Abstract

This study discusses the use of K-Means clustering algorithm to determine market segmentation and prepare targeted marketing strategies. The process involves grouping customer data based on various factors such as transmission type, customer satisfaction, payment method, and branches. After grouping the data, the initialization stage is carried out by providing an initial number, and then the clustering process is carried out. The resulting clusters are analyzed to identify different customer profiles and needs. With an in-depth understanding of each segmentation, companies can develop specific and targeted marketing strategies for each customer group. Additionally, this study discusses the construction of a brand persona by identifying the target audience, understanding their needs and wants, creating a character profile, and compiling a brand persona document that includes all the important information. The customized brand persona can then be used in the development of online value proposition and marketing strategies.

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