Case Study Advertising Effectiveness Likert

To estimate the relationship between sales and individual marketing efforts a regression analysis was performed and results are shown in Table 3. The estimated regression equation is presented below:
Table 3

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.

The results of the validation statistics of the regression equation are given in Table 4. The high value of R2 indicates that the sales as a double-log function of individual marketing efforts provide a good fit to the observed data for the brand. Since the value of the JB-statistic is less than the table value, it can be concluded that the error terms are normally distributed in this case. Further, the DW-statistic is not significant, which would lead to the conclusion that the error terms are not serially correlated in the sample data.
Table 4

Validation statistics of regression equation for Navratna

To test whether the estimated elasticities of sales with respect to the individual marketing efforts are significantly different from zero, the following hypothesis is formulated in the context of Equation (1):
H1:

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.

The results of logistic regression analysis are presented in Table 5. The estimated equation is of the form:
Table 5

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.

The validation statistics of the logistic regression equation are shown in Table 6. Results show that the G-statistic value is 38.9. Since it is significant, this would lead one to conclude that at least one of the coefficients in the model is not zero. Further, the HL-statistic value is 9.5 and insignificant in this context. This indicates that there is insufficient evidence to claim that the model does not fit the sample data adequately for the brand.
Table 6

Validation statistics of logistic regression equation for Navratna

To test where the estimated coefficients of overall customer satisfaction with respect to individual marketing efforts are significantly different from zero, the following hypothesis has been formulated in the context of Equation (2):
H2:

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.

The CSI of individual marketing efforts are presented in Table 7. Results indicate that the CSI for advertising is 0.74 for this brand. This means that customers are satisfied with the attributes of advertisement at a 74 per cent level. Furthermore, CSI is highest in the case of advertising and lowest in the case of price. Moreover, results reveal that the differences between the CSI of one effort and another are prominent in this case. This indicates that customers are not equally satisfied with the individual marketing efforts. It seems that the manager of this brand may not have formulated or implemented all the marketing efforts collectively.
Table 7

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 .

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