Data
Instacart provided an Data Set featuring customer
Instacart
Objective
Instacart, an online grocery store that operates through an app, that wanted to uncover more information about their sales patterns.Therefore we analysed the existing data in order to derive insights and suggest strategies for better segmentation based on the provided criteria.
Techniques applied
Data Cleaning: Wrangling, Combining and Exporting Data, Grouping Data and Aggregating Variables, Python Visualization, Excel Report
Tools
Analysis
Key Questions
Which days are the busiest?
Results
The busiest days of the week are the weekends with saturday being the busiest day.
Key Questions
When do the customers spent the mpst money?
Results
Instacart's customers spend the most mones on friday and saturday with expenditure peaking from 2 am to 7 am.
Key Questions
What different kind of customers do we have?
Results
There are 4 different kinds of customer profiles: married with dependants, single with dependants, single wih no dependants and married with no dependants. The majority of custormers are parents with a partner followed by single adults.
Further Insights
Recommendations
- Customer profile marketing: Advertise affordable products within specific departments such as produce, babies and pantry items to middle age group and families who generate significant revenue. Additionally ,targeting the low income profile customers with cost saving promortions would be crucial.
- Time-based marketing: To increase revenue, schedule ads on Wednesday and Tuesday after 15, as these are the least busiest days and as sales begins to decrease after 15 up to morning 6.
- High prices product marketing: AInstacart should place more ads for high-priced products in the early morning hours from 4 am until 7 am.