E-Business Applications

Table of Contents

Introduction.

Discussion.

Brief Overview of the current operation.

Importance of Artificial Intelligence.

How the business uses Artificial Intelligence.

Recommendations on better use of internet technologies.

Conclusion.

Reference list.

Introduction to Building Trust in Artificial Intelligence

Artificial intelligence is a growing trend in the ever-changing world of business. AI is a method of providing any business with smart and innovative solutions. It also provides valuable elements to several e-commerce networks to remain competitive in the market. Artificial intelligence is improving boring work patterns by improving brand performance and user experience. There is a constant competition in the e-commerce industry to satisfy the changing demands of customers and therefore most of the enterprises are implementing AI in their businesses. Using AI in e-commerce stores has enhanced the standard of marketing. AI has provided the users with several modern technologies and experiences starting from voice assistants to chatbots to even visual search engines. This evolution has enhanced the customer experience and provided the e-commerce industry with better and innovative solutions (Castelli et al. 2017). The visual search engine introduced by Artificial intelligence is a stimulating trend where customers can explore their desires with just a click. The voice assistant provided by AI has provided smooth user experience and this is used by several large e-commerce companies for improved recommendation and analysis (Corbato et al. 2018). Voice assistants in the e-commerce platform also provide humane and personal experience in online shopping. Amazon is one such e-commerce platform that uses AI and machine learning to improve customer experience and improves the business efficiencies. The business not only uses AI for improving customer satisfaction levels but also uses it internally. The e-commerce giant uses AI in several aspects of its business such as improving customer search, delivery, analyze purchasing patterns and many more. AI is used by Amazon for product recommendation based on the products that the customer has already liked. AI is integrated into all the aspects of the company that has helped it to rise in the top of several e-commerce platforms successfully.

Discussion on Building Trust in Artificial Intelligence

Brief Overview of The Current Operation

Amazon is a multinational tech enterprise that revolved around e-commerce, digital streaming, and cloud computing and artificial intelligence. The company was founded by Jeff Bezos in 1994 initially as a bookselling website and has its headquarters in Seattle, Washington. It rapidly expanded to apparel, furniture, food, toys, electronics and all requirements. The company is recognized as an industry that has massive technological innovations. The firm distributes steaming and downloads of music, video, audiobooks with the help of Amazon prime video, prime music, audible subsidiaries. The firm also maintains a publishing firm namely “Amazon publishing”, and also “Amazon studios” which is a television and film studio. Apart from these, the enterprise also maintains “Amazon web services”, which is a cloud computing part. The company manufactures electronics like Fire tablets, Fire TV, Kindle e-readers and also Echo devices. The company also has several subsidiaries namely Twitch, IMDb, Ring, and Whole Foods Market (Li and Liu, 2016). The e-commerce platform occupies a leading position in the e-commerce industry due to the improved e-commerce and cloud computing services that generates $937.75 billion and also involves 750,000 workers. The company mainly sells items to customers directly. This is performed by Amazon or through third-party retailers. The company also maintains a subscription to Amazon prime that provides the users to get quicker shipping and also access to media. The e-commerce store also has a small electronics product line. Amazon sells a variety of items on the website. The company uses a traditional buyer-to-seller method where there is a large variety of items. Apart from the huge product range, the e-commerce store also includes different customizations to improve the buyer experience. The marketing techniques of the company are unique and therefore help the company to successfully understand the experiences and details of each customer. Customer tracking is an important part of the company that improves the shopping experience and makes recommendation according to past purchases and guides ad reviews of other users (Correll et al. 2016). The “multi-levelled e-commerce strategy” that is used by the company provides it with an edge from other e-commerce stores and makes the operations of the company vast. The website allows any individual to sell their products. The website has direct merchandise and also products that are listed by third-party sellers and enterprises like Target. The operations of the company also provide unique selling experiences. The e-commerce store is used by both retailers and individuals. Large retailers like Land's End and Target and so on make use of the company for selling their items apart from selling those in their company website. Small sellers also use the company through “Amazon Auctions”, “Amazon Marketplace”. Therefore with the help of these operations, the company widens its product range and also offers a marketplace for large and small sellers (aboutamazon.com, 2020). [Referred to Appendix 1]

As an online seller, Amazon has the greatest inventories for products. The company carries on huge warehouses referred to as fulfilment centres. Apart from the products that are directly sold by the company, third party sellers can also sell products on the website. These products can be both old and new and are also stocked in the fulfilment centres. The website is made open to retail sellers that benefit the company on many levels. Amazon can keep a track of the products that are sold by the partners and decide to sell similar products at a low cost through the name of the company, or can also allow the retailers to operate on the website with no competition (aboutamazon.com, 2020).

