Abstract
Retailers constantly face familiar questions: Why do discounts work better in some stores than others? How does adding an online channel change customer behavior? What happens on digital platforms when external shocks disrupt the market? While these questions may seem straightforward, the answers are often complex and context-dependent. Understanding not just what happens, but what drives these differences, is not always easy.
This thesis examines how retail strategies such as pricing decisions, channel expansion, and product visibility shape customer behavior and influence performance outcomes. Using large-scale data and empirical models across physical stores, online channels, and digital platforms, it shows how similar actions can lead to different results depending on context. The analysis combines theory with data to move beyond description and provide structured explanations of observed patterns.
The contribution is to show that retail performance depends on how customers respond to strategic decisions. By quantifying these responses across retail environments, the thesis links strategic decisions to performance outcomes by connecting empirical evidence with theoretical insights from customer behavior. It provides a structured way to interpret data and supports more consistent, evidence-based decision making in retail.