Analysis of the Web Technologies Used in Amazon.com
Amazon.com can provide customers a convenient, dynamic online shopping experience using the latest web technologies. Among the web technologies, one is HTML5, which, according to Dutonde et al. (2022), provides complete instructions that organize information appropriately for an easy user interface. The other technology used to create amazon.com is JavaScript, as Necula et al. (2018) reveal. This serves as a medium through which interaction takes place, and it supports features like real-time updates of the products and personalized recommendations. Style sheet technology ensures the website’s design looks excellent and responsive over all devices (Dutonde et al., 2022). The website has auto AJAX, which makes it possible to avoid page reloads and thus improve the loading speed. Using Amazon’s CDN functionality, content is rendered swiftly worldwide (Wells et al., 2018). Ultimately, the strategic combination of these online technologies has made Amazon a leader in ICT and has guaranteed that its services are smooth, interactive, and personalized, which are the main ingredients to its domination in e-commerce.
E-payment Systems Analysis
According to Warrier et al. (2021), Amazon.com employs an intensive and comprehensive E-Payment system with several options like credit/debit cards, Amazon Pay, and digital money. Wells et al. (2018) also disclose that the site is security aware since it guarantees the privacy of new transactions through industry-level encryption protocols. Multiple-factor authentication enhances the level of protection for user accounts, and, at the same time, the option to save payment information creates a convenient purchase process in the future (Wells et al., 2018). Besides smooth checkout processes, the above measures ensure that Amazon’s E-Payment is reliable and seamless and makes online transactions trustworthy.
Mobile Commerce Compatibility
Warrier et al. (2021) argue that Amazon.com is in the leading position as a Mobile commerce-compatible business with an application and a website designed to respond to any query in the shortest time possible. This mobile app has complex but handy features like bar code scanning, voice search, and Push notifications, making the service more accessible for shoppers (Wells et al., 2018). The site’s unorganized structure is excellent for devices with different screen sizes so the user can have an adequate mobile-friendly interface. This commitment to mobile aids the platform’s usability as the users can shop from Amazon anytime they need it, and at any time they want from anywhere in the world, leading them to become loyal customers and happy with their mobile devices.
CRM Systems Analysis
Amazon has a robust CRM system that is used to maintain customer relationships and provide information about customers in a customized way. The recommendation engine is a machine-learning algorithm built after studying user behavior patterns, purchase history, likes, and dislikes (Wells et al., 2018). The site also has customer ratings and reviews, making it a dynamic web portal with a user-driven CRM strategy.
Cloud Usage
According to Narula and Jain (2015), the company has used cloud computing so widely from the extensive utilization of AWS only. This site’s scalability, availability, and functionality rely heavily on the help of AWS service. The cloud infrastructure enables global site operations and manages the peak load during prime events such as Prime Day and Black Friday shopping seasons (Wells et al., 2018). However, the possible risks are dependency on a single cloud provider and the costs that appear because of it.
Business Intelligence Insights
Amazon.com relies on BI insights that are relatively strong because the company extracts its data from users’ behavior, purchase history, and reviews (Wells et al., 2018). The platform uses this data for demand prediction, inventory reservation, and targeted marketing. As stated by Pons-Muñoz de Morales (2020), the advice offered is advised by an advanced recommendation engine powered by BI, which provides suggestions relating to a product of personal interest for a user; this is aimed at improving the user’s interaction. Wells et al. (2018) reveal that linking deep insights into Amazon customers’ decisions and trends enables strategic decision-making based on product offerings and market growth. In total, the adaptive business model of the platform is supported by efficient BI to remain afloat in the tough competition of e-commerce. The way offerings are aligned with client preferences and the latest trends is a strategic position that allows the platform to stay competitive.
References
Dutonde, P. D., Mamidwar, S. S., Korvate, M. S., Bafna, S., & Shirbhate, D. D. (2022). Website Development Technologies: A Review. Int. J. Res. Appl. Sci. Eng. Technol, 10(1), 359-366.
Necula, S. C., Păvăloaia, V. D., Strîmbei, C., & Dospinescu, O. (2018). Enhancement of e-commerce websites with semantic web technologies. Sustainability, 10(6), 1955.
Narula, S., & Jain, A. (2015, February). Cloud computing security: Amazon web service. In 2015, the Fifth International Conference on Advanced Computing & Communication Technologies (pp. 501-505). IEEE.
Pons-Muñoz de Morales, S. (2020). Big data and sentiment analysis consider reviews from e-commerce platforms to predict consumer behavior.
Wells, J. R., Danskin, G., & Ellsworth, G. (2018). Amazon.com, 2018. Harvard Business School Case Study, (716–402).
Warrier, U., Singh, P., Jien, C. W., Kee, D. M. H., Yi, G. Z., Jiann, T. W., … & Ganatra, V. (2021). Factors that lead Amazon.com to a successful online shopping platform. International Journal of Tourism and Hospitality in Asia Pacific (IJTHAP), 4(1), 7–17.
write