Data Analytics for E-commerce Company Introduction
Added on 2021-05-31
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Data Analytics 1Data Analytics Student nameCourseTutorUniversityDate
Data Analytics 2Data Analytics for E-commerce CompanyIntroductionBusiness organizations operate on large amounts of data that are stored on the firm’s databases (Hartmann, Zaki, Feldmann & Neely, 2014, 25). The IT departments are usually responsible for maintaining and providing business data for functional use in the companies. Consequently, most business organizations have transformed their business operations online due to the technological advancements. Thus IT personnel in the companies get involved in analyzing and predicting the business patterns of the organizations, basing on the data kept in thedatabases. Accordingly, with the internet-based operations companies rely on data analytics to develop business models that are used to predict the operations of the firms (Woerner, & Wixom,2015, 61). In using data to predict business performance, data scientists get involved in analyzingthe key operations. Data analysts work on a variety of business data to understand and determine solutions to the problems affecting the firm’s operations.The major problem affecting the performance of the e-commerce company is the decrease in profits due to increasing competition and unpredictability in customers’ expectations.This is in spite of the company leading in the market with a variety of product selections. With a wide range of product segments, it implies that the company has a vast amount of data on the sales made. Therefore, the e-commerce company needs to analyze the sales data for each productsegment and the geographic region information, so that it can improve its performance. The results of data analysis will be used in developing business models which can be employed in making decisions regarding customers and the products sold. Data analysis strategies will work out to explore the possible geographic region the company can target to add new customers and
Data Analytics 3increase the sales made. In addition, the analytics intent to innovate new business strategies and the products which should be prioritized so that it can retain more customers.BackgroundBig data refers to a collection of massive and complex data volume that comprises of huge amounts of data and data management capabilities (Anuradha, J., 2015, 321). This term was coined because of the continuous generation of information from the different emerging technologies. Researchers developed the interest in the field of big data analytics to help in stimulating economic growth as well as predicting future trends for investors (Lee, Kweon, Kim & Chai, 2017, 57). In online transactions, data analytics is based on information captured from internet clicks, social media information, and mobile transactions as well as other customer purchase transactions (Li, Xing, Liu, & Chong, 2017, 30).According to the research study by Koirala, e-commerce firms emerged as the fastest groups of businesses to adopt big data analytics (Akter, & Wamba, 2016, 180). Adoption of big data in companies led to the reduction in cost and improvement of business performance due to the vast storage and processing capacities of advanced technologies. E-commerce firms such as Amazon and Netflix rely on big data information to improve the business operations. Data captured by e-commerce firms is mainly categorized into transaction activity data, click-stream data, video data, and voice data in tracking consumer shopping behaviors (Voytek, 2017, 1231). Researchers analyzed the performance of giant retail companies and established that firms such as Amazon generated almost 30% sales through data analytics (Lee, Kweon, Kim & Chai, 2017, 978).
Data Analytics 4According to the efficient-market hypothesis, product prices reflect all information and events of the online business operations performed 9 Arthur, 2018, 42). For instances, if firms invest in big data analytics, information on the investment value gets reflected in the stock prices. Investments made in big data analysis positively affects the stock prices, therefore, leading to improved business performance (Wamba et al., 2017, 357). Several research studies indicate that companies which adopt data analytics experience improvements in business operations due to the speed of information processing.According to Faed (2013), customer relationship management can be controlled by analyzing data on online transaction platforms. Information can be captured basing on the behavioral and non-behavioral reactions of customers who engage with the business firms. Accordingly, several studies indicate that customer complaints on online platforms are crucial in improving products quality (Kwon, Lee & Shin, 2014, 390). Consequently, data captured from customer reactions can be analyzed effectively to enhance the loyalty of clients to the business.Research MethodologyIn data analytics, the whole process majors on the analysis of vast amounts of data presented. The statistical data analysis approaches are applied in studying the behavior of the market variables. In order to apply the statistical tools in data analysis, the data is modeled in a way that the responses can be explained. Thus, data generated from the statistical methods are applied in developing statistical models from which assumptions are made relating to the normality, and randomization of data.Generally, there are about seven big data analysis techniques that can be applied in developing a business model in order to predict the performance behavior (Lin, 2015, 48). These
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