Coffee retail shops business analysis, analyzing the transactional records of three stores of Roastery coffee business . Track important KPIs , describe historical performance and forecast various metrics
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Coffee Shop Retail Business Analysis
Overview
The Roastery Coffee operates three store locations in New York: Lower Manhattan, Hell's Kitchen, and Astoria. The company offers 80 products across 9 categories. This project analyzes six months of transactional data (Jan–Jun 2023) to understand sales performance, store efficiency, product trends, and forecast revenue.
Business Problems
Identify monthly revenue trends and seasonal patterns Compare store performance across locations Optimize staffing, procurement, and pricing strategy Analyze top-performing and low-performing products Track weekday vs weekend demand trends Forecast next quarter sales and plan promotions
Key Insights
Monthly revenue grew at an average of +16.3% MoM, peaking at +31.8% in May Nearly half of sales (48–49%) occur during the morning rush hours (7–11 AM) The top five categories (coffee, tea, bakery, chocolate, beans) contribute about 93% of total revenue 34% of product types generate 80% of overall revenue (Pareto principle) Astoria recorded the most orders but lowest revenue per order, suggesting smaller basket sizes July forecast shows Lower Manhattan leading revenue with $65K, followed by Astoria ($62.8K) and Hell’s Kitchen ($62.5K)
Strategy Recommendations
Adjust room pricing and promotions during high-demand periods (mornings, weekends, month-end) Use combo meals, loyalty rewards, and targeted discounts to boost sales on slow days Focus marketing and product development on the 34% of products driving most revenue For Astoria, introduce upselling and meal bundles to increase average order value For Lower Manhattan, optimize pricing on Hot Chocolate, which is showing strong growth Align staffing and inventory planning with demand peaks
Dashboard
An interactive Power BI dashboard was built to: Track KPIs such as revenue, orders, AOV, and growth trends Compare store and product performance Visualize daily, weekly, and monthly trends Forecast sales and demand for better decision-making