The top online shopping destination in the world is Amazon.com. The organization oversees businesses in practically every economic sector and sells products from various manufacturers. The potential for a large audience to shop from home ushered in a new era in marketing history. The company’s CEO, Jeff Bezos, has identified customer service as the most critical component of Amazon’s operation. Most customers purchase in physical stores, but Amazon’s market share is still increasing. An effective information system is a foundation for building an e-commerce site like Amazon, and it should be thoroughly investigated because it determines the company’s financial success.
The system’s users are from the middle class and of various ages. These could include secretaries, economists and lawyers, physicians and educators, engineers, and highly trained personnel. They are the ones who select and buy daily stuff like clothing, children’s items, furniture, home appliances, and technology online. These people range in age from youth to adults with a reliable income source. Conversely, the users can be young individuals with subcultures and values that elders find incomprehensible. However, the target market relies on product quality, expedited shipment, and website usability.
To satisfy its billions of users—representatives of various nations with distinctive tastes—Amazon has made its navigation as easy and convenient as possible. Users can search for items in the field at the top of the page after joining up. The customer inputs product-related data before clicking the “search” button to get a list of particular products. Another feature allows the system to select possible results as the user type keywords and presents them in a drop-down menu. The option for goods sorting is located in the right corner after entering terms in the search area. It suggests categorizing products in the catalog based on many factors, including low and high prices and vice versa, newness, and a rating. Selecting products involves deciding on them based on relevant criteria, such as department, brand, color, size, and price. As a result, it aids in increasing the offer even though there is not a perfect match with the item description.
In the top right corner, there is the traditional cart button. The online store must have this feature so customers can add one or more things to their shopping carts (Pappas et al., 2017). By clicking the “Add to Cart” button, selected items are added to the cart. The product name is shown on the page that follows the jump page. The item photo is posted to the product card because the product type is not often evident from the title. The user can modify the contents by removing extraneous items. Additionally, information on delivery and payment is provided in the purchasing cart.
The review feature is one of the most critical aspects of the item description page. Because Amazon receives hundreds of user reviews, the website analyzes all feedback scores and generates an evaluation list using decryption (Lee et al., 2018). Customers may see how many of each product were purchased and what rating it received. Customers can rate the reviews on Amazon by indicating whether they were helpful, and the most popular ones are shown at the top (Lee et al., 2018). People frequently check reviews before looking at product attributes, as evidenced by practice (Smith & Linden, 2017). Thus, the user does not need to look over all product details.
Talking about advantages, the fact that this online purchasing platform saves the customer’s time should be primarily mentioned. As long as users have access to the Network, they can make purchases from the online store whenever it is convenient for them and from any location. Customers do not have to travel to department stores because the search engine offers them an extensive list of websites with products. Choosing a few items and placing an order will take a few minutes.
Additionally, online shopping saves money because clients may buy things for a lot less, thanks to various discounts and discount schemes. Even without it, Amazon products are always less priced because an online retailer does not need to spend extra money on showrooms and pricey spaces in shopping malls. Typically, warehouse properties are outside of the city. Therefore, the rent is less expensive (Pappas et al., 2017). There are a lot of discounts and seasonal sales on the platform.
By entering keywords, the Amazon interface makes it simple for customers to find the products they are looking for so that the search engine can provide relevant results. The user can provide the requirements for the item, and the store will quickly display the appropriate goods. Since there is no longer a need to wait for sales assistants, the buyer is always given all the pertinent information about the acquired item, saving time (Pappas et al., 2017). On the Internet, the customer can rapidly analyze products, look at user evaluations, and read ratings from other customers. As a result, customers can choose the best purchase option.
The platform’s primary goal is to make users as comfortable as possible to encourage them to make a purchase. A helpful search engine can easily find a product by its related terms. Many product catalogs are provided to make it easier for customers to traverse the website. The business is rightfully regarded as prominent in the e-commerce market. Amazon now invests millions of dollars in improving the user interface constantly. The Internet is an environment that needs continuous adjustments. Amazon pays attention to the website’s mobile version. After reaching a certain point, the business started producing its goods and acquiring new services, which broadened its range of potential markets.
References
Lee, S. G., Trimi, S., & Yang, C. G. (2018). Perceived usefulness factors of online reviews: a study of Amazon.com. Journal of computer information systems, 58(4), 344-352.
Pappas, I. O., Kourouthanassis, P. E., Giannakos, M. N., & Lekakos, G. (2017). The interplay of online shopping motivations and experiential factors on personalized e-commerce: A complexity theory approach. Telematics and Informatics, 34(5), 730-742.
Smith, B., & Linden, G. (2017). Two decades of recommender systems at Amazon.com. Ieee internet computing, 21(3), 12-18.