Importance of Artificial Intelligence

Generating 35% of the product revenues, cross-selling and up-selling are the major activities of the e-commerce platform. The product suggestion technology of Amazon is mainly driven by AI. AI in the e-commerce platform is used by online retailers to offer chatbot services, provide customized services to online users and to analyse customer comments. It is reported that 1 in each 5 users purchases an item from a chatbot and 40% of users looks for great offers and promotions from chatbots. It is also predicted that 80% of customer interactions will be managed by AI technologies. AI is important to further successful operations of Amazon as it can help in predicting the shopping trends according to the items that are bought by users and also the time when they can make the purchase. AI is important in the functioning of Amazon as it helps the company to collect and evaluate the data in real-time and this allows an efficient business functioning, the e-commerce platform with the help of AI can provide 24*7 customer support by using chatbots (Smith and Linden, 2017). These chatbots were earlier used for traditional replies, but have evolved as intelligent creatures which can understand any issue faced by customers. Chatbots are also available on the website for helping customers in making shopping decisions. It is also provided in the app so that the customers can interact with the seller and help them in the purchasing decision. The bots interact with text, speech or even both. CRM is not used as a human resource base. Amazon used AI for going through huge amounts of data for precisely determining the clients who can make a purchase decision and therefore offer improved services to the users and secure the engagement. With improved CRM solutions, Amazon can improve accuracy so that the teams in the company can develop long term relationships with customers. Coordination helps in better functioning and IoT offers connectivity in all the components. E-commerce produces sales. AI allows the whole customer journey starting from identifying a potential consumer to depicting after the purchase is made. AI can also be used for generating precise revenue predictions for the dales managers at a lower level by offering an easy understanding of sales trends (Vanneschi et al. 2018). Amazon can optimize resource allocation for offering a healthy supply, tracking the team performance and the goods which can, in turn, result in cost-effective outcomes. AI also is important to Amazon as it provides a flawless consumer experience. The essential data is kept on track and excellent outcomes are delivered. AI also provides an exceptional and reliable user experience at each touchpoint. AI leads to effective "product content management”. AI offers retail giants like Amazon with the chance to deliver according to the demands of the customers. By using AI the e-commerce platform can connect with customers. It is also helpful in saving them time and reduces any frustration of changing minute details or repeating any process (forbes.com, 2020).

How the Business Uses Artificial Intelligence

Amazon uses AI in predicting the number of customers who are interested to make a new purchase and also to manage a cashier-less store. The AI capabilities of the e-commerce giant are made for offering customized recommendations to the users. Reports suggest that the recommendation engine of the company that is based on AI drives 35% of the entire sales. Amazon also uses AI for understanding the customer search queries and understanding the reason behind finding a specific item. Understanding the reason behind why a customer is looking for a specific item can assist the company to suggest matching products to the users and Amazon solves this issue by efficiently using AI (Herbrich, 2017). Amazon uses machine learning and AI for improving the quality of search outcomes on the website that increases the complete shopping experience. The e-commerce giant uses AI to recognize the best matches made in the context of the use of a customer. The system of the algorithm makes predictions based on searches like "Adidas pants" and shows results like “running”. Making predictions in the intention of search is an essential element of data retrieval which helps in enhancing the significance of the results by having a complete understanding of the user intents and query keywords.

Amazon uses AI also to improve warehouse operations. AI-powered technology is used in one of the most important components of the business which is delivery and is entirely reliant on flexible warehouse operation. The team behind operations at Amazon uses computer vision and evaluates the images that track the locations of each item across the warehouses. The fulfilment centres of the e-commerce giant are completely utilized through autonomous robots, control software, commuter vision, machine learning, and language perception and so on. The company evaluates the journey of each of the product so that the fly can be optimized. The store uses AI-powered robots. They can learn with the help of algorithm in real-time determining the location of the order, the probable time and the way to make the order reach fast (Irani, 2015). Artificial intelligence is also used by the company in determining the amount of a particular item a customer can buy. The company uses “Pegasus” which is an “item categorizing system” that can eliminate the problem of wrongly sorted items by half. “Xanthus” is another application used by the company adapts to modern apps and helps in carrying several forms of cargo (Albayrak et al. 2018).

