AI-Powered Digital Marketing: Enhancing Customer Behaviour Predictions

Abstract

The article explores the current practices of using artificial intelligence (AI) in digital marketing ecosystems to predict customer behaviour. It has been found that using machine learning technologies and AI analytical tools will not only facilitate the automation of marketing processes but also allow the creation of personalised content, increasing the accuracy of predicting consumer decisions, which helps businesses optimise communication with customers and increase customer loyalty. The study analysed various functional AI tools, such as analytical, predictive, generative, communication, and optimisation technologies. The study uses a scientific integration method that combines theoretical analysis, modelling and empirical research through a survey of 20 experts from five leading Ukrainian retailers. A stratified selection of respondents and a differentiated scoring methodology were used to assess the implementation of digital technologies, programmes and marketing tools. The study highlights the need to improve the methodological approach to using AI in marketing strategies to adapt business processes to changes in consumer behaviour. A conceptual model for integrating digital marketing ecosystems using AI has been developed, providing an integrated approach to data analysis, forecasting and automation of communications. A methodology for assessing enterprises' digital maturity level in marketing is proposed based on determining the implementation index of digital technologies, software and marketing tools. The study results show that artificial intelligence has great potential for developing modern marketing strategies, especially for creating personalised solutions that improve the prediction of the behaviour of individual customer groups.

Keywords: digital marketing ecosystems, artificial intelligence, customer behaviour forecasting, marketing automation, machine learning, content personalization.

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