Olist needs recommendation system to increase sales by give suggestion products with purposes to make the customer purchase faster. Dataset: https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce
The original dataset is using Portuguese Language, in order to easier to analyze, I'd translated to English Language. I'd provided with tranlated version too.
Background Project: Olist is the largest department store in Brazilian marketplaces/e-commerce. Olist connects small businesses from all over Brazil to channels without hassle and with a single contract. Those merchants are able to sell their products through the Olist Store and ship them directly to the customers using Olist logistics partners.
Objective: Build recommendation system to increase sales by give suggestion products with purposes to reduce browsing time and make the customer purchase faster.
Expected Output: Could exploit the data to give best recommendation system in order to give each user's individual tastes and preferences.
Dataset: https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce Website: www.olist.com
-----ABOUT DATASET FROM OLIST KAGGLE----- Brazilian E-Commerce Public Dataset by Olist Welcome! This is a Brazilian ecommerce public dataset of orders made at Olist Store. The dataset has information of 100k orders from 2016 to 2018 made at multiple marketplaces in Brazil. Its features allows viewing an order from multiple dimensions: from order status, price, payment and freight performance to customer location, product attributes and finally reviews written by customers. We also released a geolocation dataset that relates Brazilian zip codes to lat/lng coordinates.