  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.
