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Deep Learning for Customer Churn Prediction in E-Commerce Decision Support

Maciej Pondel, Maciej Wuczyński, Wiesława Gryncewicz, Łukasz Łysik, Marcin Hernes, Artur Rot, Agata Kozina
2021 Business Information Systems  
This paper aims to develop a deep learning model for customers' churn prediction in e-commerce, which is the main contribution of the article.  ...  Also, the paper fills a research gap and contrib-utes to the existing literature in the area of developing a customer churn prediction method for the retail sector by using deep learning tools based on  ...  This paper aims to develop a deep learning model for customers' churn prediction in ecommerce. The study pertains to the prediction of customer churn in B2C e-commerce.  ... 
doi:10.52825/bis.v1i.42 fatcat:m5chpcoasfa47dn4dyn3dzt7ei

B2C E-Commerce Customer Churn Management: Churn Detection using Support Vector Machine and Personalized Retention using Hybrid Recommendations

Shini Renjith
2017 Figshare  
This paper proposes a framework based on support vector machine to predict E-Commerce customer churn and a hybrid recommendation strategy to suggest personalized retention actions.  ...  E-Commerce industry, especially the players in Business-to-Consumer (B2C) sector is witnessing immense competition for survival - by means of trying to penetrate to the customer base of their peers and  ...  In the earlier work on the B2C E-Commerce customer churn detection [17] , customer churn prediction was achieved by the use of logistic regression approach.  ... 
doi:10.6084/m9.figshare.5579482.v1 fatcat:nm7dxbqd4jh4towvdgajknk4oq

Deep Learning for Distribution Channels' Management

Sabina-Cristiana NECULA
2017 Informatică economică  
This paper presents an experiment of using deep learning models for distribution channel management.  ...  This paper will allow researchers to choose best suited techniques and features to prepare their churn prediction models.  ...  The product review plays an important role in customer's purchase decision making process on the e-commerce websites.  ... 
doi:10.12948/issn14531305/21.4.2017.06 fatcat:5tkuomqqkjcyvmtr43uo636pxu

Churn Prediction on Higher Education Data with Fuzzy Logic Algorithm

Supangat Supangat, Mohd Zainuri Bin Saringat, Geri Kusnanto, Anang Andrianto
2021 SISFORMA  
The purpose of this research is to predict whether the student will be churn or loyal in the future, the data will be taken from 2014.  ...  Of the 100 Datasets of informatics engineering, students gained 92% of loyal students, and 8% of students predicted to churn.  ...  "A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees".European Journal of Operational Research 269.2, 760-772, 2018. [22] Sivasankar, E.,  ... 
doi:10.24167/sisforma.v8i1.3025 fatcat:fat4tv2sxfbujoja32vttldggi

Customer Behavior Analysis and Revenue Prediction System

2020 International journal for research in engineering application & management  
In the era of e-commerce there are many organizations that have implemented customer behaviour analytics for their growth in business.  ...  It is a crucial challenge for the organizations in the e-commerce world to study and analyse the behaviour of the online buyers.  ...  Ankush Hutke (Information Technology) department for their support and encouragement.  ... 
doi:10.35291/2454-9150.2020.0245 fatcat:7krgx2lnxngcrpurycvkr23i2m

A Study about E-Commerce Based on Customer Behaviors

Zainab N. Mohammed, Suhad M. Kadum
2021 Engineering and Technology Journal  
E-commerce is one of the new virtual technologies that make life simpler for both traders, marketers, and customers.  ...  the works that are related to the subject of this paper to conclude and suggest the best method to predict purchasing in e-commerce treading that depends on customer behaviors.  ...  The main aim of the paper is to thoroughly review the literature discuss the previous works in the field of decision support system in e-commerce purchasing prediction based on customers previous behaviors  ... 
doi:10.30684/etj.v39i7.1631 fatcat:uifk3wgkprd5ziren3tyuexrnq

A Survey on Churn Analysis in Various Business Domains

Jaehuyn Ahn, Junsik Hwang, Doyoung Kim, HyukGeun Choi, Shinjin Kang
2020 IEEE Access  
Churn Prediction Models of this paper used deep learning for churn prediction with data timestamps in the order of seconds or with vast amounts of customer log data in total.  ...  In this study, although deep learning is part of machine learning, it is used as a new breakthrough algorithm for churn prediction problems.  ... 
doi:10.1109/access.2020.3042657 fatcat:2wtgqgsmnbcmxls36czeygvhyy

An Optimized Kernel MSVM Machine Learning-based Model for Churn Analysis

Pankaj Hooda, Pooja Mittal
2022 International Journal of Advanced Computer Science and Applications  
Customer churn is considered as a significant issue in any industry due to various services, clients, and commodities. A massive amount of data is being created from e-commerce services and tools.  ...  In this paper, an Optimized Kernel MSVM classification model is proposed to predict and classify churn. In the proposed work, MSVM algorithm has been used for classification.  ...  Based on deep learning and reinforcement learning proposed methodology will be improved in future Bayrak, A.  ... 
doi:10.14569/ijacsa.2022.0130557 fatcat:mlbc5gxz5bhmfffvffhpqsoacm

