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Little has been written on how customer satisfaction enhances customer retention in Tanzania’s
telecommunication companies. This study addressed that concern using six variables, namely rewards, tariffs,
customer care, branch physical appearance, network quality, and network coverage. Using probability and
non-probability sampling, 120 respondents to the questionnaire were selected. Results of descriptive and
binary regression analysis revealed customers were not satisfied due to low rewards (93.3%), high tariffs
(80.8%), unsatisfactory customer care (88.3%), uncomfortable branches (80%) and unstable network quality
(75%). Concerning predictor variables, the probability of the model giving the correct prediction ranges from
10% to 71%, where the higher deviances were tariffs, branch appearance, and network coverage (71%), and
rewards (57%). Chi square analysis, which compared the full model to a model with an intercept, found only
gender (under network quality and coverage), age, income, education, and time for reward to be statistically
significant (p<005). Furthermore, the logistic regression coefficient results showed that, for rewards,
predictor variables such as age, income, and time have positive and statistically significant effects. The study
concluded that rewards cause customer satisfaction and hence retention. However, if not well handled, high
tariffs, uncomfortable branches, poor network quality, and poor coverage lead to customer dissatisfaction
and low retention. |
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