This project was made under the guidance of Ws cube tech, an organization solely involved in the education of data analytics.
The project consists of a data from 3 stores at different locations serving coffee, tea and its derivatives alongwith sides like bakery items, liquid chocolate, etc. The dataset has records of 6 months from January to June. The analysis goes through the coffee size, avg. order price, etc.
A 6-month retail analytics project focused on understanding sales trends, product performance, customer footfall patterns, and category contributions at a chain of coffee shops.
Duration: January 2023 – June 2023
Scope: Sales analytics across 3 coffee shop locations
Created By: Yog Gupta | Ws Cube Tech
The analysis uncovers:
- Temporal sales patterns (by hour, day, and month)
- Best-selling products and sizes
- Customer footfall trends
- Category-level performance
| KPI | Description |
|---|---|
| 🧾 Total Sales | Gross revenue over 6 months |
| 🚶 Total Footfall | Number of customer orders (transactions) |
| 💰 Avg Bill/Person | Total revenue ÷ total footfall |
| 🧺 Avg Order/Person | Total items sold ÷ total footfall |
- Peak sales between 7 AM – 10 AM, aligned with breakfast and office hours.
- 10 AM shows maximum unit sales (~26K units total).
- June had the highest traffic during peak hours (~6K units).
- Tuesdays and Fridays consistently lead in footfall and orders.
- Sales decline gradually after morning hours with a mild bump during lunch (2K units), then taper off toward closing.
- Sales distributed across 3 locations.
- Hell’s Kitchen outperformed the others in every month.
| Month | Total Sales |
|---|---|
| January | $81,716 |
| February | $76,144 |
| March | $98,833 |
| April | $118,940 |
| May | $156,726 |
| June | $166,485 |
🔝 June was the highest-grossing month.
- Barista Espresso
- Brewed Chai Tea
- Hot Chocolate
- Gourmet Brewed Coffee
- Brewed Black Tea
☕ Espresso and tea dominate the top spots by revenue.
- Regular size most frequently ordered
- Small size least preferred
- Large and Unspecified sizes have similar shares
- Coffee and Tea drive majority of revenue
- Bakery items, Drinking chocolate, and Flavours also show strong contribution
- Target promotions during early hours (7–10 AM), particularly on Tuesdays and Fridays
- Expand offerings or combos around top products (e.g. Barista Espresso, Brewed Chai Tea)
- Consider revising or discontinuing Small size due to low demand
- Focus on high-performing location (Hell’s Kitchen) for loyalty programs
- Continue product innovation in Bakery and Chocolate categories
- Microsoft PowerPoint (Data Visualization)
- Microsoft Excel (Data Aggregation & Cleaning)
- Pivot Charts, Trend Analysis, Time Series Aggregation
- Predictive modeling for inventory based on hourly footfall
- Customer segmentation using transaction patterns
- Loyalty program ROI analysis
This project presents a comprehensive dashboard-based analysis of coffee shop performance across products, categories, time periods, and locations. It is designed to empower coffee chain managers and marketers to take data-backed decisions for improving customer experience and driving sales.