Big data in eBay and Amazon - Essay Example

Big data in advertising and marketing of the Table of Contents Introduction 3 Big data in eBay and Amazon 3 Optimizing customer relationships 4 Personalized advertisements 4 Qubole Data Services (QDS) 5 Familiarity with consumers 5 Search engine 5 Reaching the right consumers 6 Control to consumers 6 Optimizing digital marketing 7 Conclusion 7 References 8 Introduction Big data refers to large and complex data sets which cannot be processed by using conventional database management tools. When there is a huge set of data it becomes difficult for the traditional database system to capture and curate them. Big data software tools help in managing and processing such information within a considerable amount of time at a very high speed. Volume, variety and velocity are the three main challenges that big data software’s help in overcoming. In order to handle such huge unstructured sets of information, inductive statistic techniques and non linear system identification tools are used by big data (Arthur, 2013). Big data serves as an important tool for government authorities, science and research institutes and the private sector firms for analyzing huge sets of data for meeting consumer need and to tae strategic business decisions. The digital advertising and marketing industry has evolved highly in the past decade. It is capable of capturing unstructured data of huge volume and processes it in a manner such that valuable insights can be developed. The digital industry is capable of establishing spot trends and patterns which help in discovering new relationships and provide competitive advantages to different firms. This has created a shift in the manner in which organizations advertise and market their products or services. Big data technology enables organizations to effectively capture large volumes of data and use the same for handling bulk transactions and conducting research for developing greater market opportunities. Companies such as eBay and Amazon use the big data software systems for managing customer queries, merchandizing and to handle various types of back end operations (Arthur, 2013). Big data in eBay and Amazon eBay uses the big data system to make shopping a successful experience for its customers. The company does so by analyzing different sets of information available from the big data software’s. eBay uses two data warehouses and the Hadoop software framework for storing and clustering of information. The system used by eBay enables clustering the search for different goods, merchandising and handling customer recommendations. The objective for using such a technology is to understand the customers of the company better. Amazon utilizes the big data system to handle millions of customer and third party queries each day and to perform back end operations. The company uses Linux databases for storing and processing such huge data. Amazon uses the big data system to facilitate analyzing its target customers and their preferences. Accordingly the company develops effective marketing and advertizing tactics (Blattberg, Kim & Neslin, 2008). Optimizing customer relationships Amazon collects data about its customers and sells the same to third party companies. This acts as a marketing solution for various firms who develop their product features based upon the information about the target customers. Amazon uses big data platform to obtain information about the consumers who search for different products on their website. The data is then collected and summarized on the basis of the type of products consumers search the most, the products of specific companies which are in high demand and product features which consumers are seen to search for. Such information helps firms to detect the tastes of its target consumers and accordingly develop their marketing strategies and plans. eBay uses the big data system to manage the huge amount of information relating to its consumers from across the world. The information is used by the company for analytics purposes. The company segregates the information based on product categories and analyzes them. The objective of the company is to track the journey of its customers. The information collected is then summarized and analyzed to understand consumer needs. The company takes important strategic decisions on the basis of such information such as whether free shipping impact sales or should the company maintain low auction prices (Fung, 2013). Personalized advertisements The big data system allows organizations such as eBay and Amazon to develop personalized advertisements. Firms are seen to develop advertisements which consumers are most likely to watch. The challenge is to combine creativity with technology to attract consumers. Such advertisements are developed on the basis of the massive amounts of information obtained with the help of the big data systems. eBay utilizes the concept that personalized advertisement help influencing the target market better. The company after strategically analyzing the information obtained utilizes different media channels to advertise their services. Amazon however does not rely much upon advertising their services. Instead the company relies upon its products and gives greater priority on advertising them. The company processes the information collected from the big data systems and accordingly analyses which products are more in demand or searched by specific consumers. Accordingly product advertisements are projected to individual consumers when they are identified to access the web. Amazon relies upon the word of mouth technique to popularize its services (Hemann, 2013). Qubole Data Services (QDS) QDS provides Hadoop engine facilities which help digital advertisers to extract meaning out of a bulk of unstructured data. This gives competitive advantages to companies like eBay to gain greater product knowledge and competitive advantages. The advanced technological features provided by the QDS assists the big data system with its information processing requirements such as auto-scaling. The system helps to obtain information in a flexible and fast manner thereby reducing the turnaround time required for business users (Minelli, Chambers & Dhiraj, 2012). Familiarity with consumers One of the major advantages that big data offers e-commerce based companies such as Amazon and eBay is a chance to know their consumers. Big data