Amazon’s approach to using AI is referred to as flywheel. This approach in the company keeps AI working along and also motivates the spread of knowledge and energy to other parts of the enterprise. The flywheel approach suggests that the innovation revolving around machine learning in one part of the firm improves the efforts of other parts. The teams can use technology for improving the products that in turn affect innovation in the organization. Amazon is known as the first company to use AI in its operations for improving product recommendations (Siau and Wang, 2018). The flywheel approach is seen as the crucial aspect of working as there is a development in machine learning and AI. AI is not situated at a specific office in the company; it is distributed throughout several departments. Machine learning is used for product recommendations for enhancing item forecasts. Machine learning and AI of the company powers the popular products of Amazon, namely Amazon go the store, Alexa and recommendation engine (Reis et al. 2018). The “Amazon echo” that attributes “AI bot Alexa” is one of the popular items that feature machine learning. Alexa is a voice-powered virtual assistant that the company can use for different products. Alexa can be integrated with prime video, Amazon music and customized recommendations for products from Amazon account. The Amazon Go store can also keep a track of the shopping trends of the customers. Information is collected from the smartphone cameras that track the shopping preferences which assist Amazon Go and also can be distributed with the machine learning team. AI also has a crucial part in the recommendation engine of the company that produces 35% of the revenue of the organization. Data is used from the personal preferences of users, browsing history and recent purchases and a personalized list of items are suggested to the customer. Data from Amazon Go, recommendation engine and Alexa are collected for creating a cohesive customer experience. A user can visit Amazon go and select product or dinner and ask Alexa for recommending any unique recipe and the recommendation engine can predict the items that the user can need. Therefore an innovative and personalized customer experience is provided based on AI (Liu et al. 2016). [Referred to Appendix 2]

Alexa is a personal assistant for the drivers who receive the information regarding the packets, and routes. There are also electric-powered delivery cars that have built-in Alexa. The firm builds up new robots and designs current ones to include more automation and smart algorithms in the fulfilment centres. The company also introduced “Prime Air service” that uses electric drones for delivering orders (Jackson and Orebaugh, 2018). These are AI-powered and can carry packets that are less than 5 pounds to desired locations. Amazon uses AI for redesigning supply and improving data by automating the capacity to understand customer requirement, estimating product availability, improving delivery routes and also customizing interaction with users while keeping a track of the entire supply chain. Amazon web services have more than 175 services made for storage networking, IoT, AI and so on. [Referred to Appendix 3]

Recommendations on Better Use of Internet Technologies

  • Visual search- Amazon can use the visual search on the website for improving the search results. This can help in recognizing pictures with artificial intelligence. With the help of visual search, customers can take an image and use it to search for similar items. This can work with artificial intelligence and does not only function with photographic recognition. The suggestions and search results also consider the factors of price category, brand, and also several customer reviews (Polacco and Backes, 2018). For recognizing clothing items, the technology can use machine learning with the help of artificial neural networks which imitates the factions of a human brain. This can help the e-commerce platform to increase the number of influencers.
  • Recommendations for users- with the help of AI, Amazon can intelligently scan through huge amounts of data for predicting the behaviour of customers and provide suitable and useful recommendations to the customers in person. The level of intelligence is essential to deliver a personalized shopping experience. Amazon can use AI to place orders with messaging or voice command. The algorithm can use several inputs comprising of account information, purchase history, customer likings and also third party data. This can allow the retail giant to develop and deliver better-customized messages and suggestions for the users (Lee et al. 2017). Amazon can make use of “hyper-personalization” is facilitated by understanding real customer behaviour and make estimations with data that is gathered from user activities on the desktops or smartphones. 
  • Virtual personal shoppers- AI can be used by Amazon for developing purposely built “shoppers’ that can help the users online. In-store shopping has several advantages, such as the customers can maintain a direct conversation with the seller and ask regarding any doubts. These advantages are restricted in online shopping as users need to go through the tedious process of ticking boxes for getting products that are according to their choices. The company can develop a human brain like abilities for selling smarter to the huge registered online buyers (Lee et al. 2017). The virtual shopping assistants can help in simplifying mobile shopping and offer customers with important products and deals that are tailored according to the choices.
  • “Assortment intelligence” tool- customers want retailers to alter pricing strategies. Therefore it is important that the retailers use flexibility in the price structuring for retaining customers. Amazon can use assortment intelligence which can smooth the progress of an extraordinary level of constant visibility and provide crucial insights to the product assortments of competitors. Amazon can monitor the product mix of the competitors so that it can adjust the product mix and change the pricing strategy accurately (Hernandez et al. 2016).
  • Improving dialogue systems- Amazon can start using AI to solve issues seen in dialogue systems like speech recognition, question answering, and language understanding and so on. Amazon can use deep learning for converting speech that is said by users to text accurately. The issue of responding to questions can be solved by Amazon by using AI by using the content that is seen in website pages like customer reviews and product descriptions (Hernandez et al. 2016).

