Results 11 to 20 of about 197 (159)
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
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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.
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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.
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The influence of customer value on word of mouth: a study of a financial services company in Brazil [PDF]
Revista Brasileira de Gestão De Negócios, 2018 Purpose – Our study analyzes the non-linear effect of customer lifetime value (CLV), which accounts for the revenue accumulated over the lifetime of a customer relationship, calculated using a discount rate, on customer referral value (CRV), which ...
Sandro Bonfim da Costa +2 more
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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
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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
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Customer Lifetime Value (CLV) in the Automotive E-commerce Space
International Journal For Multidisciplinary Research, 2023 Customer Lifetime Value (CLV) represents the total worth a customer brings to a business over their entire relationship. As e-commerce continues to disrupt industries, automotive companies are embracing digital platforms for vehicle sales and services, which presents new opportunities and challenges in measuring and optimizing CLV.
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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
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Customer segmentation to identify key customers based on RFM model by using data mining techniques [PDF]
International Journal of Research in Industrial Engineering, 2022 Accurate identification, attracting, and keeping the customers particularly loyal Customer Relationship Management (CRM) with the goal of optimum allotment of resources and achievement to higher profit is not a competitive profit, but it is a life ...
Abdolmajid Imani +4 more
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CUSTOMER SEGMENTATION ANALYSIS BASED ON THE CUSTOMER LIFETIME VALUE METHOD
Jurnal Aplikasi Manajemen, 2019 Companies need to understand the customers’ data better in all aspects. Detecting similarities and differences among customers, predicting their behaviors, proposing better options and opportunities tocustomers became very important for customer-company ...
edwin agung pratomo +2 more
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