Predictive Analytics in AI Marketing: Transforming Consumer Engagement

Abstract

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The accelerated use of artificial intelligence in digital marketing, the possibilities of engaging with the consumer through providing individualized experiences have grown immensely. This research investigates the role of predictive factors in the enhancement of social media marketing strategies through a dataset that includes 300,000 campaigns spread out on Instagram, Facebook and Pinterest. The methods Ethical Considerations in the analysis include logistic regression, T-tests and ANOVA, which were used to analyze variations in conversion rates, back end audience targeting and the factors affecting success of the campaigns. The results indicate that advertising on Instagram for the younger demographic groups is also more effective than other forms of advertising because of the platform’s focus on engagement. However, challenges such as privacy concerns, biased algorithms, and legal compliance issues persist. Case studies of Amazon, Starbucks and Netflix show how collaborative filtering along with AI-based personalization methods increase user satisfaction and retention. The findings underscore the evil of customer abuse for coming up with marketing strategies and the role of ethical AI in sustainable advancement of marketing in digital space.