ANALYSIS OF DATA MINING TECHNIQUES OF TELECOMMUNICATION COMPANIES IN NIGERIA

Abstract

This study applied a data mining model in sales and marketing
department of Telecommunication Industry (TI) in Nigeria. The
motivation behind the paper is as a result of competitive
challenges facing most TI sales and marketing departments
globally such as inability in gaining precise view of targeted data,
inability to translate and formulate business question correctly and
Problem of addressing data quality. The aim of this research work
is to develop and implement a model that would be used to retain
existing customers, attract new ones, effectively manage and
allocate resources, goods and services in TI. The data mining
techniques used were classification, association, sequence
discovery, visualization and prediction. The tools used to
implement the model were PHP, JavaScript, CSS and HTML.
Telecommunication Service Providers (TSP) considered were
Mobile Telephone Networks (MTN), GlobaCom (GLO), Airtel and
emerging telecommunication markets (EMTs) also known as
Etisalat. Three products on sales and marketing department of TI
such as Airtime, Electronic Recharge (e-top up) and SIM card
sales were considered. The training data used for model
exploratory analysis range from 2008 to 2015 (eight years) and
was collected from historical sales records of EMTs. The data
were cleaned and transformed. The enhanced system was
achieved through the implementation of the model which proves to
be more efficient than the existing system. The model
implemented was able to extract relevance information from
database of TI and makes sales forecast for subsequent year.
Therefore the system is recommended to be used by the TI to
enhance their productivity

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