Abstract
Amazon is an online retail store that has manged to enhance its market situation value the use of big data. It is this large data at its disposal that normally help the management to assess the tastes and preferences of the potential customers. The same framework helps in the forecasting and decision making. There are three sets of problems that are discussed in this context. The first problem is concerned with the exploration of the survival aspects of the company in the wake of increased competition. The motivation is to asses how the management of Amazon can cope in the wake of increased levels of competition. The second problem that is discussed in this context is one that regards the manner in which the company can increase brand loyalty in the wake of increased levels of completion. Problem number three is based on the analysis of the importance of bid data that has become popular in the last few years. The motivation is towards assessing how the company is benefiting from the use of such data.
Amazon Big Data Strategy
This case is detailed description of how leading organizations can use big data resources to improve their performances. Amazon is one of the leading online stores in the world. It is one of the pioneer companies in this market segment where it started as an online book store. However, due to increased market penetrations and increased use of the internet and computer services more products have since been introduced into this platform. The company has since grown to be a major retailer in the internet.
One of the major reasons why this company has been successful in its activities is the huge database that the company has acquired over the years. The company has managed to identify different tastes and preferences of consumers based on this key database the company has used in the market. Ohlhorst (2013) argues that Amazon has utilized its big data resources to provide the consumers quality products for their services. The company has developed its customer system that enables it to detect and analyse changes in the market based on the records available in the consumer sections.
First problem: How could the company survive in an area which had never been explored by other companies in the world?
Innovations were the only way possible for the company to solve its problem. This move seemed to be working well for the company since it managed to ship products to over 45 countries around the world in its first month of operation. Many people fear to venture in areas where no other companies has ever tried to venture. Most people fear to fail; .they see that as being a high risk to take in their organization hence will not be ready to be part of the statistics. They will therefore be motivated to invest in the ideas and ventures that are deemed to be less risky and also they will not be willing to risk their money in the ventures that they are not sure about (Ohlhorst, 2013). They will be determined to ensure that they only invest if they are sure that the outcomes will be positive and thus beneficial to them since they are in most cases risk averse.
However, Amazon management was ready to venture in untapped market and solve the customers’ worries. The company amazed most of the competitors by performing well in this market. The company’s bold move shaped the entire industry as more and more firms begun selling their products online. Besides selling their products online most of the competitors begun to use big data in their services. This is an indication that Amazon was the pioneer company that was determined to risk its investment capital by putting it in the ventures that have not been verified as being credible and thus worth as at that time. The amount of success that was achieved by the company motivated many others to engage in the same line of business hoping to replicate the achievements that had been made by the company. Amazon success led to increased competition in the book market from other stores such as Book Sons and Book Stack (Anderson et al., 2010)
These move prompted the company to engage and help other stakeholders in this platform to enjoy the maximum benefits. Therefore the company introduced other companies such as Nokia. Amazon believed that by extending their line of operations and including other players such as the supplier if their products in big data, they will enhance their market size and ability to conquer the market even more. Therefore they extended the market data facility to their supplier like Nokia. In the analysis of Aguado, Feijóo & Martínez, (2015), the management of Amazon believed that customer loyalty was one of the key ways to penetrate the market. They understood that through market loyalty they would increase their market share and increase the number of customers over time.
Problem 2: How could the company increase loyalty?
In order to retain its customers, Amazon needed to ensure that there is increased brand loyalty in their services, they had to ensure that customer that uses their product will request for more products in the future. Therefore, they had the task to ensure that they have learned substantially from the customers and their activities. In many cases, understanding the customer is the best ways of predicting their brand loyalty. Many activities could have been used in this case. However, Amazon was able to use one of the best approaches that have proved to be useful from this case.
The company is using a 360 degree customer profile that has enabled the company to become one of the most successful companies in the world (Walker, 2015). Through this approach the company has managed to create a highly personalized system that engages different customers around the world. The company has used this system to improve its customer performance and enhancing the security features of its organization. The company has also managed to enable other organizations in this sector to use its bi data features to enhance their operations.
The big data strategy at Amazon is used to help both the organization and its employees. Employees can also use big data to improve the quality of their customer service. Customers have an easy access to their personal profiles as well as their business activities within the organization. Customers can track any transactions within the organization as well as provide feedback and suggestions of the services. All these features are aimed at increasing the quality of services and efficiency and performance of the organization.
One of the things that the Amazon did best was this organization was to leverage on the big data to improve its market reputation as well as enhance the customer relationships. Through understanding the needs of varied customers that were spread around the world Amazon was in a good position to provide superior services that could not be matched by the competitors in the market.
The company had established that one of the approaches that was used by this company was the cross selling methods to the clients. This method ensured that the company had tailored products and services for each customer. Apart with the items that were purchased in the store the company could, analyze the past product records the customer recommendation system was able to augment the services of this key features.
