Results 11 to 20 of about 3,753 (202)
Customer-Centric Sales Forecasting Model: RFM-ARIMA Approach
Business Systems Research : International journal of the Society for Advancing Innovation and Research in Economy, 2022 Abstract Background: Decision makers use the process of determining the best course of action by processing, analysing & interpreting the data to gain insights, known as Business Intelligence.
Londhe, Sanket, Palwe, Sushila
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Analisis Loyalitas Pelanggan Berbasis Model Recency, Frequency, dan Monetary (RFM) dan Decision Tree pada PT. Solo [PDF]
Jurnal Teknologi Informasi dan Ilmu Komputer, 2020 Perkembangan bisnis alat tulis kantor dan sekolah saat ini banyak yang menjanjikan, maka banyak bermunculan pemasok baru dalam bisnis Alat Tulis Kantor dan Sekolah (ATKS).
Basri Basri +2 more
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Comparison of the RFM Model's Actual Value and Score Value for Clustering
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2023 Clustering algorithms and Recency-Frequency-Money (RFM) models are widely implemented in various sectors of e-commerce, banking, telecommunications and other industries to obtain customer segmentation.
Samidi +2 more
doaj +3 more sources
The Reference Forward Model (RFM)
Journal of Quantitative Spectroscopy and Radiative Transfer, 2017 AbstractThe Reference Forward Model (RFM) is a general purpose line-by-line radiative transfer model, currently supported by the UK National Centre for Earth Observation. This paper outlines the algorithms used by the RFM, focusing on standard calculations of terrestrial atmospheric infrared spectra followed by a brief summary of some additional ...
Dudhia, Anu, Dudhia, A
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Identifying customer priority for new products in target marketing: Using RFM model and TextRank [PDF]
Innovative Marketing, 2021 Target marketing is a key strategy used to increase the revenue. Among many methods that identify prospective customers, the recency, frequency, monetary value (RFM) model is considered the most accurate.
Seongbeom Hwang, Yuna Lee
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Tržište, 2023 Purpose – This paper explores various supervised machine learning algorithms as an additional classification method to RFM (recency, frequency, and monetary) models with the aim of improving the accuracy in predicting target groups of customers for ...
Danijel Bratina, Armand Faganel
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A NEW OPTIMIZED RFM OF HIGH-RESOLUTION SATELLITE IMAGERY [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Over-parameterization and over-correction are two of the major problems in the rational function model (RFM). A new approach of optimized RFM (ORFM) is proposed in this paper.
C. Li, C. Li, X. J. Liu, T. Deng
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An Extended RFM Model for Customer Behaviour and Demographic Analysis in Retail Industry
Business Systems Research : International journal of the Society for Advancing Innovation and Research in Economy, 2023 Abstract Background Customer segmentation has become one of the most innovative ways which help businesses adopt appropriate marketing campaigns and reach targeted customers. The RFM model and machine learning combination have been widely applied in various areas.
Ho, Thanh +5 more
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Deep Learning Approach for Evaluating Air Pollution Using the RFM Model [PDF]
Nature Environment and Pollution TechnologyAir pollution is a required environmental and public health issue in India, with multiple municipalities repeatedly ranking among the most polluted in the world.
Jannah Mohammad and Mohammod Abul Kashem
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Predicting Outpatient Follow-Up Retention After Inpatient Treatment in Patients With Alcohol Use Disorder: A Data-Driven Random Forest Approach. [PDF]
Addict BiolAmong 119 treatment‐seeking individuals with Alcohol Use Disorder (AUD), machine learning and regression analyses identified psychological and physiological factors predicting outpatient treatment engagement following inpatient care. Positive urgency and positive life events were the strongest predictors and were associated with fewer follow‐up visits.
Barb JJ +8 more
europepmc +2 more sources