放弃购物车中的产品后宣传横幅的效果

H. Yeh, Fenghung Kuo
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引用次数: 0

摘要

目的/目的:本研究实证分析和检验了在线宣传横幅对消费者在购物车中更换同类产品的反应的有效性。背景:当购物车中的产品被删除时,它可能会在同一次购买中再次放入购物车,也可能在将来被购买。否则,可能会根据客户的询盘列表或广告条的推荐而放弃该广告,并替换为类似的项目。现有文献对这一现象的认识不足,表明本研究的必要性。方法:利用台湾电子零售商的数据库,数据是经验网页点击流的轨迹。用于分析的数据主要是,当这些产品从顾客的购物车中移除时,这些产品被再次购买或替换为宣传横幅上显示的类似产品。采用少量预定义的Apriori规则和相似度算法Jaccard索引来推导有效性。贡献:本研究通过利用点击流数据中的信息,特别是点击流数据行为,解决了一个测量挑战。这些数据对于观察消费者在网站上的实时行为非常有用,也适用于研究网络横幅广告的点击率,但不是点击率。该研究开发了一种新的方法来帮助广告商评估其横幅广告的有效性。研究发现:“你可能感兴趣”和“浏览次数最多”的推荐/倡导标题对于挽回被下客的商品或再次购买类似商品并没有显著的效果。对于标题为“购买次数最多”的横幅,“观看次数最多”可能只显示商品的受欢迎程度,但不足以说服他们购买。在主机网站的当前阶段,客户可能不信任主机电子零售商,也可能不信任这种机制。此外,倡导/推荐横幅只对相同的客户访问有效,其效果会随着时间的推移而减弱。随着时间的推移,消费者对这些横幅的印象可能会变得模糊。对从业者的建议:一个管理含义是在电子零售网站上更有效地采用宣传/推荐横幅。另一个管理含义是对宣传/建议横幅的评价。通过使用数据挖掘技术来寻找电子购物者购物车中删除的产品和恢复的产品之间的关联,本研究的方法和发现对电子零售营销人员来说很重要,它反映了横幅广告的使用与个人顾客购物车中个性化购买变化之间的联系。给研究人员的建议:这项研究提出了一种新的测量方法,它挑战了利用点击流数据而不是点击率的信息——特别是零售网页的浏览行为。这些数据对于观察消费者在网站上的实时行为非常有用,也可以用于研究点击行为。对社会的影响:个性化已经成为一项重要的技术,使企业能够改善与在线客户的销售和服务关系。这种个性化使电子营销人员能够在使用横幅广告时提供真正有效的效果。未来研究:该方法的有效性具有时效性和个案性。鼓励商业从业者和学术研究人员将挖掘方法应用于长寿研究、特定的广告营销活动和个人推荐,以及任何进一步的推荐算法。
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Effects of Advocacy Banners after Abandoning Products in Online Shopping Carts
Aim/Purpose: This study empirically analyzed and examined the effectiveness of the online advocacy banners on customers’ reactions to make replacements with the similar products in their shopping carts. Background: When a product in a shopping cart is removed, it might be put back into the cart again during the same purchase or it may be bought in the future. Otherwise, it might be abandoned and replaced with a similar item based on the customer’s enquiry list or on the recommendation of banners. There is a lack of understanding of this phenomenon in the existing literature, pointing to the need for this study. Methodology: With a database from a Taiwanese e-retailer, data were the tracks of empirical webpage clickstreams. The used data for analyses were particularly that the products were purchased again or replaced with the similar ones upon the advocacy banners being shown when they were removed from customers’ shopping carts. Few pre-defined Apriori rules as well as similarity algorithm, Jaccard index, were applied to derive the effectiveness. Contribution: This study addressed a measurement challenge by leveraging the information from clickstream data – particularly clickstream data behavior. These data are most useful to observe the real-time behavior of consumers on websites and also are applied to studying click-through behavior, but not click-through rates, for web banners. The study develops a new methodology to aid advertisers in evaluating the effectiveness of their banner campaign. Findings: The recommending/advocating titles of “you probably are interested” and “the most viewed” are not significantly effective on saving back customers’ removed products or repurchasing similar items. For the banners entitled “most buy”, “the most viewed” might only show popularity of the items, but is not enough to convince them to buy. At the current stage on the host website, customers may either not trust in the host e-retailer or in such mechanism. Additionally, the advocating/recommending banners only are effective on the same customer visits and their effects fade over time. As time passes, customers’ impressions of these banners may become vague. Recommendations for Practitioners: One managerial implication is more effective adoption of advocacy/recommendation banners on e-retailing websites. Another managerial implication is the evaluation of the advocacy/recommendation banners. By using a data mining technique to find the association between removed products and restored ones in e-shoppers’ shopping carts, the approach and findings of this study, which are important for e-retailing marketers, reflect the connection between the usage of banners and the personalized purchase changes in an individual customer’s shopping cart. Recommendation for Researchers: This study addressed a new measurement which challenges to leverage the information from clickstream data instead of click-through rates – particularly retailing webpages browsing behavior. These data are most useful to observe the real-time behavior of consumers on websites and also are applied to studying click-through behavior. Impact on Society: Personalization has become an important technique that allows businesses to improve both sales and service relationships with their online customers. This personalization gives e-marketers the ability to deliver real effectiveness in the use of banners. Future Research: The effectiveness is time- and case-sensible. Business practitioners and academic researchers are encouraged to apply the mining methodology to longevity studies, specific marketing campaigns of advertising and personal recommendations, and any further recommendation algorithms.
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CiteScore
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14
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