Exploratory data analysis and seller performance prediction leveraging a sample of e-commerce data from Brazilian company Olist.

Read the code on Github here

E-Commerce Seller Performance Prediction - Interactive Plots

Deployed Model

Product Aggregations

The mean sale prices, total sale orders, total sales value and number of unique products per category have been combined in the interactive plot here:

Seller Categories

The product categories with the most number of sellers are the top categories in general. For those categories with less than 30 sellers, it may be difficult for us to get enough data to model appropriate values for them.

Order Values Across Brazil

By joining our order and seller data with our location data, we were also able to see the areas with the highest order values, where we see that most orders come from the southeastern coast, concentrated in Sao Paulo and Rio, two of Brazil’s largest cities.

Aggregated by Zip Codes

This trend was also reflected in the number of sellers and seller performance in these areas.

This provided us indication that the location and product categories would have an impact on the sales generated by sellers.

Read the full code on Github here