Clustering Marketing Strategy Based on Applications for Power Upgrading Customers

Himawan Witjaksono Adji

doi:10.37641/jimkes.v13i1.3029

Authors

Himawan Witjaksono Adji Institut Teknologi Sepuluh Nopember; Surabaya, Indonesia

DOI:

https://doi.org/10.37641/jimkes.v13i1.3029

Keywords:

Application, Customer segmentation, K-Means Clustering, Marketing strategy, Power Upgrade

Abstract

The growing electricity demand in Indonesia has led PT State Electricity Company (Perusahaan Listruk Negara/PLN), specifically PLN UID Lampung, to enhance power upgrade services for efficiency and customer-focused solutions. However, electricity sales growth at PLN UID Lampung remains below the national average, hindered by generalized marketing strategies. To address this, implementing a Customer Relationship Management (CRM) application with clustering-based segmentation can provide tailored and targeted promotions, improving sales and competitiveness in the energy sector. This study explores the use of LRFM analysis and K-Means clustering within CRM applications to improve customer management in PLN UID Lampung's power upgrade program. By analyzing customer transaction data, the study identifies four customer clusters with distinct electricity usage behaviors. Cluster 4, the highest revenue contributor, is prioritized for loyalty programs and premium services. Clusters 0 and 1 require educational initiatives and special promotions to increase engagement. The findings suggest optimizing CRM applications for better customer monitoring and segmentation. Recommendations include focusing loyalty programs on Cluster 4, enhancing educational campaigns for Clusters 0 and 1, and regularly evaluating marketing strategies to boost efficiency and retention. These targeted strategies are expected to drive power upgrade program success and strengthen PLN UID Lampung's position in the competitive energy market.

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