Pizza Sales Report

Cecilia Ojile

Data Visualizer

Data Analyst

Microsoft Power BI

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

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Posted Jan 9, 2025

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, optimi

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