instacartInstacart is an online grocery store that utilizes an app to make sales. The company is interested in discovering more about its sales patterns to enhance the effectiveness of its advertising campaigns. They assume they cannot target everyone so they are considering a targeted marketing strategy. They want to target different customers with applicable marketing campaigns to see whether they influence the sale of their products
Objective: Analyze Instacart's data, derive insights, and suggest strategies for marketing based on customer segmentation to improve sales and customer targeting.
Procedures: Importing Libraries, Importing & Exporting Datasets, Descriptive analysis, Data consistency checks, Data wrangling & subsetting, Data merging, Deriving variables, Grouping &, Aggregating data, Visualizations with Python Libraries, Reporting in Excel, Population flows
Tools used: Python, Pandas, Jupyter, Excel, PowerPoint
What are the busiest days? Busiest hour of day?
What is the time of day where most money is spent?
What are the product’s price groupings?
What are the most popular products?
What is the distribution of customers based on loyalty?
What are the ordering habits based on loyalty & region
What is the ordering behavior based on age?
What is the ordering behavior based on family status & income
KEY QUESTIONS
Population Flow
RESULTS
Instacart's busiest days of the week are Saturday and Sunday
Tuesday and Wednesday are the least busy days of the week
The busiest time of day is between 9:00 AM until 5:00 PM and slowly decreases until the morning
Example Python Coding
Image 1
Image 2
Here we answer some key questions with derivations & aggregations with the goal of learning more about the customer and their behavior
Image 1 is a derivation making a new column depicting the busiest days of sales
Image 2 is an example aggregation to discover the average orders per user across the department
Instacarts Customers
Loyal Customers have placed over 40 orders, Regular Customers have placed between 10 and 40 orders and New customers have placed 10 or fewer orders
Married, young adults with kids make up most of Instacart's customers
Customers with kids make up 75% of the total customers
Families with kids are also responsible for 75% of sales in the highest-selling categories (produce, dairy, snacks, frozen, deli, dry goods, bakery)
RECOMMENDATIONS
Schedule ads on Tuesdays and Wednesdays to try to increase sales
Schedule promos of big-ticket items over the weekend when most users are on the app
It is important to retain and speak to the largest portion of the client base as its the best opportunity for growth- gear ads towards young families with kids
