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Hypothesis one to five measured the impact of negative UGC on each dimension of CBBE, as well as CBBE overall. This was done through an experimental design where respondents CBBE was measured before and after treatment with negative UGC. Consequently, the statistical test used to test these hypotheses was a paired sample t-test. A paired sample t-test is the standard practice in experimental research designs and looks for statistical significance between the means of two groups and statistically tests if a hypothesis is supported or rejected (Kolb, 2008 p. 257). In this experiment,

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the t-test measures the same group twice: the brand perception before and after the experimental treatment. The relevant statistics to report include the p-value (to reject the null hypothesis or not), and its associated test statistic (t-value) and means. In results of the paired sample t-test, it is assumed that the data follows a normal distribution. Another assumption is that the variances of the sampled population are equal. Besides, the two samples compared in this study (brand loyal and non-loyal Meerlust customers) are independent, meaning that there is no relationship between both sampling groups.

In hypotheses six to ten, the four CBBE dimensions are used to measure the different impact on CBBE of brand loyal and non-loyal customers. Consequently, the impact of negative UGC had to first be calculated, which is done by subtracting the mean of CBBE after negative UGC, with the mean of CBBE before UGC. This was done separately for loyal versus non-loyal customers. Finally, paired sample t-tests were used to test the hypotheses as two measures (and not groups) were compared. Paired sample t-tests were thus used to compare the impact of UGC on CBBE of loyal customers, to the impact on non-loyal customers.

The specific conclusions that can be drawn from this study’s methodology are provided in the following section.

5.9 CONCLUSION

The aim of the methodology is to gain insight into the link between UGC and CBBE and to examine the relationship between the perception of brand loyal and non-loyal consumers towards customers of Meerlust before and after UGC consumption. This means that the frequency of brand loyal and non-loyal customers’ attitude patterns towards Meerlust need to be measured separately, in order to compare the difference in brand perception for both customer types. This study follows a conclusive research design that uses quantitative research techniques. Besides, this study ought to research the cause-and-effect relationship between these costumers’ attitudes towards Meerlust before and after reading negative UGC on a social medium. Therefore, a causal research design is applied to this study. Causal research examines the validity of causal relationships, which aims to determine the nature of

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the relationship between independent causal variables and the variables that established the effect of the marketing phenomenon (Malhotra and Birks, 2007, p. 79). In order to measure the causal relationship between CBBE and UGC, Aaker’s four dimensions of CBBE (1996) are used to measure brand perception prior to the cause (production of UGC) and the effect (the brand perception after reading negative UGC). All four CBBE dimensions must determine CBBE, however, the development of each dimension is also measured before and after absorbing negative UGC. This way it can be measured which dimension is mostly affected and therefore the biggest cause of possible CBBE damage.

An experimental research is the most appropriate method to apply to this study. Experimentation measures the effects of manipulation, where independent variables are manipulated that cause the marketing research problem (Shukla, 2008, p. 47). In this study, the production of UGC is the cause of the research problem and thus are manipulated by creating a fictive post on a social media platform. Only one single group of test units is exposed to this treatment which will be self-selected, since this group needs to be at least 18 years and older, know the brand Meerlust and must be regularly active on social media. It is important that the brand perception of the same Meerlust customers is measured before and after the treatment. A one-group pretest– posttest pre-experimentation is therefore the most appropriate research method for this study, since it measures one since group of test units twice and the dependent variable is taken in one single measurement (Malhotra and Birks, 2007, p. 313). The pre-treatment and post-treatment measure is the same in this study, which consists of the same questionnaire measuring brand perception.

This pre-experimental research is executed with the use of a structured online questionnaire, which is carried out and self-completed by customers of Meerlust. The online questionnaire needs to maximise the generation of insights into both loyal and non-loyal Meerlust consumers and questions are asked related to each dimension of CBBE (Aaker, 1996). The same questions are asked before and after being introduced to the treatment, so CBBE of Meerlust can be measured, based on individual brand perceptions. The goal of this structured questionnaire was to quantify data, to allow for statistical analysis. It is therefore targeted to sample at least 200 valid participants

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for the online study, where at least 100 must consist of brand loyal Meerlust customers and the other 100 are customers who are not loyal to Meerlust.

Because this study compares the degree of brand loyalty to brand perception after negative UGC, this target population of this study consists of two types of customers: brand loyal customers and non-loyal wine consumers. Brand loyal customers of Meerlust are at least 18 years old, are regularly active on social media and consist of both males and females. These customers are brand loyal, which means that they have high knowledge of wine and Meerlust, they frequently purchase Meerlust and also feel committed to Meerlust. These customers are sampled in liquor stores, wine sections in supermarkets and the UCT Wine Society is approached with the question if Meerlust consumers want to participate in the research. Meerlust customers who are not loyal to Meerlust are also 18 years or older, both male and female and are active on social media. Since these customers do not feel a commitment to Meerlust, they likely have low brand knowledge of Meerlust and purchase different wines over time. These customers are sampled in liquor stores or wine sections of a supermarket and also UCT’s Wine Society plays a part in the sampling process, where also students are asked for participation in the study.

The determination whether a customer is brand loyal or not is decided in the data analysis of the data. Questions related to brand loyalty are asked in the questionnaire, based on Aaker’s theory, which provides a clear and scientific measurement for brand loyalty. In order to make sure that both target population groups are equally represented in the questionnaire, mid-term measurements are done during data collection. The collected data regarding brand loyalty gains insight into how many questioned respondents are brand loyal and how many are non-loyal.

This study is conducted with ethical considerations. Because the treatment in the study involved an alcohol product, it was important that only persons who are at least 18 years and older were approached in the sampling process. Approached subjects were also asked for their age first before being asked if they knew the brand Meerlust. The link to the questionnaire also starts with the question if the respondent is at least 18 years or older. If not, the questionnaire was ended.

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Another ethical issue was the fictive post, which expresses negative UGC about Meerlust that never happened. Therefore, a disclaimer was added into the questionnaire, explaining that the depicted social media content is entirely fictitious and the results will be used for scientific research purposes only.

Based on the two research objectives, next chapter describes the findings of the experiment, which are presented with an analysis of descriptive and inferential statistics.

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