Analisis Mendalam Strategi Customer Relationship Management (CRM) Upoint.Id Dalam Membina Loyalitas Pelanggan Gamers di Indonesia
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Persaingan ketat dalam industri top-up game Indonesia menuntut platform untuk beralih dari strategi transaksional ke pendekatan relasional yang berpusat pada loyalitas berkelanjutan. Tujuan tinjauan ini adalah menganalisis dan mensintesis literatur evolusi Customer Relationship Management (CRM), mendefinisikan ulang loyalitas gamers, serta mengidentifikasi dan mengisi kesenjangan strategis pada implementasi CRM UPOINT.ID—sebuah platform digital di bawah Telkom Group—guna mentransformasikannya dari model transaksional menjadi model relasional berbasis komunitas yang terukur. Metodologi penelitian ini mengusulkan kerangka kerja metode campuran (mixed-method) yang terintegrasi. Secara kuantitatif, digunakan model RFM-B (Recency, Frequency, Monetary, Behavioral) yang diperluas, mengintegrasikan data perilaku non-transaksional dengan K-Means Clustering untuk segmentasi persona pelanggan. Secara kualitatif, metode Netnografi diaplikasikan pada komunitas virtual UPOINT.ID (Instagram, TikTok, YouTube) untuk mengungkap dinamika budaya dan motivasi sosial gamers. Temuan Utama mengidentifikasi adanya dualisme strategis, di mana fokus promosi harga massal berjalan terpisah dari investasi komunitas esports (UECS). Kesenjangan ini menciptakan risiko kanibalisasi pendapatan dan alokasi sumber daya yang tidak efisien. Model RFM-B berhasil mengidentifikasi persona spesifik seperti "Juara Kompetitif" (didorong oleh status) dan "Pengamat Setia" (didorong oleh rasa memiliki) yang tidak dijangkau oleh insentif diskon transaksional. Implikasi penelitian ini memberikan kontribusi teoritis dengan memperkenalkan model RFM-B yang mengkuantifikasi aset soft komunitas menjadi nilai matematis. Secara praktis, diusulkan arsitektur Social CRM (SCRM) terintegrasi penuh , dengan strategi bertingkat yang dipersonalisasi untuk setiap persona, menggantikan diskon massal dengan insentif berbasis status dan pengakuan, guna memaksimalkan Customer Lifetime Value (CLV) dan mengoptimalkan Return on Investment (ROI) komunitas UECS.
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