Pengaruh Customer-Based Value Metrics dalam Meningkatkan Hubungan Pelanggan pada Luky Petshop
The Impact of Customer-Based Value Metrics on Improving Customer Relationships at Luky Petshop
Abstract
Penelitian ini bertujuan untuk mengevaluasi bagaimana Metrik Nilai Berbasis Pelanggan memengaruhi peningkatan interaksi pelanggan di Luky Petshop. Kerangka kerja kualitatif dengan teknik deskriptif diadopsi untuk penelitian ini. Pengumpulan data dilakukan melalui diskusi semi-terstruktur dan observasi yang melibatkan pelanggan dan pemilik. Penelitian ini berfokus pada tiga metrik utama: Ukuran Dompet, Pangsa Dompet, dan Pangsa Kebutuhan Kategori. Temuan menunjukkan bahwa Luky Petshop mempertahankan hubungan yang cukup kuat dengan pelanggannya, yang dibuktikan melalui pembelian berulang. Namun demikian, kontribusi keseluruhan pelanggan terhadap bisnis tetap suboptimal, karena pelanggan terus membeli dari pesaing dan tidak semua permintaan mereka terpenuhi. Oleh karena itu, perlu untuk mengadopsi rencana Manajemen Hubungan Pelanggan (CRM) yang lebih efisien yang didasarkan pada analisis metrik pelanggan. Dengan meningkatkan ketiga metrik ini, Luky Petshop diharapkan dapat meningkatkan loyalitas pelanggan, meningkatkan pengeluaran pelanggan, dan membangun keunggulan berkelanjutan atas pesaing.
ABSTRACT
This research intends to evaluate how Customer-Based Value Metrics affect the enhancement of customer interactions at Luky Petshop. A qualitative framework with a descriptive technique was adopted for this study. Data collection was conducted via semi-structured discussions and observations involving both customers and owners. The research zeroes in on three primary metrics: Wallet Size, Wallet Share, and Category Requirement Share. Findings indicate that Luky Petshop maintains a reasonably strong rapport with its clientele, evident through repeat purchases. Nevertheless, the overall contribution of customers to the business remains suboptimal, as patrons continue to buy from competitors and not all of their demands are fulfilled. Thus, there is a need to adopt a more efficient Customer Relationship Management (CRM) plan that is informed by an analysis of customer metrics. By enhancing these three metrics, Luky Petshop is anticipated to boost customer fidelity, increase customer spending, and establish a lasting edge over competitors.
References
Dawes, J. G. (2022). Patterns of buyer behavior and brand metrics in a “high loyalty” category: liquor.
Firmansyah, E. B., Machado, M. R., & Moreira, J. L. R. (2024). How can Artificial Intelligence (AI) be used to manage Customer Lifetime Value (CLV) A systematic literature review. In International Journal of Information Management Data Insights (Vol. 4, Number 2). Elsevier B.V. https://doi.org/10.1016/j.jjimei.2024.100279
Golan Hasan, A., Nadia Stefanie Destiana, Ms., Nahruddien Akbar, M., & Cpa, A. (n.d.). Komunikasi Pemasaran Terintegrasi Menara Press Indonesia. Retrieved www.menarapress.com
Hanneke, B., Skiera, B., Kraft, T. G., & Hinz, O. (2025). Decoding blockchain data for research in marketing: New insights through an analysis of share of wallet. International Journal of Research in Marketing, 42(3), 711–727. https://doi.org/10.1016/j.ijresmar.2024.12.002
Hasan, G, Lim, J, Fernandes, N, Raymond, Eddison, T. (2023). Analisa Penerapan Manajemen Hubungan Pelanggan Pada UMKM MM. Gemini di Kota Batam. https://doi.org/10.33395/jmp.v12i2.12506
Hasan, G, Lim, J, Rena, Huang, C, Sembiring, E, I, Syukriansyah, A (2023). Analisa Customer RelationShip Management pada UMKM Es potong Moex. https://doi.org/10.55338/jpkmn.v4i2.1099
Hasan, G., & Noor Liana, E. (2022). What Influences Fashion Consumers’ Loyalty On Social Media in Indonesia? International Journal of Islamic Business and Management Review, 2(1), 42–58. https://doi.org/10.54099/ijibmr.v2i1.125
Hasan, G., & Scorpianti, E. (2022). The influence of usefulness, entertainment, interaction, enjoyment, and familiarity to purchase music platform subscriptions in Millennials and Gen-z communities through trust mediation. Jurnal Manajemen Dan Pemasaran Jasa, 15(2), 161–176. https://doi.org/10.25105/jmpj.v15i2.14071
Hasan, G., Fasha, A., & I, R. A. (2025). Influence of Attitude Toward Green Product on Green Purchase Behavior in E-Commerce. Ekuitas (Jurnal Ekonomi Dan Keuangan), 9(3), 422–441. https://doi.org/10.24034/j25485024.y2025.v9.i3.7351
Hasan, G., Lim, J., Fernandes, N., Eddison, T., & Internasional Batam, U. (2023). Dampak Customer Relationship Management (CRM) Terhadap Kinerja Perusahaan di Tiga Segmen (Keuangan, Pemasaran dan Operasional). Jurnal Minfo Polgan, 12(2). https://doi.org/10.33395/jmp.v12i2.12431
Info, A. (2022). What Influences Fashion Consumers ’ Loyalty On Social Media in Indonesia?? 2(1), 42–58.
Jhamtani, A., Mehta, R., & Singh, S. (2021). Size of wallet estimation: Application of K-nearest neighbour and quantile regression. IIMB Management Review, 33(3), 184–190. https://doi.org/10.1016/j.iimb.2021.09.001
Kurniawan, A. R., Mayasari, R., Febriantoko, J., Taman, P. T., & Jogja, W. (2021). Customer Lifetime Value Metrics as Customer Relationship Management Indicators. Business and Accounting Research (IJEBAR) Peer Reviewed-International Journal, 5(3). https://jurnal.stie-aas.ac.id/index.php/IJEBAR
Mittal, V., Han, K., Frennea, C., Blut, M., Shaik, M., Bosukonda, N., & Sridhar, S. (2023). Customer satisfaction, loyalty behaviors, and firm financial performance: what 40 years of research tells us. Marketing Letters, 34(2), 171–187. https://doi.org/10.1007/s11002-023-09671-w
Osakwe, C. N. (2022). Effects of customer characteristics and service quality on share of wallet in neighbourhood shops based on an asymmetric approach. European Business Review, 34(4), 521–540. https://doi.org/10.1108/EBR-07-2020-0185
Rasool, M. S., Sajjad, A., & Touseef, S. A. (2025). The Role of Algorithmic Ad Personalization in Driving Impulse Buying Behavior: Mediating Effects of Perceived Value and Moderating Personality Traits. Journal of Law & Social Studies, 7(2), 85–98. https://doi.org/10.52279/jlss.07.02.8598
Wieringa, M. (n.d.). What to account for when accounting for algorithms. 1–18.
