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Predicting Customer Lifetime Value and its underlying short-term cash flow effects

Boris-Möller, Henrik (2018) MIOM05
Production Management
Abstract
Background The intense competition in the Telecom industry makes service providers
invest heavily in acquiring new customers. In Telavox case, the majority of
these initial expenses are related to the sales process. To be profitable it is
necessary for the customers to generate a net profit during its time at Telavox
that compensates for this initial expense, i.e. a positive Customer Lifetime
Value. However, it can be difficult to predict a potential customer’s future
lifetime value.
Purpose The purpose is to broaden or review the academia’s understanding
concerning modelling and predict the CLV of customers in the Telecom
industry and investigate the short-term cash flow effects of the underlying
CLV factors.
Research questions... (More)
Background The intense competition in the Telecom industry makes service providers
invest heavily in acquiring new customers. In Telavox case, the majority of
these initial expenses are related to the sales process. To be profitable it is
necessary for the customers to generate a net profit during its time at Telavox
that compensates for this initial expense, i.e. a positive Customer Lifetime
Value. However, it can be difficult to predict a potential customer’s future
lifetime value.
Purpose The purpose is to broaden or review the academia’s understanding
concerning modelling and predict the CLV of customers in the Telecom
industry and investigate the short-term cash flow effects of the underlying
CLV factors.
Research questions What short-term effect has CLV from a cash flow perspective?
Is it possible to create a model for predicting CLV of new customers in the
Telecom industry?
What are the possibilities for detecting a change in CLV customers in the
Telecom industry?
Method A cash flow analysis was conducted based on the average Telavox customer
to investigate the short-term cash flows.
A retention model based on current literature was developed for the
characteristics of the largest segment (61% of revenues) at Telavox. The
model gives insights about the lifetime of customer cohorts from this
segment. To fully predict the CLV it is also needed to predict future revenues
and costs.
Results The payback time for an expansion was found to be significantly longer than
the payback time for a single customer. Increasing the rate of expansion will
generate a lower minimum of cumulative cash flow but will not affect the
time to reach break even.
The retention model was able to give a prediction of the lifetime of the
largest segment at Telavox. The model was not tested but a sensitivity
analysis indicated that the resulting values are reasonable. (Less)
Please use this url to cite or link to this publication:
author
Boris-Möller, Henrik
supervisor
organization
course
MIOM05
year
type
M1 - University Diploma
subject
keywords
Customer Lifetime Value, CLV, Modelling, Predicting, cash flow effect
other publication id
18/5594
language
English
id
8939247
date added to LUP
2018-05-03 14:57:32
date last changed
2018-05-03 14:57:32
@misc{8939247,
  abstract     = {Background The intense competition in the Telecom industry makes service providers
invest heavily in acquiring new customers. In Telavox case, the majority of
these initial expenses are related to the sales process. To be profitable it is
necessary for the customers to generate a net profit during its time at Telavox
that compensates for this initial expense, i.e. a positive Customer Lifetime
Value. However, it can be difficult to predict a potential customer’s future
lifetime value.
Purpose The purpose is to broaden or review the academia’s understanding
concerning modelling and predict the CLV of customers in the Telecom
industry and investigate the short-term cash flow effects of the underlying
CLV factors.
Research questions What short-term effect has CLV from a cash flow perspective?
Is it possible to create a model for predicting CLV of new customers in the
Telecom industry?
What are the possibilities for detecting a change in CLV customers in the
Telecom industry?
Method A cash flow analysis was conducted based on the average Telavox customer
to investigate the short-term cash flows.
A retention model based on current literature was developed for the
characteristics of the largest segment (61% of revenues) at Telavox. The
model gives insights about the lifetime of customer cohorts from this
segment. To fully predict the CLV it is also needed to predict future revenues
and costs.
Results The payback time for an expansion was found to be significantly longer than
the payback time for a single customer. Increasing the rate of expansion will
generate a lower minimum of cumulative cash flow but will not affect the
time to reach break even.
The retention model was able to give a prediction of the lifetime of the
largest segment at Telavox. The model was not tested but a sensitivity
analysis indicated that the resulting values are reasonable.},
  author       = {Boris-Möller, Henrik},
  keyword      = {Customer Lifetime Value,CLV,Modelling,Predicting,cash flow effect},
  language     = {eng},
  note         = {Student Paper},
  title        = {Predicting Customer Lifetime Value and its underlying short-term cash flow effects},
  year         = {2018},
}