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Investigating Instacart's Customer Behaviour

Descriptive analysis to identify customer segments using data from Instacart.

Note: this analysis do was conducted using publicly available data. The contents of this project are for educational purposes and do not reflect the internal operations of Instacart.

Context

The Instacart 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. Your analysis will inform what this strategy might look like to ensure Instacart targets the right customer profiles with the appropriate products.

Key Questions

The stakeholders would like to be able to answer the following key questions:

  1. The sales team needs to know what the busiest days of the week and hours of the day are (i.e., the days and times with the most orders) in order to schedule ads at times when there are fewer orders.
  2. They also want to know whether there are particular times of the day when people spend the most money, as this might inform the type of products they advertise at these times.
  3. Instacart has alot of products with different price tags. Marketing and sales want to use simpler price range groupings to help direct their efforts.
  4. 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.
  5. The marketing and sales teams are particularly interested in the different types of customers in their system and how their ordering behaviors differ.

Datasets

Deliverables

  • Python codes
  • Excel Report

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Descriptive analysis to identify customer segments using data from Instacart.

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