TY - GEN
T1 - Towards Artificial Intelligence-Driven Marketing
T2 - 8th Conference on Information Communication Technology and Society, ICTAS 2024
AU - Batani, John
AU - Mothabeng, Matau Rosina
AU - Mbunge, Elliot
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Artificial intelligence (AI) is revolutionising almost every industry and sphere of life. AI has been utilise to meet customers' expectations in business sectors by customising products and services. AI-driven marketing promises to improve customer service and satisfaction by analysing customergenerated data to create value, enhance resource allocation and develop effective and cost-effective marketing strategies through big data analytics. However, adopting AI-driven digital marketing in some resource-constrained settings is still nascent, and there is a dearth of studies to enhance AI-driven marketing. Thus, this study proposed a framework to enhance AI-driven marketing adoption by addressing the barriers to the adoption of AI-driven marketing and customer satisfaction in Lesotho. The study used a qualitative research design to (i) explore the challenges faced by businesses in Lesotho in adopting AI technologies for digital marketing and customer satisfaction, (ii) investigate the barriers to AI-driven marketing and customer satisfaction by Lesotho's businesses, and (iii) propose a framework for AI-driven marketing adoption by businesses in Lesotho. Findings revealed that lack of awareness, legislation, resistance and financial constraints were the main barriers to AI-driven marketing adoption. The proposed framework suggests interventions to deal with these impediments.
AB - Artificial intelligence (AI) is revolutionising almost every industry and sphere of life. AI has been utilise to meet customers' expectations in business sectors by customising products and services. AI-driven marketing promises to improve customer service and satisfaction by analysing customergenerated data to create value, enhance resource allocation and develop effective and cost-effective marketing strategies through big data analytics. However, adopting AI-driven digital marketing in some resource-constrained settings is still nascent, and there is a dearth of studies to enhance AI-driven marketing. Thus, this study proposed a framework to enhance AI-driven marketing adoption by addressing the barriers to the adoption of AI-driven marketing and customer satisfaction in Lesotho. The study used a qualitative research design to (i) explore the challenges faced by businesses in Lesotho in adopting AI technologies for digital marketing and customer satisfaction, (ii) investigate the barriers to AI-driven marketing and customer satisfaction by Lesotho's businesses, and (iii) propose a framework for AI-driven marketing adoption by businesses in Lesotho. Findings revealed that lack of awareness, legislation, resistance and financial constraints were the main barriers to AI-driven marketing adoption. The proposed framework suggests interventions to deal with these impediments.
KW - AI-driven marketing
KW - Artificial Intelligence
KW - data-driven marketing
KW - Digital marketing
UR - http://www.scopus.com/inward/record.url?scp=85192275919&partnerID=8YFLogxK
U2 - 10.1109/ICTAS59620.2024.10507141
DO - 10.1109/ICTAS59620.2024.10507141
M3 - Conference contribution
AN - SCOPUS:85192275919
T3 - 2024 Conference on Information Communication Technology and Society, ICTAS 2024 - Proceedings
SP - 12
EP - 19
BT - 2024 Conference on Information Communication Technology and Society, ICTAS 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 March 2024 through 8 March 2024
ER -