This project focuses on analyzing the sales performance of a coffee shop, leveraging Power BI to provide an in-depth look at key business metrics. The analysis covers total sales, product category performance, monthly trends, and shopper behavior across various store locations. By presenting interactive and dynamic visuals, the project allows decision-makers to track sales growth, understand customer preferences, and identify opportunities for improvement in product offerings and operations. The goal is to provide actionable insights that help the coffee shop optimize its strategy, increase revenue, and improve customer engagement.

Insights:

• Total Sales and Product Performance: The coffee shop generated $726,866 in total sales, with coffee accounting for the largest share at 34.87% of total sales, followed by tea at 25.24%. This highlights the importance of these categories to the business and suggests that focusing on these items, potentially through promotions or expanding product lines, could further drive growth.

• Monthly Sales Trends: The shop experienced significant revenue spikes in May ($174.37K) and June ($184.30K), reflecting a potential increase in demand during warmer months or due to specific promotions. However, there was a noticeable drop in March and April, suggesting a need to investigate whether external factors, such as holidays or weather, impacted foot traffic. The business can consider targeted marketing during these lower-performing months to stabilize sales.

• Shopper Behavior and Peak Times: The coffee shop experiences peak sales during the mornings, particularly on Friday, Sunday, and Monday. This pattern suggests a strong demand for coffee at the start of the week and just before or during the weekend, which can inform staffing, promotions, and operational adjustments. Offering targeted discounts or promotions during these peak times could further capitalize on customer traffic and increase overall sales.

• Shopper Behavior and Peak Times: The coffee shop experiences peak sales during the mornings, particularly on Friday, Sunday, and Monday. This pattern suggests a strong demand for coffee at the start of the week and just before or during the weekend, which can inform staffing, promotions, and operational adjustments. Offering targeted discounts or promotions during these peak times could further capitalize on customer traffic and increase overall sales.

• Store Performance: Different store locations, such as Astoria and Hell’s Kitchen, showed varying sales figures, which could be linked to foot traffic patterns, local demographics, or store-specific factors. Understanding the reasons behind these differences allows management to tailor marketing campaigns and promotions to the specific needs of each location.

• Top and Bottom Products: The best-performing products, like barista espresso and Gourmet brewed coffee, showed consistent month-over-month growth, while certain flavored syrups and teas underperformed. Focusing on these top-selling items could boost profits, while reviewing pricing, placement, or promotional strategies for low-performing products may help increase their sales.

• Impact of Pricing on Sales Volume: The analysis also reveals a clear relationship between unit price and transaction quantity. Products priced competitively with good value for money tend to perform better, while higher-priced specialty items may require strategic promotions or bundled offers to enhance sales.