Introduction
In the fast-paced food industry, knowing what sells
best and when can significantly impact success. For my data analyst portfolio
project, I analysed a dataset of pizza sales and created two dashboards: Home
and Best/Worst Sellers. These dashboards offer a comprehensive view of the
data, helping to identify top-selling pizzas, peak sales times, and performance
by category and size. This project highlights my skills in data cleaning,
analysis, and visualization using Tableau.
Project Overview
The objectives of this project were to:
1. Understand which pizzas drive the most revenue and
sales.
2. Identify low-performing items to optimize the menu.
3. Track customer behaviour across different times of
the day and week.
4. Provide insights into pizza size and category
preferences.
Dashboard 1: Home
The Home dashboard provides an overview of key sales
metrics, trends, and customer preferences, allowing stakeholders to quickly
grasp overall performance.
Key Metrics on the Home Dashboard:
Total Revenue:
$817.9K, showing total sales generated.
Average Order Value:
$38.3, indicating typical spending per order.
Total Pizzas Sold:
49.6K across 21.4K orders, averaging 2.32 pizzas per order.
Insights from the Home Dashboard:
1.
Hourly Sales Trends: Sales peak during lunch (12 PM - 1 PM)
and dinner (6 PM - 7 PM), informing staffing needs.
2.
Weekly Sales Patterns: Fridays and Saturdays see the
highest sales, with December showing increased orders, likely due to holiday
gatherings.
3.
Category and Size Preferences:
Pizza
Category: Supreme pizzas generated the highest revenue,
followed by Chicken and Veggie pizzas.
Pizza
Size: Large pizzas dominate sales, accounting for 43.5%,
while XL and XXL sizes are less preferred.
These insights can guide operational adjustments,
inventory management, and targeted promotions.
Dashboard 2: Best/Worst Sellers
The Best/Worst Sellers dashboard examines individual
pizza performance, highlighting both top and bottom sellers by revenue and
quantity.
Insights from the Best/Worst Sellers
Dashboard:
1. Top
5 Pizzas by Revenue: Thai Chicken Pizza leads with $43.4K in
sales, followed by Barbecue Chicken and California Chicken. The top pizzas are
mainly meat-based, indicating a preference for protein-rich options.
2. Top
5 Pizzas by Quantity: Classic Deluxe and Hawaiian pizzas are
the most popular in terms of units sold, appealing to a wide customer base and
worth promoting further.
3.
Bottom 5 Pizzas by Revenue and Quantity: Brie Carre and
Mediterranean pizzas rank lowest for both revenue and quantity, suggesting they
may need rebranding, promotional efforts, or potential removal from the menu.
Actionable Insights:
Menu
Optimization: Replace or promote low-performing pizzas
to enhance their appeal. Testing different toppings or names could increase
attractiveness.
Marketing
Strategy: Highlight
popular pizzas like Thai Chicken and Classic Deluxe in marketing campaigns to
drive more orders.
Inventory
Adjustments: Optimize inventory management based on
pizza category and size popularity, stocking up on high-demand ingredients
while minimizing waste for lesser-demand items.
Conclusion
This project provided valuable insights into pizza
sales trends, customer preferences, and product performance. The Home dashboard
serves as a high-level summary for quick insights, while the Best/Worst Sellers
dashboard offers detailed information on top and bottom-performing pizzas. By
identifying these trends, pizza businesses can better manage inventory,
optimize their menu, and create targeted promotions to increase revenue.
Final Thoughts
Analyzing data to uncover insights that drive
decision-making is essential for businesses. This project showcases my skills
in data cleaning, visualization, and interpretation. Feel free to reach out if
you have any questions or want to learn more about this project.
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