This repository contains code extracts from a data analysis project I worked on as part of the Career Foundry Data Analytics Bootcamp.
Please note, although Instacart is a real company that has made their data available online, the contents of this project brief have been fabricated for the purpose of learning.
Instacart is an online grocery store that operates through an app. In this project, I have analysed by buying patterns in relation to customer characteristics to support improved promotion targeting and marketing spend.
Key questions/requests from the marketing team include:
- What are the busiest days of the week and hours of the day?
- Are ther particular times of the day when people spend the most money?
- Which departments have the highest frequency of product orders?
- How often do users return to Instacart?
- Are there differences in ordering habits based on a customer’s loyalty status?
- Are there differences in ordering habits based on a customer’s region?
- Is there a connection between age and family status in terms of ordering habits?
- What differences can you find in ordering habits of different customer profiles?
The main purpose of this project was to develop my knowledge of Python and to familiarise myself with platforms such as Jupyter.