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Modeling and Application of Purchaser Lifetime Value in
Online Retail
Abstract: This article gives an empirical statistical
evaluation and dialogue of the predictive abilities of selected customer
lifetime value (CLV) models that would be utilized in on line buying within
e-commerce commercial enterprise settings. The contrast of CLV predictive
talents, the usage of decided on evaluation metrics, is made on decided on CLV
models: Extended Pareto/NBD model (EP/NBD), Markov chain version and Status Quo
model. The article makes use of six on-line store datasets with annual revenues
inside the order of tens of millions of euros for the assessment. The EP/NBD
version has outperformed other decided on fashions in a majority of evaluation
metrics and may be considered true and stable for non-contractual members of
the family in on-line purchasing. The implications for the deployment of
decided on CLV fashions in practice, as well as guidelines for destiny studies,
also are mentioned. Keywords: carried out computing; consumer lifetime fee;
extended pareto bad binomial distribution model; Markov chain model;
advertising control; e-trade; e-save @ Read More diggblog
Abstract
1. Introduction
2. Background
3. Methodology and Data Collection
three.1. Selection of Models for Comparison and Their
Description
3.1.1. Extended Pareto/NBD Model
3.1.2. Markov Chain Model with Decision Tree Learning
three.1.Three. Status Quo Model
three.2. Data Collection and Pre-Processing
three.Three. Description of Datasets
3.Four. Evaluation Metrics
4. Results
5. Discussion and Implications
5.1. Managerial Implications
five.2. Limitations and Further Research Directions
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix A
Modeling and Application of Customer Generation Value in
Online Retail. Informatics. 2018; five(1):2.
Https://doi.Org/10.3390/informatics5010002
Jasek, Pavel, Lenka Vrana, Lucie Sperkova, Zdenek Smutny,
and Marek Kobulsky. 2018. "Modeling and Application of Customer Era Value
in Online Retail" Informatics 5, no. 1: 2.
Https://doi.Org/10.3390/informatics5010002
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