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Amazon
Amazon is one of the companies with a remarkable history and marketing strategy. It is one of the largest online retailers and a notable example of successful electronic commerce based on an effective marketing strategy (Hall, 2019). Amazons case can be used to illustrate that the development of a marketing information system (MIS) is vital for the organizations success.
Novikova (2015) notes that the establishment of such a system requires the determination of customers needs, the identification of the data along with the means of its protection, and the development of a structure. The development of an MIS ensures that marketing managers receive accurate clients information timely. The example of Amazon shows that the companys ability to organize information, track fraud, and analyze the consumers behavioral patterns may allow for the improved quality of services and products.
Discussion
Another significant concept related to e-commerce is customer relations management (CRM). According to Cheng and Xu (2015), it can be utilized to obtain records, such as purchasing trends and use it to provide personalized services.
For example, Amazon works with users information to create wish lists for individuals based on their purchases. Moreover, CRM allows the company to develop advertising campaigns based on the data it collects, as the technology ensures that the organization can make suggestions about the items that customers may find interesting or useful. It is necessary to note that the development of CRM, as well as the MIS, is a complex process that requires significant investment, sufficient knowledge about the market and potential customers, and training for personnel. Moreover, the consideration of the organizational and legal aspects of data collection is also vital.
eBay
eBay is one of the most popular platforms where individuals can purchase and sell items. Currently, it has more than 175 billion active buyers and more than a billion active listings ( Who we are, 2019). It is evident that the company uses information about customers behavioral patterns to meet their requirements and provide them with a high-quality service. It allows eBay to remain competitive and influence the market by establishing a high standard of e-commerce.
Discussion
It is vital to describe how eBay uses analytics for its business in detail. Lopez (2016) notes that the organization utilizes machine learning and big data to perform A/B testing, improve the personalization of its services, and enhance merchandising. It allows eBay to recommend items to their customers based on their interests and purchases, as well as prevent risks for buyers and sellers, as well as to detect fraud and account take-overs.
It is necessary to mention that eBay also utilizes various software tools to work with big data. For example, Murphy (2016) reports that the company uses Hadoop, Storm, and Kafka for the data streams and repository. These tools allow eBay to access and query information and search tags related to metadata. The organizations example is notable as it shows what options other platforms may use to manage large volumes of data to accomplish their business goals.
Conclusion
In addition, eBays decision to collect users information utilizing the feedback system is crucial for the success of the company. The organization allows individuals to share their opinions on the products, pricing, and services. This feature helps customers to choose trusted sellers and avoid fraudsters. This example shows that eBays strategies of data analysis and collection help the company to develop trust-based relationships with its customers and make its performance effective.
References
Lopez, M. (2016). How eBay uses big data and machine learning to drive business value. Web.
Murphy, I. (2016). How eBay uses Apache software to reach its big data goals. Web.
Who we are. (2019). Web.
Cheng, F., & Xu, Z. (2015). Apparatus for customer relations management. Web.
Hall, M. (2019). Amazon.com. Web.
Novikova, E. N. (2015). Design of a marketing information system. Mediterranean Journal of Social Sciences, 6(1), 141-145.
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