AI-Driven Predictive Analytics for Multi-Cloud Marketing of Creative Works in Calabar Municipality, Nigeria

This study focused on AI-driven predictive analytics and multi-cloud marketing strategies required for enhancing the marketing of creative works in Calabar Municipality, Nigeria. Specifically, the study determined: AI-driven predictive analytics for enhancing marketing performance of creative works in Calabar Municipality; multi-cloud marketing platforms for scalable, flexible, and cost-efficient promotion of creative works and AI-enabled visual and predictive analytics for consumer engagement and purchasing behaviour for creative products. Research design was descriptive survey. Population was made up of 1,020 creative work practitioners in Calabar Municipality. Questionnaire was used to collect data. Data were analysed using mean, standard deviation and t-test at 0.05 level of significance. Finding are seven AI-driven predictive analytics required for enhancing marketing of creative works, including ability to: improve pricing decision using AI analytics (X̅g= 4.60); use historical sales data for forecasting demand (X̅g= 3.65) and others. Further findings are 10 multi-cloud marketing platform required for scalable, flexible, and cost-efficient promotion of creative works. These include ability to: scale marketing infrastructure without service disruption (X̅g= 3.75); deploy campaigns across multiple cloud-based platforms (X̅g= 3.45) and so on. Additional findings are 12 AI-enabled visual and predictive analytics required for enhancing consumer engagement and purchasing behavior of creative product, including among others, to ability to: predict consumer interest using AI analytics (X̅g= 4.58). Based on the findings six recommendations were made.