The Pizza Sales Performance Analysis Report with Power BI and SQL

Introduction

The purpose of this project is to help pizza business sustain and enhance their business growth. The analysis will help business owner understands their current product performance and uncover valuable insights to make data-driven decisions

Problem Statement

To identify business growth opportunities, the pizza business owner needs to understand their product performance - their data sales in order to execute growth plans such as marketing, promotions, or product optimization.

To generate insights, I developed Power BI dashboard monitoring key performance metrics using these questions:

1. What is the total revenue over a specific period?
2. How many pizzas have been sold in total?
3. What is the average order amount?
4. Which pizza names are the most and least popular by order?
5. Which pizza names have the highest and lowest quantity sold?
6. Which pizza sizes are most preferred by customers?
7. Which pizza categories generate the most sales?
8. What are the daily and monthly sales trends?
9. How do sales vary across pizza categories and sizes?

Tools and Technologies Used

• MySQL - This was needed to conduct Data Quality Assessment and also for Data Cleaning processes. The relational model is adopted to store and access structured information and I used tructured query language (SQL) to write and query data to:

  • Perform data cleaning, aggregation, and then processing tasks within Power BI.
  • Cross-validating analytical results between SQL query outputs and Power BI DAX-based calculations
  • Documented the queries and their results in Google Docs to monitor and improve query performance and management tasks.

• Power BI - This tool was required to explore data and create charts, graphs, visualizations to come up with a **Sales Performance Dashboard ** for the pizza business.

Click on the hyperlink to view the documents:

• Pizza Performance Analysis SQL Queries
• Pizza Performance Analysis Power BI Dashboard

Key Findings

The following are some of the key findings from the analysis:

• The total number of pizza orders was approximately 21,000.
• The total sales of pizza were approximately 50,000.
• The total revenue from pizza sales was $817,860.05.
• The average order value was approximately $38.
• Classic Deluxe Pizza is customer favorite.
• Large Size and Classic pizzas dominate sales
• Sales Increase in Friday, Wednesday and Saturday as daily and January,May, July monthly.

Recommendations

By implementing these recommendations, business owner can leverage sales data to make informed decisions that drive growth and profitability in their pizza business.

1. Optimize Satff anf Marketing Strategiess:

Consider leveraging the noticeable trends by day (Friday, Wednesday, Saturday) and by month (January,May,July) to optimize staffing and marketing strategies. For instance, increase staffing levels on Fridays and tailor promotions for the month of July to capitalize on these trends.

2. Inventory and Production Planning:

With a total of 50,000 pizzas sold, we can utilize this data to refine inventory and production planning processes. By identifying peak sales periods and popular pizza types, pizza owner can optimize stock levels to meet demand while minimizing waste.

3. Optimize Pricing and Promotions:

The average order amount of $38 provides valuable insights into customer spending habits. We can use this information to fine-tune pricing strategies and develop targeted promotions that resonate with customer base. For example, we can offering bundle deals or loyalty programs to incentivize higher spending.

4. Buid Customer Growth Programs for marketing, promotions and product optimization

In terms of marketing efforts:

• Promote Customer Favorites - Since the Classic Deluxe Pizza is a customer favorite and a top performer in terms of quantity, we can use its features and ** benefits **to attract more customers and drive sales further. For instances, designing promotional materials such as coupons, deals-day, or special sales.

• Prioritize Best-Selling Categories and Sizes - Given that Large Size and Classic pizzas dominate sales, we can prioritize these sizes and categories in marketing campaigns and product offerings such as introducing variations or promotions to further capitalize on their popularity.

5. Utilize Percentage Sales Data:

By examining the percentage sales by pizza category, we can see that Classic, Supreme pizzas and Large (L) size pizza are more popular among customers.Armed with this information, some recommendations will help pizza owner maximizing profitability by:

• Allocate resources - effectively by focusing marketing efforts and production resources on the most popular pizza categories and sizes will help increase sales and revenue without significant additional expenses.
• Optimize product mix - for the lower percentage of sales in top 5 categories. For example, Chicken pizzas have a lower percentage of sales, it is worth to evaluate whether adjustments to the recipe or marketing strategies are needed to increase their popularity.
• Or, we can introduce new variations or seasonal specials based on the popularity of certain categories and sizes of pizza.

6. Continuous Monitoring and Adaptation:

Continuously monitor sales data and customer feedback will help identifing emerging trends and customer preferences. This will help in maintain a competitive price on the market and sustain long-term profitability.

Author

• Nguyen Dang Xuan Linh - GitHub Profile