The Pizza Sales Dashboard provides valuable insights into the sales performance of different pizza categories, sizes, and individual items. It helps the business identify its best-selling products and those that need improvement. By analyzing daily, weekly, and monthly trends, the company can make data-driven decisions to optimize their operations and increase profitability. The dashboard also highlights key performance indicators such as total revenue, total orders, and average order value.
Key metrics such as the number of pizzas sold, busiest days and times, and best-selling pizzas are crucial for planning promotions and inventory management.
- Step 1: Cleaned data by addressing missing values and ensuring all relevant columns were accurate in MS SQL.
- Step 2: Loaded data into Power BI Desktop from MS SQL Server database.
- Step 3: Created various visuals, including bar charts, line charts, and card visuals to represent key metrics such as total revenue, total orders, and pizza sales distribution by category and size.
- Step 4: Applied slicers for pizza category and size to allow dynamic filtering of the visuals.
- Step 5: Created measures to calculate total revenue, total pizzas sold, and average order value using DAX expressions.
- Step 6: Designed the dashboard layout and applied visual filters to allow the end-user to drill down into specific sales data.
The dashboard showcases various key metrics, presented through visuals such as bar charts, line graphs, and cards for quick insight into performance:
- $817.86K
- Indicates the overall sales revenue generated during the period.
- 21,350
- Represents the total number of pizza orders placed during the year.
- 49,574
- Displays the total number of pizzas sold, helping to assess product demand and trends.
- $38.31
- This is the average revenue per order, reflecting how much customers typically spend.
- $38.31
- This is the average revenue per order, reflecting how much customers typically spend.
- 2.32 pizzas per order
- Provides insight into the typical order size, aiding in inventory planning.
- The busiest days for orders are typically Fridays and Saturdays, with the peak occurring in the evening.
- Wednesday is also relatively busy, while Sunday and Monday see fewer orders.
- The highest number of orders occurs in January and July.
- Other months show steady performance with slight dips.
- The Thai Chicken Pizza contributes the most to total revenue at $43K.
- The Classical Deluxe Pizza is the most sold, with 2.5K pizzas sold.
- The Brie Carre Pizza contributes the least revenue at $12K.
- The Brie Carre Pizza has the lowest sales, with only 490 pizzas sold.
The dashboard highlights the business's busiest periods for orders:
- Days: The majority of orders are placed on weekends, particularly Friday and Saturday evenings.
- Months: The busiest months are January and July. This insight helps in scheduling staff, inventory stocking, and running targeted promotions during peak times.
- Top Performing Category: The Classic Pizza category leads sales, both in terms of total orders and revenue.
- Top Performing Size: The Large Pizza size is the highest contributor to overall sales, both in terms of quantity and revenue. These insights help the business understand customer preferences and tailor its offerings accordingly.
The Pizza Sales Dashboard is a comprehensive tool for understanding the business's performance across various dimensions. By identifying high-performing products and peak sales periods, the business can focus on improving underperforming items, optimizing staffing schedules, and planning promotions around busy times.
- Focus on promoting best-selling pizzas, such as the Thai Chicken and Classical Deluxe pizzas.
- Consider discontinuing or revamping worst-selling items, such as the Brie Carre Pizza.
- Leverage insights from peak sales periods (weekends and specific months) to enhance marketing efforts and promotions. By continuously monitoring these metrics, the business can make informed decisions to increase customer satisfaction, boost sales, and streamline operations.