KaCeeUnruh / Ecommerce_Analysis-Python

Identify the correlation between customer buying behavior and ecommerce marketing strategy using NumPy, pandas, Jupyter, matplotlib, and Excel.
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Ecommerce Analysis - Python Project

CareerFoundry data analysis for Instacart

Summary

You’re an analyst for an existing company, Instacart, an online grocery store that operates through an app. Instacart already has very good sales, but they want to uncover more information about their sales patterns. Your task is to perform an initial data and exploratory analysis of some of their data in order to derive insights and suggest strategies for better segmentation based on the provided criteria.

Key Questions and Objectives

1) What are the busiest days of the week and hours? 2) Are there particular times of the day when people spend the most money? 3) Create simpler price range groupings to help direct marketing efforts. 4) Are there certain types of products that are more popular than others? 5) What’s the distribution among users in regards to their brand loyalty? 6) Are there differences in ordering habits based on a customer’s loyalty status? 7) Are there differences in ordering habits based on a customer’s region? 8) Is there a connection between age and family status in terms of ordering habits? 9) What different classifications does the demographic information suggest? Age? Income? Certain types of goods? Family status? 10) What differences can you find in ordering habits of different customer profiles?

Context

The stakeholders are most interested in the variety of customers in their database along with their purchasing behaviors. They assume they can't target everyone using the same methods, and they’re considering a targeted marketing strategy. They want to target different customers with applicable marketing campaigns to see whether they have an effect on the sale of their products. This analysis will inform what this strategy might look like to ensure Instacart targets the right customer profiles with the appropriate products.

Data Sets

Datasets were presented by CareerFoundry: