Introduction
Alibaba.com is the largest online sales and shopping platform in China. The company was founded in 1999 as a small enterprise that focused on providing a digital platform to enable other companies to list their information. Currently, the company operates two major websites namely, Taobao and Tmall.1Taobao is an online marketplace that facilitates trade among consumers. Tmall, on the other hand, facilitates online business-to-business trade. This paper will analyze the use of data mining at Alibaba.com to improve performance. In addition, the weaknesses of the company’s website and how it can be improved will be discussed.
Data Mining
The managers of Alibaba.com are using data mining in the following ways to improve the performance of their company. First, the company is using data mining to help sellers and loan providers who are using its services to assess customers’ credit risk.2 The company uses its online transaction platform (AliPay) to collect information about customers’ loan repayment history and expenditure patterns. Using advanced analytical tools, the company analyzes the data to determine customers’ ability to repay their loans. As a result, sellers are able to determine customers who have low default risks. The resulting improvement in trade volume enables Alibaba.com to increase its revenue.
Second, the company uses data mining to improve the profitability of its Yu’EBao investment scheme.3 In this case, data mining enables the company to predict the time when customers are likely to transfer cash from Yu’EBao to their AliPay accounts. The prediction enables the company to reduce the risk of capital flight. As a result, the company is able to invest the money that customers deposit in their Yu’EBao accounts in profitable financial products.
Third, Alibaba.com uses data mining to model consumer interests.4 The main objective of this strategy is to determine the products that buyers are likely to purchase. This helps sellers to list the right products to increase their sales. Look-a-like modeling is also used by the company to cross-sell related products. This strategy increases sales by encouraging buyers to purchase the substitutes of the products that are not available on the company’s website. In addition, it improves customer satisfaction and loyalty, which in turn enables Alibaba.com to defend its market share.
Fourth, Alibaba.com depends on data mining to segment the markets for various product categories. This involves building customer profiles based on their purchasing patterns, demographics, and psychographic attributes.5 Appropriate segmentation enables companies that are selling their products through Alibaba’s website to target the right customers in order to increase their sales. Alibaba.com also uses customers’ information to forecast sales on behalf of the sellers who are using its website. Sellers require reliable sales forecasts in order to plan their production capacities effectively. This leads to increased sales, which benefit Alibaba.com through the increase in sales transaction fees.
Finally, the company uses data mining to improve the efficiency of its website. Data mining enables the company to monitor buyers’ and sellers’ activities on its website. For instance, monitoring sellers’ performance in terms of their response to customers’ queries and the ability to deliver products enables the company to ensure trust between sellers and buyers. In addition, tracking buyers’ activities on the website enables the company to predict customers’ responses to adverts.6 This helps in designing effective adverts that lead to high sales.
The Company’s Website
The company’s website has the following weaknesses. First, the website has too much clutter and its layout is confusing.7 The website has too many items listed on the same page. As a result, product images are very small and lack clarity. This limits buyers’ ability to see the features of the products that are listed on the company’s website. This problem is exacerbated by the fact that product descriptions are written in small font. Thus, customers have to struggle to read the descriptions. The poor layout of the website is also a disadvantage to the sellers since their products cannot be viewed easily by the customers who intend to make purchases. The resulting reduction in sales discourages sellers from using Alibaba.com to sell their products. This reduces the company’s revenues and profits.
Second, the company’s website has poor navigation capability. Most buyers and sellers find it difficult to complete various tasks on the website without interruptions. This problem is attributed to the fact that the website’s utilities bar has several items that are hardly used by customers. The search engine is also not effective since it does not facilitate seamless location and comparison of products and prices. Moreover, the website’s user interface does not provide adequate help to customers to find the information that they need. These factors have a negative impact on buyers’ shopping experience. Thus, the company is likely to lose its customers if it fails to improve the performance of its website.
Third, hyper-linking reduces the ease of using the company’s website. The website has several links that open new tabs on the browser when clicked. In addition, the website uses flash-based adverts that are difficult to open using a slow internet connection. As a result, customers are forced to use expensive bandwidth to access the website.
Improvements
First, the layout of the website should be redesigned to make it attractive and easy to use. The company should minimize the number of items per page and use clear product images. Attractive colors and a legible font should be used to convey product information in order to attract customers.8 Second, the company should improve navigation on the website by removing unnecessary items on the utility bar. The resulting improvement in usability and brand experience will enable the company to encourage more buyers and sellers to use its website in a profitable manner.
Third, the capability of the search engine should be optimized to improve buyers’ shopping experience. The search bar should enable buyers to locate products easily and to make comparisons in order to make the right purchase decision. In addition, the company should introduce a help bar that is easy to use and has all the information that buyers and sellers require to use the website effectively.
Conclusion
Alibaba.com has responded to increased competition in its industry by using data mining to determine and to satisfy market needs. Data mining enables the company to examine customers’ purchasing patterns, payment history, and frequency of using its website. As a result, the company is able to provide services that are relevant to buyers and sellers who are using its website. However, the company’s website has too much clutter and is difficult to navigate. These weaknesses have negative effects on customers’ shopping experience. Thus, the company should improve the layout of its website and introduce an effective navigation system.
Bibliography
Alibaba Group. “About Us.” Alibaba Group Ltd. 2014. Web.
Beaird Jason. The Principles of Beautiful Web Design. McGraw-Hill: New York, 2010.
Guo Chengqi and Xiaorui Hu. “Rogue Insiders, Signature Loopholes, and Fraud Rings: Lessons Learned by a Chinese B2B Mogul.” International Journal of Accounting and Information Management 20, no. 4 (2012): 348-362.
Linoff Gordon and Michael Berry. Data Mining Techniques for Marketing and Sales. New York: McGraw-Hill, 2011.
Tu Yanbin. “An Application of Web-based data Mining: Selling Strategies for Online Auctions.” Online Information Review 32, no. 2 (2008): 147-162.
Footnotes
- Alibaba Group, “About Us,” Alibaba Group Ltd. 2014. Web.
- Alibaba Group.
- Alibaba Group.
- Yanbin Tu, “An Application of Web-based data Mining: Selling Strategies for Online Auctions,” Online Information Review 32, no. 2 (2008): 148.
- Chengqi Guo and Xiaorui Hu, “Rogue Insiders, Signature Loopholes, and Fraud Rings: Lessons Learned by a Chinese B2B Mogul,” International Journal of Accounting and Information Management 20, no. 6 (2012): 350.
- Gordon Linoff and Michael Berry, Data Mining Techniques for Marketing and Sales (New York: McGraw-Hill, 2011), 108.
- Alibaba Group.
- Jason Beaird, The Principles of Beautiful Web Design (New York: McGraw-Hill, 2003), 56.