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Marketing Strategy Assignment : Big Data

   

Added on  2021-05-27

6 Pages2221 Words84 Views
Data Science and Big Data
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1-Problem Statement 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, datasharing, 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.
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2-Research Questions: Q1- How will big data analytics improve strategic marketing decisions? Research methodologyThis research question will be addressed by addressing few specific questions. Those questionsare:what does big data mean? what are the characteristics of this data? How it can be collectedand analysed? what is the value that can be provided to the business marketing strategy? Therelationship between big data analytics and improving business marketing strategy can beinferred. To answer this research question, the researcher will adopt interpretivism researchparadigm. Research paradigm is based on the source, nature and knowledge development fromthe data. In the following research study on impact of big data on the strategic marketingdecisions of the companies, the researcher will be adopting the interpretivism paradigm. In thisresearch paradigm, the researcher will analyze the data based on the observational andinterpretation 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 areal world scenario (Runeson et al., 2012). A case study company will be chosen to collectinformation on their application of big data analytics. Primary data will be collected from thecase 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 cloudcomputing 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 getthe 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 casestudy company to get an insight about the big data collection process and the software used fordata analysis, and how it adds value to the marketing decisions. New knowledgeThis 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.
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Q2- The collecting and analyzing of big data need more advanced and complex technologies andapproaches to provide more valuable information for businesses. To what extend is big data analyticsbeneficial and valuable for businesses in term of cost compare with the available technology andapproaches?MethodologyTo answer this research question, the researcher will first conduct a comprehensive literaturereview to gather knowledge about the available technologies and approaches that are used tocollect and analyze big data. The purpose of the research question is to understand theefficiency and effectiveness of the current technologies and approaches for collecting andanalysing big data. To answer this research question, the researcher will be adopting deductiveanalysis approach. The researcher will reflect upon the features of techniques of the big datacollection and analysis and their effectiveness on the strategic decisions of the companies, andnot 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 ofcomplexity 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 theone, which is collected from already published sources, such as, journals, newspapers,magazines, books, annual reports of the companies (Punch, 2013). From the websites, annualreports and other publications of the two case study companies, the researcher will gather thedata on the cost of big data collection and analysis. The cost comparison will be made by theresearcher using qualitative data analysis process. After the cost comparison, the researcherwill identify the value of the outputs of each case in terms of taking the strategic marketingdecision. A comparison between the value of information that is produced against the cost ofcollecting and analyzing it, will be made to understand the effectiveness of differenttechnologies.New knowledgeThis 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.
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