The telecom industry is a highly competitive market, with frequent innovations required to sustain the business. The current business situation indicates a mismatch between user expectations and tariff plans available in the market. Furthermore, most service providers suffer from a high churn rate. The client (service provider) would therefore like to analyze the market and offer more customized plans that help to increase the retention rate. So the business objective is to develop a model to profile the customers based on their usage patterns, the activities they indulge in order to design a service plans that will cater to their areas of interest. To realize the business objective, there is a need to apply unsupervised data mining techniques on given data to bring out clusters of people with similar data-usage attributes and mobile preferences. The clusters, soidentified can then be targeted by service providers with customized data plans and contracts. Thus this help in choosing the best recommendation plans to increase the profit of the service provider and even the customers.