Designing a Real-Time Data-Driven Customer Churn Risk Indicator for Subscription Commerce

Alexandros Deligiannis, Research & Development Department, Apifon S.A., Thessaloniki, 570 01, Greece, Charalampos Argyriou
2020 International Journal of Information Engineering and Electronic Business  
The proposed algorithm re-computes the probability of churn for each customer at regular intervals using past purchase transaction data and incorporating subscription-based business logic.  ...  One of the main goals of customer relationship management is to reduce or eliminate "customer churn", i.e. loss of existing customers.  ...  In order to predict the customer churn, Ahmad et al. applied 4 advanced machine learning algorithms on big telecommunication data [14] : (i) Decision Tree; (ii) Random Forest; (iii) Gradient Boosted Machine  ... 
doi:10.5815/ijieeb.2020.04.01 fatcat:yzct3qepqbfjra6ly62nnk5tbm

Enhanced feature mining and classifier models to predict customer churn for an E-retailer

Karthik B Subramanya, Arun Somani
2017 2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence  
Motivation and Previous Contributions A review of Customer churn prediction approaches across various industry verticals and their efficiency motivates us to develop a new framework for churn in e-commerce  ...  We develop our own customer churn predictive model for E-commerce industry that leverages some of the advantages a Big Data infrastructure brings to the table.  ... 
doi:10.1109/confluence.2017.7943208 fatcat:iqcquinf65faxnypiy53svg6um

Customer Lifetime Value Prediction Using Embeddings

Benjamin Paul Chamberlain, Ângelo Cardoso, C.H. Bryan Liu, Roberto Pagliari, Marc Peter Deisenroth
2017 Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '17  
CLTV prediction is an important problem in e-commerce where an accurate estimate of future value allows retailers to effectively allocate marketing spend, identify and nurture high value customers and  ...  The state of the art in this domain uses large numbers of handcrafted features and ensemble regressors to forecast value, predict churn and evaluate customer loyalty.  ...  , (3) e customer churn rate. e model supports the rst two objectives by allowing ASOS to rapidly identify and nurture high value customers, who will go on to have either high frequency, high order size  ... 
doi:10.1145/3097983.3098123 dblp:conf/kdd/ChamberlainCLPD17 fatcat:vyosgrgxlvbhxkzg7ib26vikaa

A Predictive Analytics Model for E-commerce Sales Transactions to Support Decision Making: A Case Study

Shereen Morsi
2020 International Journal of Computer and Information Technology(2279-0764)  
knowledge for better decision making by precautionary measures from prediction rates and different applications that have been applied by global e-commerce firms.  ...  Therefore, this paper aims to shed light on the importance and the role of using predictive analytics models in the Egyptian e-commerce firms where these tools became dominant resources for gaining valuable  ...  and discover the reasons for customer churn, in real-time [10] .  ... 
doi:10.24203/ijcit.v9i1.3 fatcat:2wlb4kvrffbpziajx5yl3amxli

Data science in economics: comprehensive review of advanced machine learning and deep learning methods

Saeed Nosratabadi, Amir Mosavi, Puhong Duan, Pedram Ghamisi, Ferdinand Filip, Shahab S. Band, Uwe Reuter, Joao Gama, Amir H. Gandomi
2020 Zenodo  
The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models.  ...  Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency.  ...  Acknowledgments: Support of the Alexander von Humboldt Foundation is acknowledged. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.5281/zenodo.4087812 fatcat:4flgeabkxvgjrpbydfby3v6tua

Customer Churn Modeling via the Grey Wolf Optimizer and Ensemble Neural Networks

Maryam Rahmaty, Amir Daneshvar, Fariba Salahi, Maryam Ebrahimi, Adel Pourghader Chobar, Reza Lotfi
2022 Discrete Dynamics in Nature and Society  
In recent years, many methods have been developed including data mining for predicting the customer churn and manners that customers are likely to behave in the future and therefore, taking action early  ...  The customer churn is one of the key challenges for enterprises, and market saturation and increased competition to maintain business position has caused companies to make all attempts to identify customers  ...  [9] proposed a hybrid system based on feature selection methods, artificial neural networks, support vector machine, decision tree, and K-nearest neighbor to predict customer churn. e data about 3150  ... 
doi:10.1155/2022/9390768 fatcat:sz7q6jhj4bbwljjsuoyaf7b6ty

A Prediction of Customer Behavior using Logistic Regression, Naivesbayes Algorithm

Ruchita Atre, Namrata Tapaswi
2022 International Journal of Computer Applications  
In past two decades e-commerce platform developed exponentially, and with this advent, there came several challenges due to a vast amount of information.  ...  For each topic, the existing problems are analyzed, and then, current solutions to these problems are presented and discussed.  ...  PROPOSED SYSTEM Online reviews have become an important source of information for users before making an informed purchase decision. The main aspect of analyzing customer reviews on e-commerce sites.  ... 
doi:10.5120/ijca2022921904 fatcat:so7c5tvhdjdr3enh3eegz2qn3e
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