The project aimed to improve the retailer’s sales performance by analyzing sales data, optimizing logistics, and recommending strategic decisions.
Conducted exploratory data analysis (EDA) to understand trends and identify key factors like population, income, and education levels affecting sales. Used linear regression modeling to predict the sales potential for new locations. Recommended St Kilda, Victoria for a new physical store due to its favorable demographics and economic factors. Suggested enhancing internet presence in Pyrmont Ultimo, New South Wales, for increasing market competitiveness.
Performed network analysis (Using R to process the national geo data) to identify the optimal locations for distribution centers across Australia and also a new store location, selecting seven areas. Designed vehicle routing plans to reduce logistics costs using ArcMap for two scenarios: Plan A: Daily delivery with higher fixed and variable costs. Plan B: Weekly delivery with lower costs but tailored routes. Recommended Plan B for its cost-effectiveness, suggesting specific trucks and route configurations.
Combined tools like R, Python, and ArcMap for data processing, regression analysis, and network optimization. Developed a composite index considering shop sales, local labor force, transport industry, and other metrics to select distribution centers.
Increased understanding of factors influencing sales. Optimized distribution logistics to balance cost and efficiency. Provided actionable recommendations for expanding physical and digital sales strategies.