Walmart’s senior management suspects that overall sales performance is driven by a limited number of stores, while sales volatility may originate from a different subset of locations. At the same time, the CEO is uncertain whether observed weekly fluctuations can be systematically explained by holiday effects and macroeconomic conditions, or whether they reflect random noise. The objective of this project is to translate these managerial concerns into data-driven insights using exploratory analysis, regression modeling, and clustering techniques. The ultimate goal is to provide actionable recommendations rather than purely statistical results.

This project analyzes daily bank customer visit patterns using time-series and event-based modeling techniques in R. The study examines weekday effects, seasonality, and the impact of special events and promotions on customer visits. The analysis is conducted as part of the Marketing Analytics (MiM811) course and is intended for academic purposes.