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This study helps telecom companies in making decisions that optimize its sales points to reduce costs, also
to identify profitable customers and churn ones. This study builds two research models; physical model for
continuous mining of database where ever it resides i.e., as we have On Line Analytic Processing (OLAP)
we must have On Line Data Mining (OLDM), and logical model using Technology Acceptance Model.
Previous Studies showed that using basic information of customers, call details and customer service
related data, a model can effectively achieve accurate prediction data.
This research gives a new definition and classification for telecommunication services from the data
mining point of view. Then this research proposed a formula for total rank a shop and each term of this
formula gives a sub rank. The proposed example shows that even a shop with lower numbers of population
and visitors, it still has higher rank.
This research suggested that telecom operators has to concentrate more on their e-shopping and epayment
as it is more cost effective and use data from shops for marketing issues. Some assumptions made
in this study need to be validated using surveys, also proposed ranking should be applied on live database.