Discuss about the Business Qualitative Inquiry and Research Design.
Marketing strategy is the most important strategy for any particular business. It is responsible for all types of long-term survival of all organizations. Moreover, the decisions about these strategies often turn out to be problematic in nature. In traditional marketing, the majority of the companies rely on small data sets (megabytes to gigabytes) of their customers’ requirements with limited analytics approaches. However, the advanced technology has introduced a modern marketing strategy, which deal with Big Data (terabytes to exabytes) and has more advanced methods of analysis. Big data analytics is one of the most important processes to uncover any type of hidden information by mining, processing and analysing big data.
Big data has become the newest trend in the data science and analytics. It is referred to the sets of data that are so huge and complex that the traditional data analytics and processing software are not adequate enough the deal with these data (John Walker, 2014). There are many challenges in the big data handling, and those include the challenges in data capture, data storage, analysis, data search, data sharing, visualization, transfer, updating, querying, privacy of information and managing the data source. The major characteristics of the big data are represented through volume, variety and velocity (McAfee et al., 2012). Variability and value are newest additions to the concept of big data. The nature of the research topic, that is, the detailed aspects of big data and its impact will be analyzed in this research. It will help to get the in-depth insight into various qualitative aspects of the big data. The name itself suggests that volume is the main feature of big data. Size of the data influences the value of the data significantly. Secondly, variety represents heterogeneity of the data sources and its nature, both in the structured and unstructured manner (Provost & Fawcett, 2013). Data can be come in various forms, such as, emails, spreadsheets, pdfs, audio, videos, images etc. and all are analyzed accordingly. The variety creates challenges for mining, analyzing and storage of the data. Velocity refers to the speed of data generation to meet the demands. In case of big data, the speed of the data flow from various business processes, logs, social media and other websites, sensors etc. are considered as the velocity of the data (Chen, Chiang & Storey, 2012). Variability refers to inconsistency and value is what the data is representing after the analysis, are another two major characteristics.
This research would be identifying the problems of the marketing strategies and decision-making about those strategies with the help of big data analytics. It would explore in details the features of big data and analytics and how it adds value to the decision making solution of the companies. It would also provide relevant solutions to those problems and the implications.
This research question will be addressed by addressing few specific questions. Those questions are: what does big data mean? what are the characteristics of this data? How it can be collected and analysed? what is the value that can be provided to the business marketing strategy? The relationship between big data analytics and improving business marketing strategy can be inferred. To answer this research question, the researcher will adopt interpretivism research paradigm. Research paradigm is based on the source, nature and knowledge development from the data. In the following research study on impact of big data on the strategic marketing decisions of the companies, the researcher will be adopting the interpretivism paradigm. In this research paradigm, the researcher will analyze the data based on the observational and interpretation skills and draw inferences from the findings to reach to the conclusion (Bevir & Rhodes, 2012). Case study research design will be chosen to address this research question. Case studies help in narrowing down the horizon of the data collection and analyze those in a real world scenario (Runeson et al., 2012). A case study company will be chosen to collect information on their application of big data analytics. Primary data will be collected from the case study company by using the interview method. Laboshin, Lukashin & Zaborovsky (2017) showed in their paper that Big data is collected from various sources, especially through cloud computing storage framework and analysed using many new technologies, such as, YARN, MapReduce, Hadoop, Oracle, Spark, Hive, Kafka and many more. The researcher will try to get the information about which software the company uses for collecting and analysing big data. Qualitative analysis will be done on the interview responses from the employees of the case study company to get an insight about the big data collection process and the software used for data analysis, and how it adds value to the marketing decisions.
This research can explain what is the value that is produced by big data analytics when it is used in strategic marketing decisions as a main source of data, and how the quality of the decisions can improve.
To answer this research question, the researcher will first conduct a comprehensive literature review to gather knowledge about the available technologies and approaches that are used to collect and analyze big data. The purpose of the research question is to understand the efficiency and effectiveness of the current technologies and approaches for collecting and analysing big data. To answer this research question, the researcher will be adopting deductive analysis approach. The researcher will reflect upon the features of techniques of the big data collection and analysis and their effectiveness on the strategic decisions of the companies, and not generate any new theory as in case of inductive approach (Neuman, 2014). Hence, deduction of the observations from the findings will be suitable to explore the research topic. Two case study companies will be chosen in this case, one with big data with high level of complexity and volume, and the other with big data with low level of complexity and volume. Secondary data will be collected for answering this research question. Secondary data is the one, which is collected from already published sources, such as, journals, newspapers, magazines, books, annual reports of the companies (Punch, 2013). From the websites, annual reports and other publications of the two case study companies, the researcher will gather the data on the cost of big data collection and analysis. The cost comparison will be made by the researcher using qualitative data analysis process. After the cost comparison, the researcher will identify the value of the outputs of each case in terms of taking the strategic marketing decision. A comparison between the value of information that is produced against the cost of collecting and analyzing it, will be made to understand the effectiveness of different technologies.
