Aditi Ganesh Joshi
Surbhi Garg
Ashish Murlidhar Pagote
During the course of this project, we plan to use and integrate the data from an e-commerce firm in Brazil called “Olist”. Olist provides a marketplace for various SMBs to sell their products online. The aim of this project is divided into two parts as follows:
- Perform exploratory data analysis on order data to identify the most frequently bought products, product segments, etc.
- Conduct Market Basket Analysis and Customer Segmentation on the e-commerce data to understand consumer behavior.
- Analyze trends and forecast future sales
- To study the effectiveness of the marketing funnel at Olist, an e-commerce firm in Brazil, in terms of various metrics based on the conversion of qualified leads, revenue, and various attributes associated with them.
- Understand the logistics and address inefficiencies
There are a couple of data sources freely available on Kaggle that will help us address various business challenges relevant to the e-commerce firm. Finance, Marketing, Logistics, Customer Insights, and Product Operations are some of the key domains where this data can be utilized to improve efficiency, engagement, and revenue.
We obtain this data from the following 2 sources on Kaggle:
Link1: https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce
Link2: https://www.kaggle.com/datasets/olistbr/marketing-funnel-olist
The first data source is a collection of 9 different CSV files that capture information regarding customers, products, sellers, customer orders, payment information, geolocation of customers, and seller and customer’s order reviews.
The second data source is a collection of 2 different CSV files. This data source captures information about marketing campaigns toward sellers of the Olist platform.