EFFECT OF MARKETING MIX ON CUSTOMER SATISACTION IN THE CASES OF EAST AFRICA BOTTLING S.C

Abstract

This study evaluates the effect of marketing mix on customer satisfaction in the case of East Africa Bottling S.C. To show this effect data is collected from participants (customers) who live in Addis Ababa. The objective of this research was to determine the effect of marketing mix on customer satisfaction in the case of East Africa Bottling S.C. The study tries to investigate the different characteristics of marketing mix elements. Also it measured the attitude towards products, price, promotion and place/ distributions were the major elements. Through Explanatory research methods and well developed questioners was conducted to the research and 200 respondent have participated who live in Addis Ababa, The participant were selected by connivance sampling technique (population size is large). Finally the data were analyzed by using “SPSS 20 version”. The results of the study indicated that the effects of products on the customers’ satisfactions were very good and the rest of the other elements were price, promotion and place/ distribution results shows average. The correlation matrix indicated that there is a strong relationship between independent variables (products, price, promotion and place/ distribution) and dependent variable (customer satisfaction). According to the Regression results the independent variables of marketing mix (Product, Price, and Place/Distribution) of the company are found to have effect on the dependent variable (Customer satisfaction). However, the promotion mix variable is not significant in this study. From the results indicated that among all the independent variables the determinant factors of most effect or contribution on the Customer satisfaction is “Product”, the β value is 0.666. In addition to these the model summary shows that the adjusted R2 is .948 which means about 94.98% of the variance in the dependent variable that is customer satisfaction was explained by the independent variables( product, price, promotion and place), and finally the ANOVA results shows , it is possible to see the overall significacet of the model. The table shows that the F-value (907.667) is significant at 0.01 level of significant (P value that corresponds to F statistics is significant). The overall model is significant enough in explaining how customer satisfaction depends on all four independent variables (product, price, promotion and place/Distribution) jointly.