sores information such as what specific consumers search and buy on the web and their locations. This facilitates firms to understand the characteristics of their target market segment and develop familiarity with them. When firms have adequate information about consumers, it is easier to market different types of products to them. Amazon is seen to utilize this concept for optimizing their selling prices. Although it is not possible for organizations to compel individuals to buy the products they come across online, but with the help of big data, it is possible for them to improve their chances of sale as there is better information regarding the prospective consumers who would buy their products (Jeffery, 2010). Search engine Online consumers rely much upon the search engine to look for their desired products. When the names of products are entered in the wrong way, many sites are seen to be unable to produce results. Amazon however updates its product searches when consumers make queries regarding products by entering the same in different ways. This improves the chances of showing results thereby raising the sales opportunities for the company. However it is not a simple task to update the manner in which particular goods are searched for in the web due to data abundance. Therefore companies like eBay rely upon big data technology for improving their search results. This increases their competitive advantages in the market (Jeffery, 2010). Reaching the right consumers In the digitalized global business environment it is seen to be extremely difficult for companies to decide which consumers should be targeted and how they must be approached. Multinational companies have their consumers spread across the globe making them diversified in terms of tastes, preferences and purchasing behavior. Big data offers firms with suitable information regarding the market patterns existing in different regions. Information regarding the types of products most popularly searched and purchased by consumers in different parts of the world is provided to the company. This helps them to strategically form their marketing plans and meet consumer need more efficiently. When organizations know what consumers need and are effectively able to deliver the same, then the chances of developing loyal customers of the brand increases (Jeffery, 2010). Control to consumers Smart retailers are keen on gathering data that reduces their marketing efforts and concurrently also helps in increasing their sales revenue. Amazon realizes the fact that not all people across the world indulge in online purchase and sales. Hence using social media channels such as television and newspaper for marketing different products will not be a suitable investment as it targets to attract the entire market. Also not all type of online shoppers shop for everything online. They are seen to buy certain classes of products. The objective of big data is to summarize information regarding the products which people purchase online, the items they search for, the aspect or features which attract them. The system also gathers information regarding the personal details of potential consumers like the frequency of their purchase, the price range they prefer, the amount they spend on an average, their location and so on. This information is then analyzed using different software’s such as Hadoop to derive meaningful data. Based on such information, firms such as Amazon advertise their products to specific consumers (Parkin, 2009). Optimizing digital marketing The digital marketing platform is different from the others. Online retailers rely much upon consumer information for advertizing their products. Other retailing firms are seen to promote their products to the entire market and therefore consumer specific information is not required by them. Online retailers such as Amazon and eBay develop their marketing strategies based upon the information provided to them through bid data software’s and applications. Big data helps such firms to develop comprehensive details regarding the target consumers and accordingly develop their marketing and sales tactics. It is possible for them to easily analyze different variable and dependent factors that influence sales. Researchers have stated that since digital marketing and advertizing technique is based upon actual facts and focuses upon reaching potential consumers directly, the affectivity of such marketing is high (Ryan & Jones, 2014). Conclusion The market forecasts and analytical results provided by big data plays a critical role in strategic marketing for companies such as Amazon and eBay. One of the primary advantages big data provides to the consumers is that, they can access a huge amount of data incurring less expense. Since the information processing time is also quick, firms can take fast actions to market their products. One of the critical challenges faced by companies who use the big data system is to provide security to the users. The cloud based system of big data facilitates large scale analytics. Research and development based upon the information obtained from big data enable companies to update existing and launch new products on a regular basis. This increases the product range for companies like Amazon and eBay, therefore being able to have a wide spread market and high revenues. (TOTAL WORD COUNT = 1760 or 7 pages; without cover page, table of contents, references) References Arthur, L. (2013). Big Data Marketing: Engage Your Customers More Effectively and Drive Value. New Jersey: John Wiley & Sons. Blattberg, R. C., Kim, P. & Neslin, S. A. (2008). Database Marketing: Theory and Practice. New York: Springer. Fung, K. (2013). Numbersense: How to Use Big Data to Your Advantage. New York: McGraw-Hill Education. Hemann, C. (2013). Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World. New Jersey: Pearson Education. Jeffery, M. (2010). Data-driven Marketing: The 15 Metrics Everyone in Marketing Should Know. New Jersey: John Wiley. Minelli, M., Chambers, M., & Dhiraj, A. (2012). Big data, big analytics: emerging business intelligence and analytic trends for todays businesses. New Jersey: John Wiley & Sons. Parkin, G. (2009). Digital Marketing: Strategies for Online Success. London: New Holland Publishers. Ryan, D. & Jones, C. (2014). Understanding Digital Marketing: Marketing Strategies for Engaging the Digital Generation. London: Kogan Page. Read More