This project involves analyzing the Zomato dataset, which consists of four tables: goldusers_signup, users, sales, and product. The goal is to answer 11 questions that provide insights into the dataset's characteristics, user behavior, and sales trends.
goldusers_signup: This table contains information about users who have signed up for the Zomato Gold program.
users: This table contains general information about all users, including their userid and signup_date.
sales: This table contains information about sales transactions made through Zomato.
product: This table contains information about the products sold on Zomato, including their prices and categories.
--- 1. What is the total amount each customer spent on zomato?
--- 2. How many days has each customer visited zomato?
--- 3. What was the first product purchased by each customer?
--- 4. What is the most purchased item on the menu and how many times was it purchased by all customers?
--- 5. Which item was the most popular for each customer?
--- 6. Which item was purchased first by the customer after they became a member?
--- 7. Which item was purchased just before the customer became a member?
--- 8. What is the total orders and amount spent for each member before they become a member?
--- 9. If buying each product generates points for eg. 5rs = 2 zomoto points and each product has different purchase points for eg. for p1 5rs = 1 zomato point, for p2 10rs = 5 zomato points and p3 5rs = 1 zomato point. Calculate points collected by each customer and for which product most points have been given till now? (2rs = 1 zomato points)
--- 10. If the first one year after a customer joins the gold program (including their join date) irrespective of what the customer has purchased they earn 5 zomato points for every 10rs spent who earned more 1 or 3 and what was their points earnings in their first year ? (1 Zomato points = 2RS) = (0.5 points = 1rs)
--- 11. Rank all the transactions of the customers
The goal of this project is to analyze the Zomato dataset to gain insights into user behavior, sales trends, and product popularity. By answering these questions, we can identify patterns and trends that can inform business decisions and improve the overall user experience.
This project was completed using Postgre SQL to analyze the dataset and answer the questions posed. The results are presented in a clear and concise manner and summaries to help illustrate key findings.
This project demonstrates my ability to analyze a dataset using SQL and extract insights that can inform business decisions. The results provide a comprehensive understanding of the Zomato dataset and highlight key trends and patterns that can be used to improve the platform.