Purpose This study examines the impact of website metrics on e-commerce performance, focussing on average session duration (ASD) and e-commerce retail conversion rates. It aims to identify key metrics that drive user engagement and sales within a major online marketplace. The research seeks to provide actionable insights for optimising websites and improving conversion strategies by leveraging aggregated web analytics metrics. Design/methodology/approach Comprehensive website traffic data, encompassing a final sample of 1,315 pages, were collected for one month and analysed using SPSS 25.0. Multiple regression analysis examined how various web analytics metrics, ASD and e-commerce conversion rate are related. Hayes Process Model 1 investigated the moderation effect of page type on the relationship between session duration and conversion. Findings ASD positively predicted e-commerce conversion. Bounce rate (BR), new user ratio and pages per session significantly influenced session duration. Contrary to expectations, page type did not moderate the relationship between session duration and conversion rate, suggesting that engagement dynamics remained consistent across different page structures. Originality/value Unlike prior research that often relies on individual user clickstream data, this study uses comprehensive, site-wide traffic data, offering a broader perspective on website performance and user behaviour. This approach also incorporates key e-commerce metrics, such as BR and conversion rate, which have received limited attention in academic studies.
Naim Çetintürk (Thu,) studied this question.