Analisis Prediksi Profil Pelanggan Seluler Untuk Pemasaran Aplikasi Netflix

Suryadi Tanuwijaya, Andry Alamsyah, Maya Ariyanti


The development of Indonesia ICT environment has made mobile video-on-demand (VOD) platform as one of
emerging lifestyle. With advance smartphone technology, mobile phone subscribers able to enjoy high resolution
mobile VOD service with greater user experience. The purpose of this study is to profile and predict potential
customer of one of VOD platform, Netflix, for personalize marketing target. Using machine learning predictive
analytic methodology, customer profile and behavior data is divided into 3 clusters using K-Means model before
tested with several supervised model for getting best model for each cluster. Feature importance analysis will give
marketing insight for product offering follows up to each targeted potential customer. Significant variables
affecting Netflix buyer and non-buyer within 3 different clusters are defined clearly with number of potential
customer that can be targeted as future subscriber of Netflix. Based on the research results, this method can be
used by mobile operator to target potential customer with effective promotional or product offering by personalized
marketing approach based on behavioral pattern and customer needs. It is expected by implementing this
methodology, effectivity and accuracy of marketing will be increased compared to conventional method.
Keywords: Predictive Analytic, behavior, Personalized Marketin

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