This research can identify the efficiency level of some available approaches and technologies that are used in big data analytics. This could find out a clear relationship between the cost of investing in big data analytics and the returned value of this investment.
The purpose of this research question is to identify the differences of information that is produced for businesses by small data analytics and big data analytics. It also aims to evaluate how the level of accuracy of information for both methods can be determined, and how the decision of using this information as a main source during creating the marketing strategy can be taken logically. To address these factors, the researcher will be exploring the previous literatures and research papers to gather knowledge about the data accuracy rate measures that are available and used to measure big data accuracy level. This would help to determine which accuracy rate measure should be chosen in this research. Once again, two case study companies will be chosen by the researcher; one with small data analytics and the other with big data analytics. Secondary data on the accuracy of the data analytics will be collected from the case study companies and will be compared using qualitative or descriptive research method. The researcher will collect the accuracy rate of the small data analytics and big data analytics from the two case study companies and will compare the outputs. Qualitative study will be helpful in this case as only the comparison of the outputs need to be made and the quantitative calculations are not required (Lewis, 2015). By comparing the output, the researcher aims to find out the most precise method to get the most accurate solution, that would improve the quality of strategic marketing decision making of the companies.
This research can find out the data accuracy level that is produced by big data analytics and small data analytics, which are used in marketing strategy and decision making.
The third research question among the three has the most significance for the research problem. The importance of big data analytics lies in the accuracy of decisions. The strategic marketing decisions are made by the companies to capture a bigger share in the market and increase their profitability. For that accurate customer and sales data are required, and the larger the dataset, the wider will be the impact on creating a vision about the market size and market condition. The features of big data, the available technologies and cost effectiveness can be sourced from previous literatures; and cost effectiveness of the big data collection and analysis depends on the size of the company. Thus, to have the most impact on the strategic marketing decisions by the companies, the accuracy of the data analytics is important. If the analysis is not accurate, the company might make a wrong decision. Hence, the third question is most impactful in conducting this research.
References
Bevir, M., & Rhodes, R. A. (2012). Interpretivism and the analysis of traditions and practices. Critical policy studies, 6(2), 201-208.
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: from big data to big impact. MIS quarterly, 1165-1188.
John Walker, S. (2014). Big data: A revolution that will transform how we live, work, and think.
Laboshin, L., Lukashin, A., & Zaborovsky, V. (2017). The Big Data Approach to Collecting and Analyzing Traffic Data in Large Scale Networks. Procedia Computer Science, 103, 536-542. https://dx.doi.org/10.1016/j.procs.2017.01.048
Lewis, S. (2015). Qualitative inquiry and research design: Choosing among five approaches. Health promotion practice, 16(4), 473-475.
McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: the management revolution. Harvard business review, 90(10), 60-68.
Neuman, L. W. (2014). Social research methods. Pearson Education Limited.
Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big data, 1(1), 51-59.
Punch, K. F. (2013). Introduction to social research: Quantitative and qualitative approaches. sage.
Runeson, P., Host, M., Rainer, A., & Regnell, B. (2012). Case study research in software engineering: Guidelines and examples. John Wiley & Sons.
Essay Writing Service Features
Our Experience
No matter how complex your assignment is, we can find the right professional for your specific task. Contact Essay is an essay writing company that hires only the smartest minds to help you with your projects. Our expertise allows us to provide students with high-quality academic writing, editing & proofreading services.
Free Features
Free revision policy
$10Free bibliography & reference
$8Free title page
$8Free formatting
$8How Our Essay Writing Service Works
First, you will need to complete an order form. It's not difficult but, in case there is anything you find not to be clear, you may always call us so that we can guide you through it. On the order form, you will need to include some basic information concerning your order: subject, topic, number of pages, etc. We also encourage our clients to upload any relevant information or sources that will help.
Complete the order form
Once we have all the information and instructions that we need, we select the most suitable writer for your assignment. While everything seems to be clear, the writer, who has complete knowledge of the subject, may need clarification from you. It is at that point that you would receive a call or email from us.
Writer’s assignment
As soon as the writer has finished, it will be delivered both to the website and to your email address so that you will not miss it. If your deadline is close at hand, we will place a call to you to make sure that you receive the paper on time.
Completing the order and download