Balance as One of the Attributes in the Customer Segmentation Analysis Method: Systematic Literature Review

Abstract

The banking industry is very competitive. To utilize the information, they have in order to be a competitive advantage winner is reasonably very crucial for the company. At present, the company does not only focus on the company's strategy that prioritizes products (e.g. product or service oriented), however also necessitates to focus on the company's strategy in prioritizing customers. Customer segmentation, its attributes, and the appropriate analysis method are going to get accurate data segmentation results, so that it is able to be used as a reference by the company and as a basis for determining its products' marketing strategies. This systematic literature review discusses the types of attributes operated, including customer balance attributes, whether or not they can be included in segmentation. In addition, it also discusses what popular analytical methods are widely used in the customer segmentation process. Literature searching in the digital library resulted in a total are 592,363, 1,361, and 21 papers respectively in the first, second, and third stage. 10 papers found finally in the final stage that were considered capable of answering research questions. Based on 10 papers selected, it can be concluded that customer balances can be functioned scientifically as one of attributes for segmentation use. The popular analytic methods operated for customer segmentation are recency, frequency, monetary (RFM) model (4 times appeared), K-Means algorithm (6 times occurred), and C-Means (2 times emerged).

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