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Predicting Customer Behaviour in the Web Hosting Industry - A Study in Mathematical Modelling

Demuth, Maren LU (2018) In Bachelor's Theses in Mathematical Sciences NUMK01 20172
Mathematics (Faculty of Engineering)
Abstract
Companies want to keep their customers. Especially, when they offer subscription based services instead of one time purchases. In the former case, if customers want to leave the company, they need to cancel their subscription. This is called customer churn.

On the example of One.com, a company that offers subscription based web hosting, a mathematical model is developed to predict customer churn, so that churn preventive measures can be taken. In particular, tree based statistical learning methods such as Decision Trees and Random Forests are applied to the customer dataset of One.com and it is observed that churn predictions are made with sufficient accuracy, given that the available dataset contains information that is explanatory of... (More)
Companies want to keep their customers. Especially, when they offer subscription based services instead of one time purchases. In the former case, if customers want to leave the company, they need to cancel their subscription. This is called customer churn.

On the example of One.com, a company that offers subscription based web hosting, a mathematical model is developed to predict customer churn, so that churn preventive measures can be taken. In particular, tree based statistical learning methods such as Decision Trees and Random Forests are applied to the customer dataset of One.com and it is observed that churn predictions are made with sufficient accuracy, given that the available dataset contains information that is explanatory of churn. Then both models, Decision Tree and Random Forest, successfully deliver results that can be used for churn preventive measures on the customer base of One.com. (Less)
Please use this url to cite or link to this publication:
author
Demuth, Maren LU
supervisor
organization
course
NUMK01 20172
year
type
M2 - Bachelor Degree
subject
keywords
Mathematics, Modelling, Machine, Learning, Statistics, Customer, Churn, Random, Forest, Decision, Tree, Prediction, Model
publication/series
Bachelor's Theses in Mathematical Sciences
report number
LUNFNA-4019-2018
ISSN
1654-6229
other publication id
2018:K7
language
English
id
8936029
date added to LUP
2018-06-07 17:29:09
date last changed
2018-06-07 17:29:09
@misc{8936029,
  abstract     = {Companies want to keep their customers. Especially, when they offer subscription based services instead of one time purchases. In the former case, if customers want to leave the company, they need to cancel their subscription. This is called customer churn.

On the example of One.com, a company that offers subscription based web hosting, a mathematical model is developed to predict customer churn, so that churn preventive measures can be taken. In particular, tree based statistical learning methods such as Decision Trees and Random Forests are applied to the customer dataset of One.com and it is observed that churn predictions are made with sufficient accuracy, given that the available dataset contains information that is explanatory of churn. Then both models, Decision Tree and Random Forest, successfully deliver results that can be used for churn preventive measures on the customer base of One.com.},
  author       = {Demuth, Maren},
  issn         = {1654-6229},
  keyword      = {Mathematics,Modelling,Machine,Learning,Statistics,Customer,Churn,Random,Forest,Decision,Tree,Prediction,Model},
  language     = {eng},
  note         = {Student Paper},
  series       = {Bachelor's Theses in Mathematical Sciences},
  title        = {Predicting Customer Behaviour in the Web Hosting Industry - A Study in Mathematical Modelling},
  year         = {2018},
}