CHAPTER 3: METHODOLOGY
RESEARCH TYPE

Researchers in the business domain, specifically marketing and sales management, use qualitative and quantitative research designs to collect and analyse data. Methodologies for testing hypothesis are qualitative if non-numerical data (such as texts, video, or audio files) are used whereas the quantitative design involves numerical data, which is processed to find patterns or statistical averages. In this research, the author applies both qualitative and quantitative methods to explore key issues in under-researched problems and explain the benefits and challenges of a well-defined concept, phenomena, or activity. To achieve these objectives, the author uses questionnaires and a statistical-based method to gather and gather and analyse primary data.

A questionnaire usually contains a set of semi-structured, multiple-choice questions which research participants answer. The qualitative research method, which allows use of non-numerical data, is widely preferred due to its flexibility for researchers who need more time to develop, test and debug questions before distributing questionnaires to a large number of people. Furthermore, the context, word selection and sequence of the semi-structured questionnaire can influence how individuals interpret, tabulate, and respond to the closed-end statements showing all answers. Use of open-end questions/statements as seen in the research questions allows research respondents to answer questions using their own words thereby giving the author an insight into how the participants think. It is also relevant because the author goes further from asking why to using word selections to grasp how many people within a sample population think in certain ways. The questionnaires containing twenty (20) questions about brand awareness and intent data, including knowledge of Salesforce systems, were administered to consumers above the age of eighteen selected from different nationalities, genders, religion, educational backgrounds, and social class. The purpose is to understand their thoughts, attitudes, and expectations from technology diffusion in brand marketing. In other words, analysis on the use of intent data to increase brand awareness explores what comes to mind when consumers hear or see a brand name, logo, slogan, or certain attributes. Results from the survey were processed and factored while making inferences, conclusions, and recommendations.

CONCEPTUAL FRAMEWORKS AND SUPPORTING THEORY

A conceptual framework is used in academic studies to explain the relationship between variables. It outlines the relevant objectives of a chosen research process and maps and illustrates how variables link up to make rational conclusions. This paper therefore explores the correlation between dependent and independent variables, which may be two or more and different in nature, form, pattern, direction, strength, or relationship. The conceptual framework for this study starts with the question: “Is there a relationship between brand awareness (X) and intent data (Y)” – where X is the independent variable and Y is the dependent variable.

Figure 3.1: Theoretical Concepts

Source: The Author (2022)

According to Aaker (1991), there is a positive relationship between brand awareness and consumers’ intention to pay for goods and services. Based on the empirical research supported by other relevant studies in the business domain, the first hypothesis for this research is:

Hypothesis 1: Brand awareness has a positive correlation with purchase intention.

Brand awareness is strengthened by brand marketing, brand association and perceived quality—all of which combine to improve purchase intention, customer experience, brand equity and loyalty. Experts in sales and marketing management also agree that the success of modern-day brand awareness efforts depends on the effectiveness of digital marketing strategies. Thus, Search Engine Optimization (SEO), social media marketing, content marketing and display advertising are the bedrock of brand marketing as shown in Figure 3.2, customer purchase intention is measured through these metrics as dimensions. And the central tenet of the research model is from Lavidge and Steiner’s Hierarchy of Effects theory, which states that advertising (or brand marketing) has a significant impact on consumers’ decision to purchase or not purchase a product or services.

Figure 3.2: Dimensions in Brand Awareness and Intent Data

Source: The Author (2022)

According to the Activation Theory by Anderson (1983), business owners should focus on building an emotional connection between brands and consumers to consistently deliver an interactive and immersive journey that leaves a positive perception of a brand in consumers’ minds. This memorable experience is necessary not just to connect with consumers but to showcase the company's values and ultimately improve customer engagement. Hence the second proposition:

Hypothesis 2: Positive Brand Associations increase brand loyalty.

Through awareness, a consumer can compare two brands in the same product segment and decide on what factor or preference should a product or service gain a better rating than others. Is it perceived quality, price, brand equity emotional attachment? Hence the third proposition:

Hypothesis 3: A consumer’s evaluation of a brand is an outcome of cognitive functioning.

The study goes further to analyse the impact of social media marketing and consumers’ purchase intention with focus on education, technology savviness and access to digital devices. The author observed that brand loyalty is connected to cognitive functioning because an individual’s preference (liking0 for a product is not dependent on the tangible or intangible attributes of a brand. Using these three hypotheses, the author considers “brand awareness” an independent variable for the structural equation.

POPULATION SAMPLE AND DATA COLLECTION METHOD



REFERENCES

Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning & Verbal Behaviour, 22(3), 261–295. https://doi.org/10.1016/S0022-5371(83)90201-3
Lavidge, R. J. and Steiner, G.A., "A Model for Predictive Measures of Advertising Effectiveness," Journal of Marketing, October 1961, pp 59-62.
Aaker, D.A. (1991), Managing Brand Equity, The Free Press, New York, NY.