Introduction
This is a PowerBI project on Pizza Sales using data for the year 2015. This pizza company needs to analyze their data to understand customer preferences, optimize inventory, streamline operations, target marketing efforts effectively, ensure quality control, and stay ahead of competitors.
Problem Statement
KPI's
Total Revenue
Average order value
Total Pizza sold
Total orders
Average pizza per order
Charts Requirement
Daily trend for total orders
Monthly trend for total orders
Percentage of sales by Pizza Category
Percentages of sales by Pizza size
Total pizza sold by size category
Top 5 best sellers by Revenue, Total, Quantity and Total Orders
Bottom 5 sellers by Revenue, Total, Quantity and Total Orders
Skills/ concepts demonstrated:
I used the following PowerBI features:
Data Preparation and Modeling
Data Import and Integration:
Imported data from excel.
Use Power Query to clean, transform, and shape data.
Merge and append data from multiple sources.
Data Modeling:
PowerBI automatically created relationships between tables.
I developed calculated columns and measures using DAX (Data Analysis Expressions).
I implemented hierarchies and role-playing dimensions.
Data Analysis and DAX
Basic DAX:
I wrote simple DAX formulas for calculated columns and measures.
I used basic DAX functions such as SUM, DINSTINCTCOUNT, RELATED.
Data Visualization
Creating Visualizations:
I used different types of charts (bar, line, pie)
I utilized slicers for interactive filtering.
Formatting and Aesthetics:
Apply themes and formatting to ensure visual consistency.
Use conditional formatting to highlight important data points.
Arrange and align visuals for a clean, professional look.
Interactive Features
Interactivity:
Create and configure report-level, page-level, and visual-level filters.
Implement drill-throughs to navigate between report pages.
Use bookmarks and buttons to create interactive storytelling experiences.
Analytical Skills
Data Insights:
Analyze and interpret data trends and patterns.
Create KPIs to track key performance metrics.
Use statistical methods to provide deeper insights.
You can interact with the report here
Visualization:
The dashboard was created by using different types of charts (bar, line, pie). I utilized slicers for interactive filtering. I applied themes and formatting to ensure visual consistency. I used conditional formatting to highlight important data points. Finally i arranged and align the visuals for a clean, professional look.
Below is a snippet of the final dashboard in PowerBI.
Key Insight
Total Revenue: The dashboard shows a significant total revenue of $817,860 in 2015.
Peak Orders: Orders are highest on weekends, Friday/Saturday evenings and there are maximum orders from Month of July and January
Sales performance: By catogory: Classic category contributes to maximum sales and total orders. By size: Large size pizza contributes to maximum sales
Best sellers By Revenue: The Thai Chicken contributes the maximum Revenue. By Quantity: The Classic Deluxe Pizza Contributes to maximum Total Quantities. By Total Orders: The Classic Deluxe Pizza Contributes to maximum Total Orders.
Worse sellers By Revenue: The Brie Carre Pizza contributes the minimum Revenue. By Quantity: The Brie Carre Pizza Contributes to minimum Total Quantities. By Total Orders: The Brie Carre Pizza Contributes to minimum Total Orders.
Recommendations
Increase marketing efforts during weekends, Friday/Saturday evenings, and peak months (July and January).
Promote and bundle the Classic Deluxe Pizza; consider premium pricing or signature dish promotion for Thai Chicken Pizza.
Evaluate the necessity of the Brie Carre Pizza; consider rebranding, recipe alteration, or discounting.
Introduce new varieties or limited editions within the Classic category and explore new size options or combo deals featuring large pizzas.
Align staff schedules and resources to peak times; ensure a robust supply chain to avoid stock outs during peak periods.
Monitor inventory levels of best-selling items closely to ensure constant availability.
Implement loyalty programs rewarding frequent purchases, especially of best-selling items.
Gather customer feedback on poor-performing items to identify potential improvements.
Conclusion
Implementing these recommendations will likely lead to increased sales, improved customer satisfaction, and better overall business performance.
Thank you for your interest and time. Your valuable suggestions are welcome. Feel free to connect with me for further discussion here
