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Customer Profitability Analyses and Customer Lifetime Value [PDF]
MAB, 2015 The main objective of this paper is to compare two key approaches in the !eld of Customer Accounting (CA), namely Customer Pro!tability Analysis (CPA) and Customer Lifetime Value (CLV).
Ashok Sridhar, Michael Corbey
doaj +4 more sources
Engineering ReportsCustomer Lifetime Value (CLV) is widely used as an analytical perspective for understanding user behavior and supporting marketing decision‐making.
Long He, Di Chen, Yuhang Li
doaj +2 more sources
Journal of Computer Science and Technology StudiesCustomer Lifetime Value (CLV) is a critical metric in marketing analytics, enabling businesses to assess long-term profitability and optimize customer retention strategies. Traditional CLV models rely on heuristic approaches such as Regency, Frequency, and Monetary (RFM) analysis, but the advent of Artificial Intelligence (AI) and Machine Learning ...
null Jasmin Akter +4 more
openaire +2 more sources
Integrating Business Intelligence and CRM Systems With a Machine Learning Approach for Predictive Customer Retention in E-Commerce. [PDF]
ScientificWorldJournalIn the rapidly evolving e‐commerce landscape, retaining existing customers has become more cost‐effective and strategically important than acquiring new ones. This study proposes a data‐driven framework that integrates business intelligence (BI) tools, machine learning, and customer relationship management (CRM) decision support to improve predictive ...
Zeinali M, Ramezani Asli L, Khalili MA.
europepmc +2 more sources
Sales Forecast of Marketing Brand Based on BP Neural Network Model.
Comput Intell Neurosci, 2022 With the advancement of globalization, the market competition among enterprises has become increasingly intense. To win a good market, an enterprise must understand and grasp the laws of the market economy and accordingly predict the future of the market. Efficient market estimates are based on a careful study of various types of market data. Therefore,
Feng W.
europepmc +2 more sources
Engaging in customer citizenship behaviours to predict customer lifetime value [PDF]
, 2022 The aim of this study is to analyse the research gap of the relationship between customer citizenship behaviour (CCB) and customer lifetime value (CLV) in the customer engagement framework (CE).
Moliner-Tena, Miguel Ángel +1 more
core +2 more sources
IET Software, Volume 17, Issue 4, Page 797-808, August 2023., 2023 Abstract Retraction: [Tao Cheng, Lianjiang Li, Optimization of E‐commerce platform marketing method and comment recognition model based on deep learning and intelligent blockchain, IET Software 2023 (https://doi.org/10.1049/sfw2.12117)]. The above article from IET Software, published online on 3 February 2023 in Wiley Online Library (wileyonlinelibrary.
Tao Cheng, Lianjiang Li
wiley +1 more source
A Framework Towards Customer Lifetime Value’s Macro and Micro Dimensions in the Service Sector: A State-of-the-Art Review [PDF]
, 2023 Today, the role of customer relationship management as a strategic tool in the development of production and service organizations as well as attracting and retaining customers in competitive industries is undeniable.
Mohammad Safari,Minoo Sahebodari
core +1 more source
Ranking customers for marketing actions with a two‐stage Bayesian cluster and Pareto/NBD models
Applied Stochastic Models in Business and Industry, Volume 38, Issue 4, Page 609-619, July/August 2022., 2022 Abstract Modelling customer behaviour to predict their future purchase frequency and value is crucial when selecting customers for marketing activities. The profitability of a customer and their risk of inactivity are two important factors in this selection process. These indicators can be obtained using the well‐known Pareto/NBD model. Here we cluster
Ignasi Puig‐de‐Dou +2 more
wiley +1 more source
Application of Data Mining Methods in Grouping Agricultural Product Customers
Mathematical Problems in Engineering, Volume 2022, Issue 1, 2022., 2022 The sheer complexity of the factors influencing decision‐making has required organizations to use a tool to understand the relationships between data and make various appropriate decisions based on the information obtained. On the other hand, agricultural products need proper planning and decision‐making, like any country’s economic pillars.
Tzu-Chia Chen +10 more
wiley +1 more source