefits of big data and how their marketing strategies can be enhanced for greater organizational impact