Results 121 to 130 of about 15,566,129 (208)

Customer Segmentation Using an Extended RFM Model and Clustering Algorithms in E-Commerce

Journal of Theoretical and Applied Electronic Commerce Research
Customer segmentation is a critical step in the efficient utilization of customer data and maximization of profitability in the e-commerce sector.
Tuncay Ozcan
doaj   +1 more source

A Machine Learning Model for Local Market Prediction Using RFM Model

Elinvo (Electronics, Informatics, and Vocational Education)
This study explores the application of machine learning for local market prediction in e-commerce. By leveraging the RFM segmentation method, the model predicts product sales based on user shopping patterns. The RFM score, calculated using recency, frequency, and monetary values of customer purchases, segments customers into distinct categories.
Muhammad Yahya, Jumadi Mabe Parenreng, Fathahillah Fathahillah, Abdul Wahid, M. Syahid Nur Wahid, Muhammad Fajar B   +5 more
openaire   +1 more source

Comparison of classical RFM models and Machine learning models in CLV prediction

, 2020
Masteroppgave(MSc) in Master of Science in Business Analytics - Handelshøyskolen BI ...
Qismat, Temor, Feng, Yan
openaire   +1 more source

Association between relative fat mass and obstructive sleep apnea and the potential mediating effect of hypertension: based on NHANES 2005-2008 and 2015-2018

Nutrition Journal
Background Obesity has been identified as one of the contributing factors to obstructive sleep apnea (OSA). The current obesity assessment indicators have poor ability to distinguish between fat and muscle.
Qizheng Guo, Weihang Xu, Changcong Wang, Muchen Xie, Zhuoxin Wu, Ning Zhang, Baorui Zhang, Dongmei Mu   +7 more
doaj   +1 more source

Segmentasi Pelanggan Menggunakan Model RFM dengan Algoritma K-Means++ (Studi Kasus: Mondae Coffee)

Mondae Coffee di Kota Kendari masih mengelola pelanggan secara umum sehingga promosi dan program loyalitas belum sepenuhnya dilakukan secara tepat sasaran. Penelitian ini bertujuan menerapkan model Recency, Frequency, Monetary (RFM) dan algoritma K-Means+
Bambang Pramono, Wa Ode Fahmi Ramadhani, Statiswaty Statiswaty   +2 more
core   +1 more source

Database Marketing Tools for SMEs The case of RFM Model [PDF]

Advances in Intelligent Systems Research, 2014
Aquilino Costa, Andrea Sousa, João Lourenço, Carlos Silva, Maria Augusto, Teresa Guarda   +5 more
openaire   +1 more source

Ramadan fasting model modulates biomarkers of longevity and metabolism in male obese and non-obese rats

Scientific Reports
The health advantages of Ramadan fasting, a time-restricted eating from dawn to dusk, have garnered attention. Nevertheless, prior observational studies have found inconsistent findings because of challenges regulating variables such as sleep patterns ...
Abeer Abdallah Alasmari, Maha H. Alhussain, Abdulrahman Saleh Al-Khalifah, Noura Mohammed Alshiban, Rawan Alharthi, Nouf M. Alyami, Hesham S. Alodah, Mohammed F. Alahmed, Bayan A. Aljahdali, Ahmed S. BaHammam   +9 more
doaj   +1 more source

Body roundness index vs. Relative fat mass: associations with cardiovascular-kidney-metabolic syndrome in a cross-sectional study

Diabetology & Metabolic Syndrome
Background Research has indicated that the primary cause of cardiovascular-kidney-metabolic (CKM) syndrome is excess or dysfunctional adipose tissue.
Jun Qiu, Shishuang Jiang, Xiaohong Gou, Youlian Zhou   +3 more
doaj   +1 more source

A Fuzzy Linguistic RFM Model Applied to Campaign Management

, 2018
In the literature there are some proposals for integrated schemes for campaign management based on segmentation from the results of the RFM model. RFM is a technique used to analyze customer behavior by means of three variables: Recency, Frequency and Monetary value.
Carrasco González, Ramón Alberto, Blasco López, María Francisca   +1 more
openaire   +1 more source

Моделювання процесу сегментації клієнтів за допомогою RFM-аналізу для підтримки маркетингових рішень

Метою даної роботи є моделювання процесу сегментації клієнтів у сфері електронної комерції з використанням RFM-аналізу для підтримки маркетингових рішень.
Хижняк, Анастасія Олександрівна
core