Big Data Analytics and How it Influences Marketing Strategy - Samples

Question: Discuss about the Big Data Analytics and How it Influences Marketing Strategy and Decision-making about Strategy. Answer: 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. For achieving this, a specific process could be utilized. Big data analytics is one of the most important processes to uncover any type of hidden information by simply testing big data. This literature would be identifying the problems of the marketing strategies and decision-making about those strategies with the help of big data analytics. This literature would also provide relevant solutions to those problems and the implications. Future works would also be mentioned here. Approach Method for finding, analysing and comparing literature The method utilized for searching for literature was: i) Identification of proper key words that are solely related to the problem ii) Using Google Scholar for searching all the key words and find out Journal Articles. Several peer articles, journal articles and conference papers were searched and around twenty eight papers were eventually shortlisted. After evaluating each of these papers, twelve journal articles were selected. These papers completely define and help the literature analysis to be successful. Organizing the Literature analysis This literature analysis is organized with the following areas: i) Influence of big data analytics in marketing strategy. ii) Influence in decision-making about strategies. Scope of Literature Analysis This particular literature analysis is strictly restricted to peer reviewed journal articles. The specific research problem could be approached from several perspectives. This literature analysis mainly aims at the solutions for making marketing strategy and decision-making strategy easier and simpler for any organization. The scopes of the literature review are given below: i) Small and medium sized enterprises with mitigating marketing risks. ii) Decision making about the strategies becoming easier. Literature Analysis Problems in Marketing Strategy Marketing strategies are the significant strategies in an organization. A company for gaining their competitive advantages and maximum profit utilizes those (Pappas, 2016). However, often few problems are observed within this strategy. These problems become an important barrier in the way to the success of that organization. The major problems are as follows: i) Targeting High Value Sources of Growth: This is the first and the foremost problem in marketing strategy. High value sources of growth should be effectively targeted for any successful business (Hallbck Gabrielsson, 2013). If a company chooses the wrong target or of lesser value target, it eventually lowers the overall growth and potential of return-on-investment. ii) Dealing with Bulk Data: This is the second important problem in marketing strategy. The organizations have to collect bulk amount of data about the market for understanding their position in the market. Any type of wrong data entry can backfire their plan and their strategy would fail. iii) Slower Process of Data Analysis: Pappas, 2016 state that, the third important problem in the marketing strategy is the slower process of data analysis. The world is progressing with excess speed and every organization should know about their strengths and weaknesses with respect to analysis of data. If the process of analyzing data is slower than usual, there is a high chance that the marketing strategy would be a major failure. iv) Utilizing Insight for Shaping Strategies: The data orientation in any particular organization might reach to a high level. However, in comparison to that data, the insight might not reach to its height. New and better customers insights are highly recommendable for any marketing company. v) Decision Making: According to Hallbck Gabrielsson, 2013, this is again one of the most significant factors in the marketing strategies of any particular organization. The company should undertake the perfect decision for their business so that there exists no loophole in the undertaken strategy. Moreover, the company for gaining advantages that are more competitive as well as profit should properly execute this strategy. There are various reasons for problems in decision making in any organization (Pappas, 2016). The most significant reasons for the decision-making problem mainly include impulsiveness, risk avoidance, ignorance, halo effect, one solution threat, no follow-ups, no delegation and many more. Big Data Analytics Big data analytics is the procedure of examination of all types of varied and large sets of data or big data for uncovering any hidden pattern, preferences of customers, unknown correlations and any kind of important information (Kambatla et al., 2014). This type of analytics eventually helps the organizations in taking any type of decision. The entire concept of big data is utilized for capturing data, which are streamed into the businesses. The most significant advantages of this big data analytics is the speed and efficient. It is extremely efficient and could be easily utilized by any organization (Gandomi Haider, 2015). The most important advantages of big data analytics in an organization are as follows: i) Implementation of new Strategies: This is the most important advantage of big data analytics in a business. It helps to implement new strategies by reducing the overall complexities of data analysis. ii) Analyzing Data without Errors: As per Waller Fawcett, 2013, the data could be easily analyzed with the help of big data analytics and this could be done without errors within it. iii) Cost Effective: The third advantage of big data analytics is that it is extremely cost effective (Kwon, Lee Shin, 2014). It does not incur huge cost and could be easily afforded by all organizations irrespective of its size. iv) Better Sales Insights: Big data analytics is also responsible for bringing better sales insights within the organization. v) Easy Fraud Detection: Frauds could be easily detected and prevented with the help of big data analytics (Loebbecke Picot, 2015). These