The loyalty effect
(2015) FEKP02 20151Lund University School of Economics and Management, LUSEM
Department of Business Administration
- Abstract
- Authors:
Oskar Bill, Alexander Jöndell
Supervisors:
Carl-Henric Nilsson
Associate Professor
Lund University ¬ School of Economics and Management Department of Business Administration
Charlotta Johansson
Associate Professor
Lund University ¬ Faculty of Engineering Department of Automatic Control
Purpose:
The purpose is to predict customer loyalty by utilising big data. This will be done by combining two models: The American Customer Satisfaction Index (ACSI) and the Net Promoter Score (NPS) using the benefits of each model, the cause and effect relationship in ACSI and the simple survey methodology in NPS.
The findings are aimed to facilitate a work method enabling companies to use big data in order to predict... (More) - Authors:
Oskar Bill, Alexander Jöndell
Supervisors:
Carl-Henric Nilsson
Associate Professor
Lund University ¬ School of Economics and Management Department of Business Administration
Charlotta Johansson
Associate Professor
Lund University ¬ Faculty of Engineering Department of Automatic Control
Purpose:
The purpose is to predict customer loyalty by utilising big data. This will be done by combining two models: The American Customer Satisfaction Index (ACSI) and the Net Promoter Score (NPS) using the benefits of each model, the cause and effect relationship in ACSI and the simple survey methodology in NPS.
The findings are aimed to facilitate a work method enabling companies to use big data in order to predict customer loyalty to be able to pro-actively work with detracting customers and to grow future profits.
Method:
The methodology had both a quantitative and qualitative approach. By deducting a model from a theoretical analysis a linear relationship was derived between ACSI and NPS. The drivers of loyalty was then developed from a qualitative analysis and tested through a quantitative analysis of the relationships in the model.
Findings:
A relationship between the NPS and the ACSI was possible to prove. However, it was not possible to predict customer loyalty since the drivers of loyalty could not be explained with the available data and further research is therefore needed. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/5464089
- author
- Bill, Oskar LU and Jöndell, Alexander
- supervisor
- organization
- alternative title
- Predicting customer loyalty using the American Customer Satisfaction Index and the Net Promoter Score
- course
- FEKP02 20151
- year
- 2015
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Customer loyalty, Net Promoter Score, NPS, American Customer Satisfaction Index, ACSI
- language
- English
- id
- 5464089
- date added to LUP
- 2015-08-19 11:15:05
- date last changed
- 2015-08-19 11:15:05
@misc{5464089,
abstract = {{Authors:
Oskar Bill, Alexander Jöndell
Supervisors:
Carl-Henric Nilsson
Associate Professor
Lund University ¬ School of Economics and Management Department of Business Administration
Charlotta Johansson
Associate Professor
Lund University ¬ Faculty of Engineering Department of Automatic Control
Purpose:
The purpose is to predict customer loyalty by utilising big data. This will be done by combining two models: The American Customer Satisfaction Index (ACSI) and the Net Promoter Score (NPS) using the benefits of each model, the cause and effect relationship in ACSI and the simple survey methodology in NPS.
The findings are aimed to facilitate a work method enabling companies to use big data in order to predict customer loyalty to be able to pro-actively work with detracting customers and to grow future profits.
Method:
The methodology had both a quantitative and qualitative approach. By deducting a model from a theoretical analysis a linear relationship was derived between ACSI and NPS. The drivers of loyalty was then developed from a qualitative analysis and tested through a quantitative analysis of the relationships in the model.
Findings:
A relationship between the NPS and the ACSI was possible to prove. However, it was not possible to predict customer loyalty since the drivers of loyalty could not be explained with the available data and further research is therefore needed.}},
author = {{Bill, Oskar and Jöndell, Alexander}},
language = {{eng}},
note = {{Student Paper}},
title = {{The loyalty effect}},
year = {{2015}},
}