Response of sales to marketing efforts of Navratna
The interpretation of this equation is that all the marketing efforts except price have positive effects on sales. The equation also suggests that a 1 per cent increase in these efforts would lead to an increase/decrease in sales for this brand. For instance, the sample elasticity with respect to advertising is 0.375. This means a 1 per cent increase in advertising would lead to an increase in sales by 0.375 per cent over the study period. Furthermore, this figure indicates that the volume of sales is moderately elastic with respect to advertising effort for this brand. Results also reveal that the partial coefficient of determination (r2) is highest for price. That is, price has the greatest impact on sales followed by salesforce, advertising, sales promotion and distribution.
Validation statistics of regression equation for Navratna
The estimated elasticity of sales with respect to each marketing effort is zero.
That is, in mathematical form, H0: βi=0 against Ha: βi>0 or βi<0.
The findings (Table 3) of the tests of the hypothesis suggest that the coefficients of individual marketing efforts such as advertising, salesforce, sales promotion, distribution and price are significantly different from zero for the brand on one-tailed tests.
Response of overall customer satisfaction to marketing efforts for Navratna
The interpretation of this equation is that all the independent variables have positive effects on log-odds, which is a function of overall customer satisfaction level. This indicates that the log-odds of overall customer satisfaction increase if the perceived customer satisfaction increases with respect to individual marketing efforts. Results also reveal that the estimated coefficients of all the marketing efforts are significant for this brand. The value of each estimated coefficient can be interpreted as the predicted change in the log-odds (function of overall customer satisfaction level) associated with one unit change in the corresponding variable, holding all other variables constant. Furthermore, the exponential constant raised to the power of the estimated coefficient represents the factor by which the predicted odds ratio changes from one when the corresponding variable changes by one unit, holding all other variables constant. For example, the multiplicative factor is 18.9 in the case of advertising. That is, the odds ratio will change from 1.00 to 18.9 for a unit increase in perceived customer satisfaction with respect to this effort. Moreover, results indicate that advertising has the greatest impact on overall customer satisfaction, followed by salesforce, distribution and price for the brand.
Validation statistics of logistic regression equation for Navratna
The estimated coefficient of overall customer satisfaction with respect to each marketing effort is zero.
That is, in mathematical form, H0: λi=0 against Ha: λi>0.
The findings (Table 5) of the tests of the hypothesis suggest that the coefficients of individual marketing efforts such as advertising, salesforce, distribution and price are significantly different from zero for the brand on one-tailed tests.
Marketing effort-wise CSI and ROI for Navratna
The results of ROI in individual marketing efforts are also shown in Table 7. Results reveal that the ROI is highest in salesforce and lowest in distribution for the brand. That is, every rupee spent on each marketing effort does not yield the same amount of ROI over the study period. It means that the formulation and implementation strategies of each effort may impact its own effectiveness as well as others.
Беккер не знал, сколько времени пролежал, пока над ним вновь не возникли лампы дневного света. Кругом стояла тишина, и эту тишину вдруг нарушил чей-то голос. Кто-то звал .