Optimizing Advertisement Spend Timing for Personal E-Commerce: The Critical Role of Weekends in Driving Page Views

Abstract

Personal e-commerce operators face significant challenges in optimizing limited advertising budgets, necessitating precise understanding of how temporal factors moderate ad effectiveness. This study addresses this gap by examining the joint influence of advertising expenditure and time-based variables—specifically weekends and holidays—on daily page views, leveraging a dataset from a personal e-commerce platform. Using a stepwise regression framework, this paper first established a baseline model testing ad spend in isolation, followed by an additive model incorporating binary weekend and holiday indicators. Results demonstrate that advertising expenditure alone fails to explain traffic variation; however, when temporal context is controlled, weekends emerge as a dominant predictor of heightened page views, while holiday effects remain statistically undetectable due to data constraints. Critically, ad spend exhibits a weak but significant effect only after accounting for weekend timing, revealing that prior models overlooking temporal confounders underestimate advertising’s marginal impact. These findings advocate reallocating budgets toward weekend periods and highlight the imperative for richer temporal data collection to refine targeting strategies.