advantages has made big data analytics extremely popular and acceptable by all. Solutions to the Problems of Marketing Strategy Big data analytics can be easily termed as the significant game changer for the marketers. In todays world, the entire marketing industry is solely driven by data. Any type of erroneous or wrong data could lead a company to major losses (Moniruzzaman Hossain, 2013). The problems with the marketing strategy and the decision making about those strategies could be easily and efficiently resolved by big data analytics. According to Demirkan Delen, 2013, the probable solutions to any type of problems in marketing strategies and decision making about those strategies by big data analytics are given below: i) Conversion Optimization: This is one of the significant ways to solve the problem of marketing strategy in an organization (George, Haas Pentland, 2014). Big data analytics help the marketers to draw the statistics of their business. According to the big data analytics, 48% of the total data belongs to customer analytics, 21% to the operational analytics, 12% to fraud and compliance, 10% to new product and service innovation and the final 10% to the enterprise data warehouse optimization (Gandomi Haider, 2015). ii) Collection of Data: The big data analytics allows the organizations to collect, as much data is possible for their business (Power, 2014). There is no such restriction regarding the amount of data. The organization can collect huge amount of data and big data analytics could easily examine and analyze them. iii) Properly Timed Content: The third important solution to the problem of marketing strategy is the properly timed content (Duan Xiong, 2015). The timing and content are evenly distributed by big data analytics. For example, the email marketing platform of an organization eventually optimizes and sends time based peak activities. This is completely based on big data (Moniruzzaman Hossain, 2013). Due to even distribution of time and content, decisions could be easily taken by the organization. iv) Follows structured Analysis: There are few distinct steps in big data analytics and by following these steps, the marketers could take their decision easily (Kwon, Lee Shin, 2014). The steps in big data analytics include: a) Defining of the Problem b) Researching c) Mind mapping and Sketching d) Feedback e) Creating Digital Design f) Feedback g) Finalizing These above mentioned steps would be useful for the marketers to undertake any decision regarding marketing strategies. Implications of the Solutions These above mentioned solutions would definitely reduce the overall complexity of the problems of marketing strategy (George, Haas Pentland, 2014). Moreover, the marketers could easily take the decisions about those strategies. However, often big data analytics could also be a major threat for the organization. The main problem with this analytics is that it deals with huge amount of data and if there is any problem in the data, the entire data set would crash. Future Research Areas As per Waller Fawcett, 2013, this literature analysis suggests various areas of future work. The first significant are would be machine learning. This would be undertaking the entire world of big data analytics. The next important factor would be that the businesses would be buying algorithms, instead of software (Power, 2014). The cost effectiveness might not long last and big data analytics might be costly in future. Conclusion Therefore, from the above discussion it can be concluded that, big data analytics is the method for analyzing big data or large set of sets to help in any type of difficult and information related decision-taking situations. The marketing strategy in any particular business is the long term and forward looking approach to plan all the significant goals and objectives in a business. Often the marketers face problem in deciding the right strategy. Big data analytics plays the most significant role in this type of situation. It helps to reduce the complexity of evaluating the marketing strategies and thus make the organization successful. The above literature analysis as clearly depicted the problem of big data analytics and how this influences the marketing strategy as well as decision-making strategy. The problem statement, approach, and the literature analysis are properly given here. References Demirkan, H., Delen, D. (2013). Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud.Decision Support Systems,55(1), 412-421. Duan, L., Xiong, Y. (2015). Big data analytics and business analytics.Journal of Management Analytics,2(1), 1-21. Gandomi, A., Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics.International Journal of Information Management,35(2), 137-144. George, G., Haas, M. R., Pentland, A. (2014). Big data and management.Academy of management Journal,57(2), 321-326. Hallbck, J., Gabrielsson, P. (2013). Entrepreneurial marketing strategies during the growth of international new ventures originating in small and open economies.International Business Review,22(6), 1008-1020. Kambatla, K., Kollias, G., Kumar, V., Grama, A. (2014). Trends in big data analytics.Journal of Parallel and Distributed Computing,74(7), 2561-2573. Kwon, O., Lee, N., Shin, B. (2014). Data quality management, data usage experience and acquisition intention of big data analytics.International Journal of Information Management,34(3), 387-394. Loebbecke, C., Picot, A. (2015). Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda.The Journal of Strategic Information Systems,24(3), 149-157. Moniruzzaman, A. B. M., Hossain, S. A. (2013). Nosql database: New era of databases for big data analytics-classification, characteristics and comparison.arXiv preprint arXiv:1307.0191. Pappas, N. (2016). Marketing strategies, perceived risks, and consumer trust in online buying behaviour.Journal of Retailing and Consumer Services,29, 92-103. Power, D. J. (2014). Using Big Datafor analytics and decision support.Journal of Decision Systems,23(2), 222-228. Waller, M. A., Fawcett, S. E. (2013). Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management.Journal of Business Logistics,34(2), 77-84.