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Modeling partial customer churn: On the value of first product-category purchase sequences

V.L. Miguéis, Dirk Van den Poel, A.S. Camanho, João Falcão e Cunha
2012 Expert systems with applications  
This paper proposes to include in partial churn detection models the succession of first products' categories purchased as a proxy of the state of trust and demand maturity of a customer towards a company  ...  Motivated by the importance of the first impressions and risks experienced recently on the current state of the relationship, we model the first purchase succession in chronological order as well as in  ...  Methodology This paper aims to predict partial churn by considering a variable length of the first-category purchase sequence for each customer, depending on whether a longer first sequence contributes  ... 
doi:10.1016/j.eswa.2012.03.073 fatcat:erxtdoacufegla23nk5wd72qny

Comparison of Deep Learning Algorithms to Predict Customer Churn within a Local Retail Industry

Alexiei Dingli, Vincent Marmara, Nicole Sant Fournier
2017 International Journal of Machine Learning and Computing  
One of the causes for a decrease in profits is when current customers stop transacting. When a customer leaves or churns from a business, the opportunity for potential sales or cross selling is lost.  ...  The Restricted Boltzmann Machine attained the best results that of 83% in predicting customer churn. Index Terms-Customer churn, deep learning, retail grocery industry.  ...  Based on this definition, [6] predicts churn for the grocery industry based on the first product category the customer has purchased.  ... 
doi:10.18178/ijmlc.2017.7.5.634 fatcat:ztotqb6gr5gprojgh7fn4wbjfi

Machine learning as intelligent tool for churn prediction in Telecommunication Industry

Megha Gupta, Anju Bhandari
2018 International Journal of Computer Applications  
Since the market is very competitive and the number of prepaid customers, "it increases, it is vital that companies to actively confront with the distraction of customers, the identification of behaviour  ...  , together with a set of real data from the open data provider to evaluate the manufacturer's productivity.  ...  It is better to focus on those who value the long-term value of products, and believes that investing in good quality is an asset. We should deal with them better.  ... 
doi:10.5120/ijca2018917621 fatcat:sklzc4zlefg65m4eclngbcmct4

Intelligent data analysis approaches to churn as a business problem: a survey

David L. García, Àngela Nebot, Alfredo Vellido
2016 Knowledge and Information Systems  
The survey is structured according to the stages identified as basic for the building of the predictive models of churn, as well as according to the different types of predictive methods employed and the  ...  This is preceded by an in-depth discussion of churn within the context of customer continuity management.  ...  AUC with separate validation data sets. [81] Purchase behaviour, seen as a sequence of the historical purchased products (grouped in 9 sets of products). Company database. Domain Knowledge.  ... 
doi:10.1007/s10115-016-0995-z fatcat:2k3c3dnh75ggnesqkrif3w6cwm

Knowledge Discovery On Investment Fund Transaction Histories and Socio-Demographic Characteristics for Customer Churn

Mustafa Adnan Merdan, Hasan Erdinc Kocer, Mohammed Hussein Ibrahim
2018 International Journal of Intelligent Systems and Applications in Engineering  
One of the most commonly used application areas of data mining is recognizing customer churn. Data mining is used to obtain behavior of churned customers by analyzing their previous transactions.  ...  In this paper, it is aimed to recognize the churned customers of a bank who closed their saving accounts and determine common socio-demographic characteristics of these customers.  ...  On the modeling of the customer churn, ordinal regression technic has used in this study for the first time.  ... 
doi:10.18201/ijisae.2018448452 fatcat:jefc2loyunbufjfaktcwswhrxi

Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals [article]

Andrew Cotter, Heinrich Jiang, Serena Wang, Taman Narayan, Maya Gupta, Seungil You, Karthik Sridharan
2018 arXiv   pre-print
We study the problem of training non-convex models subject to these rate constraints (or any non-convex and non-differentiable constraints).  ...  We provide extensive experimental results enforcing a wide range of policy goals including different fairness metrics, and other goals on accuracy, coverage, recall, and churn.  ...  Both the production regression model h and the new classifier f (x) use the same model architecture: both are RTL models that are an ensemble of 50 lattices, where each lattice acts on 6 of 16 continuous-valued  ... 
arXiv:1809.04198v1 fatcat:mvzkt5dwvzfwlava2hesyqzb64

Clustering Prediction Techniques in Defining and Predicting Customers Defection: The Case of E-Commerce Context

Ait Daoud Rachid, Amine Abdellah, Bouikhalene Belaid, Lbibb Rachid
2018 International Journal of Electrical and Computer Engineering (IJECE)  
A review of the literature on customer churning models reveals that no prior research had considered both partial and total defection in non-contractual online environments.  ...  <p><span>With the growth of the e-commerce sector, customers have more choices, a fact which encourages them to divide their purchases amongst several e-commerce sites and compare their competitors' products  ...  Partial and total churning Among the first main hurdles which face on the customers churn prediction in the non-contractual businesses is the difficulty of defining churn because the characteristics that  ... 
doi:10.11591/ijece.v8i4.pp2367-2383 fatcat:x52tycenmzb45ksmoqaiiz7lma

mbonsai: Application Package for Sequence Classification by Tree Methodology

Yukinobu Hamuro, Masakazu Nakamoto, Stephane Cheung, Edward H. Ip
2018 Journal of Statistical Software  
For example, brand purchase history in customer transaction data is in a form like AABCABAA, where A, B, and C are brands of a consumer product.  ...  The decision tree-based package mbonsai is designed to handle sequence data of varying lengths using one or multiple variables of interest as predictor variables.  ...  The development of mbonsai was part of the ERATO Minato Discrete Structure Manipulation System Project, which was funded by the Japan Science and Technology Agency, Japan (PI: Shin-ichi Minato).  ... 
doi:10.18637/jss.v086.i06 fatcat:abhoawmj5fa6rglsfdtwu7yf2a

