Instacart Data Analysis




- Project name
- Client
- Tools used
- GitHub
Instacart Case study
Instacart
Python, PowerPoints
Overview
Instacart is an online grocery store that operates through a mobile app, offering customers the convenience of shopping from home. This project analyzes its sales data to uncover customer purchasing patterns, supporting a targeted marketing strategy.
The visualizations provide key insights into consumer purchasing behavior, revealing distinct patterns across days and hours. Saturday and Sunday are the busiest days of the week, reflecting higher engagement likely due to leisure time and convenience for shopping. Conversely, Tuesday and Wednesday see the least activity, indicating that weekdays may be busier with work and other commitments.
Furthermore, there appears to be a link between the timing of orders and spending patterns. The analysis shows that customers tend to spend more during specific times, possibly aligning with promotional offers or targeted marketing during peak shopping hours. These insights emphasize the importance of tailoring marketing strategies and operational efficiencies to align with consumer habits for maximum impact