MIS272: Predictive Analytics - Computer Science Case Study Assessment Answer

Case study
Olist Store is the largest department store in the Brazilian marketplaces. Olist connects several small businesses in Brazil to customers so those Brazilian merchants can sell their products to their customers through Olist. Shipment of products to customers is done using Olist logistics partners. Customers buy/order products through Olist store and sellers get notified to then fulfil the order. Customers will then receive the product/s they have ordered (or are notified of an estimated delivery date). A satisfaction survey is sent to the customer by email too so they can write some feedback comments on the purchase experience.
The data set that you are given contains a large number of customer orders and customer satisfaction review scores for each order/purchase experience. You are asked to explore and analyse this data set and then, create insights as to what patterns relate to the different customer satisfaction levels (1 to 5, with 5 being most satisfied). You are expected to analyse the data set using exploratory methods, develop appropriate predictive models to test your exploratory hypotheses, then evaluate and further improve your models.
The original data set contained 100K product orders from 2016 to 2018; however, to avoid computational power issues, a sample of 20K orders have been extracted for this assignment. It is expected that no further sampling will be done on this data set. More details on the data set can be found at https://www.kaggle.com/olistbr/brazilian-ecommerce. It is strongly recommended that you read the data definitions to better understand the data context and terminology before you attempt the development of the analytic solution/s.

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