Abstract
Nowadays, many companies are using the gamification approach to promote their products in digital marketing. A gamification marketing approach can only be more effective if the companies can understand their customers’ behaviors through their navigation patterns. Once their behaviors are known by the companies, the appropriate enhancements can be made to improve the marketing strategy. This paper aims to analyze the navigation patterns of the customers based on customer engagement metrics of the time spent on page and visit frequency of each page. Based on these engagement metrics, the action sequences of customers are generated and then evaluated. A sequence model is created to predict the subsequent actions of the customers and to determine the likelihood of using the gamification marketing application. The sequence algorithms, Markov model, and Recurrent Neural Network (RNN) are applied to the sequence models to analyze the customer’s navigation pattern when they are accessing the gamification marketing application.
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Acknowledgments
This work is supported in part by Telekom Malaysia Research & Development Grant No. RDTC/191001 (MMUE/190086) and Multimedia University.
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Lim, ZY., Ong, LY., Leow, MC. (2021). Experimental Study on Predictive Modeling in the Gamification Marketing Application. In: Fujita, H., Selamat, A., Lin, J.CW., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2021. Lecture Notes in Computer Science(), vol 12799. Springer, Cham. https://doi.org/10.1007/978-3-030-79463-7_32
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DOI: https://doi.org/10.1007/978-3-030-79463-7_32
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