Integration of Machine Learning Techniques to Evaluate Dynamic Customer Segmentation Analysis for Mobile Customers

01/31/2017
by   Cormac Dullaghan, et al.
0

The telecommunications industry is highly competitive, which means that the mobile providers need a business intelligence model that can be used to achieve an optimal level of churners, as well as a minimal level of cost in marketing activities. Machine learning applications can be used to provide guidance on marketing strategies. Furthermore, data mining techniques can be used in the process of customer segmentation. The purpose of this paper is to provide a detailed analysis of the C.5 algorithm, within naive Bayesian modelling for the task of segmenting telecommunication customers behavioural profiling according to their billing and socio-demographic aspects. Results have been experimentally implemented.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/03/2023

Customer Profiling, Segmentation, and Sales Prediction using AI in Direct Marketing

In an increasingly customer-centric business environment, effective comm...
research
11/18/2022

Estimating defection in subscription-type markets: empirical analysis from the scholarly publishing industry

We present the first empirical study on customer churn prediction in the...
research
09/29/2020

Towards Intelligent Risk-based Customer Segmentation in Banking

Business Processes, i.e., a set of coordinated tasks and activities to a...
research
10/25/2020

Machine Learning Based Network Coverage Guidance System

With the advent of 4G, there has been a huge consumption of data and the...
research
04/06/2023

Modelling customer lifetime-value in the retail banking industry

Understanding customer lifetime value is key to nurturing long-term cust...
research
08/27/2020

Propensity-to-Pay: Machine Learning for Estimating Prediction Uncertainty

Predicting a customer's propensity-to-pay at an early point in the reven...
research
01/25/2017

A Model-based Projection Technique for Segmenting Customers

We consider the problem of segmenting a large population of customers in...

Please sign up or login with your details

Forgot password? Click here to reset