The increased quality of services increased loyalty significantly. More and more customers kept ordering through the online platform. Aguado, Feijóo & Martínez (2015) observe that Amazon did not even advertise during its first months of operation but used the word of mouth as the key form of marketing. With the advent of social media and other internet platform, the company has been able to increase the size of big data tremendously. Today the company has wide database that is able to incorporate various aspects within the business environment.
Problem 3: What is the significant of big data?
Amazon has significantly, improved its services over the years that it has been in the market. The company has established itself as being a global leader in the e-commerce platform and other services such as the internet services. Accoring to Mayer-Schönberger & Cukier (2013), the company offer services to millions of individuals around the world besides the company also provide services to corporations around the world. The company success was initiated the moment it started to focus on heavy data .The company embarked on the transitions from an online retailer to a giant company that use big data as its key strategies to penetrate the market segment.
The company alongside other major internet providers like yahoo and twitter realized that they had huge volumes of client data that they could manipulate for their own benefits. While other internet providers did not concentrate on this big data available from the consumers the company realized that it had huge potential to expand its market seize using this big data.
Therefore, Amazon was among the first companies that used big data for their benefits. The company was quick to cash in with the big data through the customer database that the company had created. Each customer who shopped on their internet platform around the world would use their personal details which were used to analyze their preferences.
The company was quick to set out a product development team that was able to analyze this data and recommend various products for the consumers. This team was also tasked to innovate different ways in which the company could use the data collected from the company to the benefit of the organization. As result the company was able to set out a big data revolution which changed the way the company approached the online retail business.
One the things that comes out clearly in this segment is that the e-commerce business is depend on the ability of the organization to provide the right products and services to the customers. The customers want a reliable organization where they can get essential goods and services. Besides the platform should be reliable and should be ready to understand the customer preferences. Therefore understanding the needs and the preferences of consumers is a key factor in the development of successful online business.
Businesses should understand the precise products and services that are needed in the organization. One of the ways through which an organization can understand the customer needs is through conducting a market research. Market research involves gathering customer information involving their purchase behaviours, locations, nature of products they purchase and the demographics (Mayer-Schönberger & Cukier, 2013). Luckily, Amazon realized that through the customer information in their platform they could easily get this information. Therefore they developed system that could monitor this system and provide clients their specific and customized products.
One of the ways through which this company was able to use this service was by recommending products and services to the consumers. Walker (2015) observes that the company as it came to be known as product “recommender” due to the number of products that the company could recommend to various people using their online platform. The company could provide suggestions on the new products available in the market that could suite individual customers based on their past purchasing records and behaviours on the online platform.
This was initially portrayed as a linkage business model where Amazon was determined to ensure that it facilitates the linking of the buyers and sellers from various parts of the world. The motivation was to come up with a market entry strategy that was motivated towards ensuring that buyers and sellers are linked in such a way that help them understand the manner in which they have get the products that they desire at the most affordable prices and in within the most convincing time frames.
All the recommendations on the online platform were as result of the data that they collected from the customer. Most customers could find this feature to be valuable since they could know about the new products that would interest them as soon as they are available online. Through other marketing services offered by the company such as discount on the links provided by the company, the customers enjoyed this platform. Many customers were satisfied hence could make more purchases from Amazon.
The expectation of the company was that with the increased number of customers being served, the management was determined to ensure that a large number of these customers had to come back and also they were poised to recommend their friends and even family members to use the services that they found to be encouraging, efficient and reliable in various aspects. Walker (2015) argues that this implied that the number of customers using the services of Amazon had to increase and that there was a determination to ensure that when they came back, they had to access services that are of extremely high quality to lock them on for the long-term.
One of the things that the company management did for this organization was to leverage on the big data to improve its market reputation as well as enhance the customer relationships. The company provided superior services that could not be matched by the competitors in the market. One of the approaches that was used by this company was the cross selling methods to the clients. Together with the items that were purchased in the store the company could, analyse the past product records the customer recommendation system was able to augment the services of this key features.
The company realized that it needed other stakeholders in this platform to enjoy the maximum benefits. Therefore the company introduced other companies such as Nokia. Amazon believed that by extending their line of operations and including other players such as the supplier if their products in big data, they will enhance their market size and ability to conquer the market even more. Therefore they extended the market data facility to their supplier like Nokia. The company believed that customer loyalty was one of the key ways to penetrate the market. They understood that through market loyalty they would increase their market share and increase the number of customers over time.
References
Aguado, J. M., Feijóo, C., & Martínez, I. J. (2015). Emerging perspectives on the mobile content evolution. Hershey, PA: Information Science Reference.
Anderson, D. R., Sweeney, D. J., Williams, T. A., Freeman, J., & Shoesmith, E. (2010).Statistics for business and economics. London: Cengage Learning.
Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Boston: Houghton Mifflin Harcourt.
Ohlhorst, F. (2013). Big data analytics: Turning big data into big money. Hoboken, N.J: Wiley.
Walker, R. (2015). From big data to big profits: Success with data and analytics. Oxford: Oxford University PressTop of Form
