This project involves a comprehensive analysis of the Olist Store dataset. The analysis aims to uncover valuable insights about the store's performance, customer behavior, and sales trends. The project utilizes various data analysis techniques and visualizations to present the findings.
The Olist Store dataset provides information on orders made at Olist Store, an online e-commerce platform. The data includes details about orders, products, sellers, and customer reviews. The primary goal of this project is to perform an exploratory data analysis (EDA) to derive meaningful insights that can help improve the store's business strategies.
The dataset used for this analysis spans from 2016 to 2018 and includes nine interconnected sub-datasets covering customers, geolocations, order items, payments, reviews, orders, products, sellers, and product category translations.
Here's a breakdown of the key datasets:
- olist_customers_dataset
- olist_geolocation_dataset
- olist_order_items_dataset
- olist_order_payments_dataset
- olist_order_reviews_dataset
- olist_orders_dataset
- olist_products_dataset
- olist_sellers_dataset
product_category_name_translation The data is available on the Kaggle Olist Store Dataset.
The analysis section covers the following key areas:
- Descriptive statistics of the dataset
- Customer segmentation based on purchase behavior
- Payment Preferences
- Sales trends over time
- Product performance analysis
- Customer review analysis
Interactive Report:- Link
The analysis provided several insights that can help Olist Store improve its business strategies. Key takeaways include understanding customer purchase patterns, identifying high-performing products, and leveraging customer feedback to enhance service quality.
- Complete Project Link - Comprehensive Analysis of Olist Store - Blog Post
- Dataset Link - Kaggle Olist Store Dataset