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Assignment代写:亚马逊信息系统策略研究(7)

时间:2018-05-16 09:18来源:www.ukthesis.org 作者:英国论文网 点击联系客服: 客服:Damien
 
3.3 Product comparison
Chart 3 Product comparison layout
In order to better help consumers to make purchasing decisions, Amazon can integrate ShopEx or ECShop online store system into their own website, these two systems allow consumers to easily use commodity comparison function. Consumers can find the same type of products they need, there is a contrast function key set up for each product, as long as consumer clicks the contrast function key, the product will be included in the comparison range, while there will be  4-6 similar products for contrast. Product price, product material, origin and other information will be displayed in the same form, consumers can clearly see, most importantly, the bottom line of each comparison form will be a simple comparison report provided by Amazon, which introduces the characteristics of each product, what are the comparative advantages, the scope of application and so on. The contents of this report can be preset in the back-end administration of ShopEx or ECShop online store system.
 
3.4 Referral
Chart 4 Characteristics of different consumer groups (Shi and Liao, 2017)
Algorithms of Amazon's current product referral system are based on consumers’ purchase history and visit records, taking it as the main recommendation basis, while characteristics of consumer behaviour of consumer group are less considered. Therefore, Algorithms of Amazon's current product referral system can be further improved, characteristics of consumer groups can be taken as one of the basis for recommending products. For example, it can be seen from the figure above that, for 40-50 male consumers, 65% of consumers are willing to spend more money to buy technology products, spend less money to buy clothing. As a result, Amazon's system can use up-selling when it  recommends products to 40-50 male consumers, recommending more advanced but more expensive technology products to them, and in addition, cross-selling strategies can be used to recommend middle and low-end men's clothing to men when they opt for technology products. For 30-40 years old female consumers, they are willing to spend more money on the purchase of clothing, at the same time, they will buy children's clothing, therefore, in recommendation for this part of consumers, Amazon can consider recommending children's wear.
 
4.0 Conclusion 结论
 
Based on 4R theory, this essay puts forward some suggestions on how Amazon further improves its information system. The suggestions include four aspects, first of all, Amazon needs to establish a consumer behaviour assessment system, by recording consumers’ buying behaviour on the website and giving appropriate incentives to consumers to develop their habit of spending on Amazon’s website to enhance their loyalty. Followed by the application of group chat and voice technology to customer service, it will help Amazon to provide timely response to consumer consultation and have understanding of consumer needs. Third, to improve product comparison system can help customers to make the best purchase decision. Finally, based on characteristics of consumer groups to analyze consumer preferences, it will help Amazon to recommend targeted products to consumers to make recommendations more targeted.  (责任编辑:cinq)


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