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Syahroni Hidayat
Universitas Negeri Semarang
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Journal : Journal of Applied Data Sciences

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Integration of Sentiment Analysis and RFM in Restaurant Customer Segmentation: A 7P-Based CRM Model with Clustering Sunarko, Budi; Hasanah, Uswatun; Hidayat, Syahroni; Rachmawati, Rina
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.633

Abstract

The increasing use of digital platforms like Tripadvisor has created opportunities to transform customer review data into strategic insights for Customer Relationship Management (CRM). This study proposes a novel CRM model by integrating the Recency, Frequency, Monetary (RFM) framework with the 7P marketing mix to segment restaurant customers more effectively. Using 3,716 Tripadvisor reviews, annotated based on 7P elements and clustered through unsupervised learning, three key customer segments were identified: acquisition, retention, and win-back. Evaluation metrics show strong clustering performance with a Silhouette Score of 0.73 and a Davies-Bouldin Score of 0.08. The acquisition cluster (Product) demonstrates the highest Frequency (37,664) and Monetary value (64.94), signifying high engagement and revenue potential. The retention cluster (Physical Evidence, Place, Process, Promotion, Traveler) shows stable interaction patterns with Recency values of 1261–1262 and moderate Frequency (378–2,079). The win-back cluster (Price, People) reflects lower Frequency (198–946) but equal Recency (1259), indicating recent but infrequent activity, which is ideal for reactivation strategies. By mapping customer reviews to 7P labels and analyzing them using RFM, the model uncovers specific behavioral patterns tied to service quality, pricing, and promotions. This integration allows restaurants to apply tailored strategies: offering loyalty rewards to high-frequency customers, promotional incentives for those with high Recency, and prioritizing high-monetary customers for exclusive programs. The novelty of this research lies in its combined use of sentiment-based review analysis and RFM–7P segmentation, offering a scalable, data-driven framework for enhancing customer satisfaction, loyalty, and long-term business growth in the restaurant industry.
Co-Authors Abdulloh Abdulloh Abdurahim, Abdurahim Achmadi, Taofan Ali Adam Bachtiar Maulachela Adiastoro, Mahendra Agung Budiwirawan Agus Ardiyanto Ahmad Zuli Amrullah Ahmat Adil Akbar Juliansyah Amrullah Anan Nugroho Ananda, Briska Putra Andi Sofyan Anas Ansar Ansar Ardiansyah, Muhammad Irfan Astri Iga Siska Ayu, Hanifah Baroroh, Luluk Taufiqul Budi Sunarko Budiarto, Jian Budisantoso, Heri Tri Luqman Danang Tejo Kumoro Danang Tejo Kumoro Darmawan, Joelianto Dian Syafitri Chani Saputri Dinata, Muhammad Imam Diyanasari, Ledi Esa Apriaskar Febry Putra Rochim Feddy Setio Pribadi Fikri, Akmal Habib Ratu Perwira Negara Haikal Abror Hakiki, Muhammad Khikam Hanif Ardhiansyah Hanif Hidayat Ida Ayu Widhiantari Intan Ermawati Irmayanti Irmayanti, Irmayanti Ismarmiaty Ismarmiaty, Ismarmiaty Joko Sumarsono Khoiron, Ahmad Mustamil Khoirudin Fathoni, Khoirudin Kumoro, Danang Tejo Mona Subagja Muhammad Fathurrahman Muhammad Hilmy Herdiansyah Muhammad Muhammad MUHAMMAD TAJUDDIN Muhammad, Naufal Murad Murad Murad, Murad Ni Luh Putu Merawati Nugroho, Anan Nur Iksan Qudsi, Jihadil R Fanny Priniti Raden Fanny Printi Ardi Rahmat Sabani Rezky Ramdhaningsih Ria Rismayati Rian Febriyanto Rina Rachmawati Risanuri Hidayat Rismayati, Ria Rizal, Ahmad Ashril Salim, Nur Azis Sandi Justitia Putra Satria, Rifki Lukman Simanjuntak, Jhonatur Stheven Subagja, Mona Sukmawaty Sukmawaty Sukmawaty Sukmawaty Sulistianingsih, Nani Sulistyawan, Vera Noviana Tajuddin, Muhammad Taofan Ali Achmadi Teguh Bharata Adji Uswatun Hasanah Uswatun Hasanah USWATUN HASANAH Wafi, Ahmad Zein Al Wahyudi, Tri Agus Wardatullatifah S, Ince Siti Yusuf, Siti Agrippina Alodia Yusuf, Sitti Agripina Alodia Zaenal Abidin Zaurarista Dyarbirru Zidan Vieri Wijaya