Plato's Pizza - New Jersey's Greek-inspired pizza place
This project analyzes a year's worth of sales data from a fictitious pizza place. The dataset includes information on the date and time of each order, the pizzas served, along with details on their type, size, quantity, price, and ingredients.
- Customer Traffic: How many customers do we have each day? Are there any peak hours?
- Order Details: How many pizzas are typically in an order? Do we have any bestsellers?
- Revenue Analysis: How much money did we make this year? Can we identify any seasonality in the sales?
- Menu Optimization: Are there any pizzas we should take off the menu, or any promotions we could leverage?
- Customer Traffic Analysis: Analyze customer traffic trends and identify peak hours to optimize staffing and improve operational efficiency.
- Order Insights: Identify the average number of pizzas per order and the top-selling pizzas to inform inventory management and marketing strategies.
- Revenue Tracking: Determine the total revenue generated throughout the year and identify seasonal trends to inform forecasting and budgeting decisions.
- Menu Evaluation: Assess the popularity of various pizzas on the menu, identify underperforming items, and explore opportunities for promotions to optimize the menu and increase sales.
This dataset consists of four tables in CSV format:
- Orders Table: Contains the date and time of all orders.
- Order Details Table: Lists the different pizzas served with each order and their quantities.
- Pizzas Table: Includes the size and price for each distinct pizza, as well as its broader pizza type.
- Pizza Types Table: Provides details on the pizza types, including their names, categories, and ingredients.