Conclusion on Building Trust in Artificial Intelligence

Amazon is known for the innovative use of AI in several aspects of working. It not only uses AI for improving product recommendations but also uses it in delivery processes, improving user experience and providing assistance while shopping. With the effective use of AI, the e-commerce platform has generated 35% of the total sales. Amazon uses AI for looking through an enormous quantity of data for accurately understanding the consumers who can make a buying decision and consequently present better services to the users and protect the engagement. Amazon makes use of machine learning and AI for enhancing the superiority of exploring results on the website that boosts the absolute shopping experience. The e-commerce platform uses AI to distinguish the best equivalent made in the context of the use of a customer. The company has improved the user experience since the first time it used AI on its website. However, it still needs to use improved technologies for improving the user experience and to compete in the ever-changing business environment.

Reference List for Building Trust in Artificial Intelligence

aboutamazon.com, (2020), How artificial intelligence helps Amazon deliver, available at: https://www.aboutamazon.com/innovation/artificial-intelligence, accessed on: 25.9.2020

Albayrak, N., Özdemir, A. and Zeydan, E., 2018, May. An overview of artificial intelligence based chatbots and an example chatbot application. In 2018 26th Signal processing and communications applications conference (SIU) (pp. 1-4). IEEE.

Castelli, M., Manzoni, L., Vanneschi, L. and Popovič, A., 2017. An expert system for extracting knowledge from customers’ reviews: The case of Amazon. com, Inc. Expert Systems with Applications, 84, pp.117-126.

Corbato, C.H., Bharatheesha, M., Van Egmond, J., Ju, J. and Wisse, M., 2018. Integrating different levels of automation: Lessons from winning the amazon robotics challenge 2016. IEEE Transactions on Industrial Informatics, 14(11), pp.4916-4926.

Correll, N., Bekris, K.E., Berenson, D., Brock, O., Causo, A., Hauser, K., Okada, K., Rodriguez, A., Romano, J.M. and Wurman, P.R., 2016. Analysis and observations from the first amazon picking challenge. IEEE Transactions on Automation Science and Engineering, 15(1), pp.172-188.

forbes.com, (2020), How Amazon Has Reorganized Around Artificial Intelligence And Machine Learning, available at: forbes.com/sites/blakemorgan/2018/07/16/how-amazon-has-re-organized-around-artificial-intelligence-and-machine-learning/#4c0b80457361, accessed on: 25.9.2020

Herbrich, R., 2017, February. Machine Learning at Amazon. In WSDM (p. 535).

Hernandez, C., Bharatheesha, M., Ko, W., Gaiser, H., Tan, J., van Deurzen, K., de Vries, M., Van Mil, B., van Egmond, J., Burger, R. and Morariu, M., 2016, June. Team delft’s robot winner of the amazon picking challenge 2016. In Robot World Cup (pp. 613-624). Springer, Cham.

Irani, L., 2015. Difference and dependence among digital workers: The case of Amazon Mechanical Turk. South Atlantic Quarterly, 114(1), pp.225-234.

Jackson, C. and Orebaugh, A., 2018. A study of security and privacy issues associated with the Amazon Echo. International Journal of Internet of Things and Cyber-Assurance, 1(1), pp.91-100.

Lee, D.Y., Jo, J.C. and Lim, H.S., 2017. User sentiment analysis on Amazon fashion product review using word embedding. Journal of the Korea Convergence Society, 8(4), pp.1-8.

Li, J.T. and Liu, H.J., 2016. Design optimization of amazon robotics. Automation, Control and Intelligent Systems, 4(2), pp.48-52.

Liu, G., Nguyen, T.T., Zhao, G., Zha, W., Yang, J., Cao, J., Wu, M., Zhao, P. and Chen, W., 2016, August. Repeat buyer prediction for e-commerce. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 155-164).

Polacco, A. and Backes, K., 2018. The amazon go concept: Implications, applications, and sustainability. Journal of Business and Management, 24(1), pp.79-92.

Reis, L.P., de Souza, A.L., dos Reis, P.C.M., Mazzei, L., Soares, C.P.B., Torres, C.M.M.E., da Silva, L.F., Ruschel, A.R., Rêgo, L.J.S. and Leite, H.G., 2018. Estimation of mortality and survival of individual trees after harvesting wood using artificial neural networks in the amazon rain forest. Ecological Engineering, 112, pp.140-147.

Siau, K. and Wang, W., 2018. Building trust in artificial intelligence, machine learning, and robotics. Cutter Business Technology Journal, 31(2), pp.47-53.

Smith, B. and Linden, G., 2017. Two decades of recommender systems at Amazon. com. Ieee internet computing, 21(3), pp.12-18.

Vanneschi, L., Horn, D.M., Castelli, M. and Popovič, A., 2018. An artificial intelligence system for predicting customer default in e-commerce. Expert Systems with Applications, 104, pp.1-21.

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