ARTIFICIAL INTELLIGENCE APPLICATION AND MARKETING EFFECTIVENESS OF ONLINE SHOPPING BUSINESSES IN NIGERIA

Francis Okafor Francis; Osagie Leslie Uwabor

doi:10.5281/zenodo.17414396

Francis Okafor Francis Department of Marketing, Faculty of Business Administration, University of Nigeria, Enugu Campus. Nigeria https://orcid.org/0009-0001-7408-5006
Osagie Leslie Uwabor Department of Marketing, Faculty of Management Sciences, Federal University Otuoke (FUO) Bayelsa State. Nigeria https://orcid.org/0009-0001-4812-6417

DOI: https://doi.org/10.5281/zenodo.17414396

Keywords: Artificial Intelligence, Marketing Effectiveness, Data Mining, Machine Learning, Sales Volume.

Abstract

This study investigates the relationship between artificial intelligence application and marketing effectiveness of online shopping firms in Nigeria. The objectives of the study were to investigate the influence of data mining and machine learning on sales volume. Employing the cross-sectional survey design, the study implemented the quasi-experimental research design. A research questionnaire was developed in accordance with the research questions and distributed to the management level employees and IT staff of these online businesses, who comprised the target population of the study. Each of the twenty-four (24) e-commerce companies chosen for this study received five (5) questionnaires from the researcher. Following data cleansing, an overall total of 102 copies of the disseminated questionnaire were recovered. For this analysis, we utilised SPSS Version 25.0 and the PPMCC to test our hypothesis over these copies. The findings indicated that there exist a positive and significant correlation between the volume of sales and data mining, as well as a positive and significant correlation between the volume of sales and machine learning in Nigerian online purchasing firms. The study recommended that; the data mining activities of the online shopping firms should be standardized to ensure that online shoppers can access desired products and services without any challenges or shortcomings; machine learning should be integrative enough to help both the online business and their customers maintain mutual exchange of information and directives that will not be detrimental to the online shoppers and in extension, the organization.

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