Markov Chain Analysis of Brand Loyalty Predictors

Abstract

The strength of subscribers’ loyalty to selected network service providers over a period using variance analysis revealed that subscribers’ loyalty is functionally affected by Tariff Rates, Customer Service, Special recharge plans, 3G/Internet services and Network Connectivity. First order Markov Chain is used to find out the equilibrium market share of products in the present period as a basis for predicting future market shares. These factors have shown to have significant relevance to customers in terms of their preference to network brands. Though two brands lead the brand share in the market, their brand loyalties, the switching probability rate among these two brands are also significantly reflected from the markov transitional probability matrix. This is also evidently seen that the market share probability for both these two leader brands decreases while the market share for third and fourth player is increasing in the next time period. These proportions can be used as a guiding principle on future allocation purposes (i.e. optimal policy that maximizes the expected revenue of the process over a finite number of stages). From the study, it was concluded that for a profitable operation of any telecommunication network service provider, its marketing strategy must be designed to ensure that these variables; network coverage, tariff, free sms, connectivity and customer services interact optimally.