Results 101 to 110 of about 3,753 (202)

Customer Loyalty Segmentation With Rfm Model At "ABC" Mart

open access: yesJurnal Ekonomika Dan Bisnis (JEBS)
In an effort to determine groups of customers who have the potential to be loyal, it is necessary to carry out a careful examination based on the characteristics of each customer in transactions. Having similar characteristics to create a customer grouping is also needed in the customer segmentation concept.
Meiriza Azwar   +2 more
openaire   +1 more source

REDD+, RFM, Development, and Carbon Markets

open access: yes, 2011
Combining responsible forest management (RFM) experiences with literature reviews and stakeholder discussions allows an assessment of the potential role of RFM in reduced emissions from deforestation and forest degradation and conservation, sustainable ...
Bastiaan Louman   +2 more
core   +1 more source

Can normalized difference vegetation index and climate data be used to estimate soil carbon, nitrogen, and phosphorus and their ratios in the Xizang grasslands?

open access: yesFrontiers in Earth Science
Accurately quantifying the relative effects of climate change and human activities on soil carbon, nitrogen, and phosphorus in alpine grasslands and their feedback is an important aspect of global change, and high-precision models are the key to solving ...
Shaohua Wang   +6 more
doaj   +1 more source

Customer Loyality Segmentation with RFM Model at PCP Cafe

open access: yesJurnal Ekonomika Dan Bisnis (JEBS)
The intense competition in the business sector motivates every business unit to manage their services, especially towards their customers, to the fullest. One of them is to increase customer loyalty by segmenting or grouping each customer into several clusters and determining the appropriate marketing strategy for each of these groups.
Rahmadeni Rahmadeni, Jerry Heikal
openaire   +1 more source

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

open access: yesJournal 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 geospatial model of RFM analysis: An application to tourism in the Iberian Peninsula

open access: yesProcedia Computer Science, 2022
Itzcóatl Bueno   +3 more
openaire   +1 more source

A Fuzzy Linguistic RFM Model Applied to Campaign Management

open access: yes, 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   +1 more
openaire   +1 more source

""Counting Your Customers" One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model" [PDF]

open access: yes
This research extends a Pareto/NBD model of customer-base analysis using a hierarchical Bayesian (HB) framework to suit today's customized marketing. The proposed HB model presumes three tried and tested assumptions of Pareto/NBD models: (1) a Poisson ...
Makoto Abe
core  

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

open access: yesScientific 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   +9 more
doaj   +1 more source

RECYCLING PROJECT WITH RFM ANALYSIS IN INDUSTRIAL MATERIAL SECTOR

open access: yes, 2020
With the advancement of technology and the widespread use of the Internet, the concept of big data, which we are often beginning to hear its name, has emerged. Big data can be briefly defined as an unstructured data stack.
Akca, Esra, Erpolat Tasabat, Semra
core  

Home - About - Disclaimer - Privacy