Results 11 to 20 of about 192 (158)
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
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
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
wiley +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
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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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
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.
openaire +1 more source
Discrete Dynamics in Nature and Society, Volume 2022, Issue 1, 2022., 2022 Currently, Customers are struggling to retain their business in today’s competitive markets. Thus, the issue of customer churn becomes a significant challenge for the industries. In order to achieve this, it is vital to have an efficient churn prediction system. In this paper, we discuss methods for reducing features using PCA, Autoencoders, LDA, T‐SNE,
Seyed Mohammad Sina Mirabdolbaghi +2 more
wiley +1 more source