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All Journal Jurnal Ilmu Kedokteran (Journal of Medical Science) INTEGER: Journal of Information Technology Satya Widya JURNAL FARMASIMED (JFM) Abdi Masyarakat Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Al-Mubin: Islamic Scientific Journal Mimbar Kampus Jurnal Pengabdian Masyarakat (ABDIRA) Jurnal Al-Kifayah: Ilmu Tarbiyah dan Keguruan Jurnal Pandu Husada JIMR : Journal Of International Multidisciplinary Research JSIKOM (Jurnal Studi Ilmu Komunikasi) Prosiding Seminar Nasional dan Call For Paper Kebidanan Universitas Ngudi Waluyo Journal of Management and Informatics Prosiding Seminar Nasional Pengabdian Kepada Masyarakat: Peduli Masyarakat jurnal Ilmu Sosial Journal Of Public Policy (Social Politics) Sciences (Polisci) Jurnal Murid ZONA: Jurnal Pengabdian Masyarakat Jurnal Ilmu Multidisiplin
Putri, Nabila
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Journal : Journal of Management and Informatics

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Beyond Descriptive Analytics: Predictive Models For Strategic Marketing Decisions Putri, Nabila; Ainindhira, Aghisti
Journal of Management and Informatics Vol. 4 No. 2 (2025): August Season | JMI : Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i2.165

Abstract

As marketing ecosystems grow increasingly complex, organizations are under pressure to move beyond descriptive analytics and embrace predictive models to enhance strategic marketing decisions. This study investigates the application of predictive analytics, powered by machine learning, in optimizing marketing decision-making processes. Employing a quantitative research approach, we analyzed historical and behavioral data from a digital retail platform over a 12-month period. Several machine learning techniques logistic regression, random forest, and XGBoost were used to build predictive models that estimate customer conversion probabilities and forecast campaign outcomes. The results indicate that predictive models can significantly improve the precision of strategic marketing initiatives, enabling marketers to identify high-value customer segments and allocate resources more efficiently. Compared to traditional methods, the predictive approach led to a measurable uplift in campaign effectiveness and ROI. From a managerial perspective, the study highlights how data-driven strategy and real-time insights can support agile, evidence-based decision-making in competitive markets. Academically, this research contributes to the growing field of predictive marketing analytics by demonstrating the strategic utility of machine learning techniques. In an era where consumer behavior evolves rapidly, leveraging predictive tools is no longer optional it is essential.
Co-Authors Ahmad Syaifudin Ainindhira, Aghisti Ainur Ropik Aisyah Elliyanti Akbar, Sultan Alpina Damayanti, Alpina Angelica, Revina Ardina, Thesa Asmaul Husna Astrid, Gita Bahri, Musa Cimi Ilmiawati, Cimi Dani Rosdiana Dedet Erawati Dedi Irwanto, Dedi Esha, Indi Fadhila, Rheza Yapi Febriyenti, Dini Firliansyah, Hafiz Fortinasari, Paulina Hakiki, Rizkiy Harahap, Esta Rayani Harahap, Sari Ima Rahmawati IZZAH, NURUL Jamilus Jamilus Jayanti, Widya Khairunnisa Khairunnisa Khalil, Khairul Arkan Khalil, Syafiq Lestari, Etika LUBIS, IRFAN DARFIKA M. Yahya Mahendra, Ichlasul Mardhatilah, Ashifa Marhamah, Siti Habibah Marsela, Ranti Marziah, Sari Paton Masitoh, Cahya Meili Amandha Mellani, Annisa Mohammad Zoqi Sarwani, Mohammad Zoqi Mubaroakh, Pintaria Muhammad Firdaus Mulayana, Dede Mulia, T. Iqbal Munawarah, Adeliya Musdalifah, Meldawati Nazwa, Anggita Nengsih, Eka Yulia Ningrum, Novia Novitasari, Lenny Nugraheni, Nonik Nuraida, Siti Rahma Nurhaswinda Nurmalinda Nurmalinda Purba, Novandi Putri, Aprilian Putri, Nurpita Rahayu, Erna Rahmawati, Shinta Ramadhina, Retno Richa, Putri Ridwal Trisoni Rini Susanti Rizal, Muhammad Syahrul Rizandi, Hidayat Rizki Febriani , Aulia Rudi Hariyanto Safari, Dodi Safitri, Nuridha Audinia Sam, Karnilan Lestari Ningsi Sarassari, Rosantia Sari, Heni Elmiani Selviani, Seri Siagian, Bagas Anggara Siti Khumayah Sri Mulyani Sukri Tasya Jadidah, Ines Ulya, Kharirotul Veronica, R. Merlinda Zahra, Lativa