To identify the most appropriate recommendation model for an e-commerce business, a live evaluation should be performed on the shopping website to measure the influence of personalization in real-time. The aim of this paper is to introduce and justify two new metrics -- CTR NoRepeat and Click & Buy rate -- which stem from the standard metrics, Click-through(CTR) and Buy-through rate(BTR), respectively. The former variation tackles the issue of overestimation of clicks in the original CTR while the latter accounts for noting purchases of products that have been previously clicked, in order to validate that the buy included in the metric is a result of customer interactions. A significance test for independence of two means is conducted for multiple datasets, between each of the new metrics and its respective parent to determine the novelty and necessity of the variants. The Pearson-correlation coefficient is calculated to assess the strength of the linear relationships and conclude on the predictability factor amongst the aforementioned factors to investigate unknown connections between customer clicks and buys. Additionally, other metrics such as hits per customer, buyers per customer, clicks per customer etc. are introduced that help explain indicators of customer behavior on the e-commerce website in reference.
翻译:为了确定电子商务业务的最适当建议模式,应在购物网站进行现场评估,以衡量个人化对实时影响的影响。本文件的目的是介绍和说明两个新的指标 -- -- CTR NoRepeat和点击与购买率 -- -- 分别来自标准指标、Click-tough(CTR)和Buy-tough利率(BTR) -- -- 的两种新指标。前一种变数处理对原CTR中点击量的过高估计问题,而后一种变数则涉及注意到以前点击过的产品购买量的账户,以证实该指标中包括的购买是客户互动的结果。对两种手段的独立性进行了重大测试,即每个新指标与各自的母体之间,以确定变数的新颖性和必要性。Pearson-corlation系数是用来评估线性关系强度,并得出上述各种因素之间的可预测性因素,以调查客户点击与购买之间的未知联系,以便核实该指标是否包含客户互动的结果。此外,其他指标,例如每个客户点击电子客户、每个客户购买者、每个客户点击每个市场的行为指标等等。