Unsupervised Learning Framework for Customer Requisition and Behavioral Pattern Classification

Udoinyang G. Inyang, Okure O. Obot, Moses E. Ekpenyong, Aliu M. Bolanle
2017 Modern Applied Science  
K-means algorithm was used to partition the entire input space of customers' transaction dataset into 3 and 4 disjoint segments based on customers' frequency (F) and monetary value (MV).  ...  To achieve this, an in-depth analysis of customers' characteristics and purchasing behavioral trend is required.  ...  Acknowledgments This research was supported by the Tertiary Education Trust Fund (TETFund) grant.  ... 
doi:10.5539/mas.v11n9p151 fatcat:2j5uonahs5eelnilqluynugn2i

Purchase Signatures of Retail Customers [chapter]

Clement Gautrais, René Quiniou, Peggy Cellier, Thomas Guyet, Alexandre Termier
2017 Lecture Notes in Computer Science  
Both the set of products and the refilling time periods give new insights on the customer behavior.  ...  We propose the novel concept of customer signature, that identifies a set of important products that the customer refills regularly.  ...  A first one is to take product categories into account, allowing to find new types of regularities over product categories or brands.  ... 
doi:10.1007/978-3-319-57454-7_9 fatcat:ai4yzvbjprcmhox2asrpetvvvy

D6.2 – Use case description and implementation Y3

Maurizio Megliola, Stathis Plitsos, Bernat Quesada Navidad, Antoni Munar, Richard McCreadie, Anestis Sidiropoulos, Dimitris Poulopoulos
2021 Zenodo  
BigDataStack delivers a complete high-performant stack of technologies addressing the needs of data operations and applications.  ...  A toolkit allowing the specification of analytics tasks in a declarative way, their integration in the data path, as well as an adaptive visualization environment, realize BigDataStack's vision of openness  ...  & Recall Measures ROC curve, precision and recall of model recommendations (purchase / no purchase, churn / no churn) per customer / product.  ... 
doi:10.5281/zenodo.4442338 fatcat:ubk5s63g4bhlvfmmdibguyf4lq

Data Mining Using RFM Analysis [chapter]

Derya Birant
2011 Knowledge-Oriented Applications in Data Mining  
purchase, how often the customer will purchase, and what will the value of his/her purchases.  ...  The proposed model depends on the sentence "the best predictor of future customer behavior is past customer behavior".  ...  In their proposed method, sequential rules are extracted using customers' RFM values from the purchase sequences in the database.  ... 
doi:10.5772/13683 fatcat:amuirc7jlvdynjtplcparklzdy

Loyalty Analytics: Predicting Customer Behavior Using Reward Redemption Patterns under Mobile-App Reward Scheme

Yoonseock Son, Dobin Yim, Wonseok Oh
2017 International Conference on Information Systems  
The hidden Markov model is developed to capture the dynamics in latent state transitions of customers depending on the type of loyalty program used and the predictive model is used to assess the informative  ...  Using a large panel dataset consisting of 201 million transactions made by 4.9 million customers over a period of two years, we implement both the hidden Markov model and data mining approach to grasp  ...  State Path Prediction In this analysis, we predict the most likely sequence of customers' state based on the observed data.  ... 
dblp:conf/icis/SonY017 fatcat:3axklksrizfajeqwgndsi2sto4

Predicting customer retention and profitability by using random forests and regression forests techniques

2005 Expert systems with applications  
Our findings suggest that past customer behavior is more important to generate repeat purchasing and favorable profitability evolutions, while the intermediary's role has a greater impact on the customers  ...  Finally, our results demonstrate the benefits of analyzing different customer outcome variables simultaneously, since an extended investigation of the next buy-partial-defection-customer profitability  ...  Moreover, we are grateful to Leo Breiman for the public availability of the random forests and regression forests software.  ... 
doi:10.1016/j.eswa.2005.04.043 fatcat:shenpxhcdbathkxribyegeuioi

Using association rules to assess purchase probability in online stores

Grażyna Suchacka, Grzegorz Chodak
2016 Information Systems and E-Business Management  
We discuss our approach aimed at assessing a purchase probability in a user session depending on categories of viewed products and session features.  ...  The paper addresses the problem of e-customer behavior characterization based on Web server log data.  ...  Compliance with ethical standards Conflict of interest The authors declare that they have no conflict of interest.  ... 
doi:10.1007/s10257-016-0329-4 fatcat:7evjhqsjrjbirp33hs3ay4l3c4
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