The paper "Results of Consumer Insight " is an outstanding example of a marketing case study. This report presents the results of Consumer Insight research carried out to establish the effects of the use of photographic depiction types of food ads on consumer responses and to gain insights into foodie consumers and the marketing communications outcome for Sara Lee. The research used a 1 factor (chocolate chip cookie) × 3 factors (depiction type: image 1, image 2 and image 3) on the experimental survey. Quality control was done before and after data collection by eliminating those who did not meet the set requirements.
Data is analysed in two parts Experimental study and Foodie survey (Pitt and Ang, 2016). From the experimental study, t-tests and p-tests were done to establish if depictions influenced consumer responses. For instance, the p-value for the mean difference of image 1 vs. image 2 on AAd is p=0.400; therefore, the null hypothesis is accepted since there is no significant difference. Multiple regression was done to show if dependent variable ABrand was significantly predicted by the independent variables. The p-value for social proof is p= 0.029; social proof significantly predicts ABrand.
On the Foodie survey part, data analysed showed that the consumers are average foodies. However, the data showed that women have more interest in food than men do. This consumer insight research is necessary because it enables the researcher to identify the variables that have a concrete impact on Brand Attitude so if they are improved, they lead to successful future campaigns. 2. Evaluation of the findings Part 1: Experimental study The mean value of each consumer’ s response to each depiction was calculated and evaluated.
Independent sample t-test was done to investigate if the depiction types mean values were significantly different. Elements such as logo, brand name, and slogan were standardised since the research did not aim at investing their effects. The mean difference of; Image 1 Cookie alone vs. Image 2 Cookie bitten by a consumer, Image 1 Cookie alone vs. Image 3 Cookie shared by people and Image 2 Cookie bitten by a consumer vs. Image 3 Cookie shared by people was calculated. Correspondingly, a t-test was done to show if there was a difference between the mean values were significant t-tests whether two mean values are significantly different from zero.
The t-value of image 1 cookie alone vs. image 2 cookie bitten by a consumer on the Ad attitude was t=-0.849 which lies between -1.96< =0< =+1.96. hence, there was a significant difference at a 95% confidence interval. H0:p=0: the mean difference is not significantly different from zero. H1:p< =0.05: the mean difference is significantly different from zero. The null hypothesis was tested using p-test statistic which in this case was mean a minus mean b=0.
The p-value for image 1 cookie alone vs. image 2 cookie bitten by a consumer on Ad attitude was p=0.400. Thus, the null hypothesis was accepted since there was no significant difference. Image 1 cookie alone vs. image 2 cookie bitten by the consumer on Social proof had a p=0.064; there is no significant difference. Thus, the null hypothesis was accepted. The p-value for image 1 vs. image 3 on Ad attitude was 0.02. The mean difference was significant; thus, reject the null hypothesis.
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