/InstaCart-Python

Career Foundry data analytics project to provide a client recommendations on a marketing strategy. Jupyter notebooks include cleaning and merging data along with creating new columns to offer the best understanding of consumers' interactions with products.

Primary LanguageJupyter Notebook

InstaCart-Python

InstaCart recognizes the need to establish a targeted marketing strategy for different consumers of their app. They want to determine whether the marketing campaigns have an effect on the sale of products. I analyzed InstaCart's data to inform this marketing strategy to target customer profiles with appropriate products.

Key Questions and Objectives

● The sales team needs to know what the busiest days of the week and hours of the day are in order to schedule ads at times when there are fewer orders.

● Are there are particular times of the day when people spend the most money?

● Marketing and sales want to use simpler price range groupings to help direct their efforts.

● Are there certain types of products that are more popular than others? The marketing and sales teams want to know which departments have the highest frequency of product orders.

● The marketing and sales teams are particularly interested in the different types of customers in their system and how their ordering behaviors differ.

Note: Instacart is a real company that’s made their data available online. However, the contents of this project brief have been fabricated for the purpose of this Achievement.

Data

Data Dictionary.

InstaCart Orders & Products Datasets

Note: Fabricated data from Career Foundry is unavailable for upload because of the size limitations of GitHub