Jan-Feb, 2024

Case Study: 'Instacart'
website views analysis

Marketing Strategy for an Online Grocery Store.

(CF student case study)

'Instacart' Portfolio Project Cover
Fig 1. Portfolio case study - intro cover

Goal

Analyze customer purchasing behaviors to create a customer-segmented classification model for targeted marketing strategies and boosting sales revenue.

Here are the questions they want me to answer first:

1. What are the busiest days of the week and hours of the day?
2. At what times of the day do people tend to spend the most money?
3. Is there a connection between age and family status in terms of ordering habits?
4. Which types of products are most popular?
5. What are the characteristics and spending habits of different customer profiles based on Income?

Instacart
Fig 2. Workflow of my analysis
Instacart
Fig 3. Insights gained from my analysis
Instcart
Fig 4. Final Recommendations
Instcart
Fig 4. Final Recommendations
Instcart
Fig 4. Final Recommendations

final thoughts

In conclusion, The analysis revealed that Saturdays and Sundays between 8 AM and 4 PM are the busiest shopping hours, with 9 AM marking the peak spending time. Most orders consist of low-to-mid-range priced products, primarily fresh food items such as produce, meat, seafood, and dairy. Shopping behavior varies significantly by income, particularly in average order prices. Recommendations include targeting high-income customers with premium product promotions during early morning hours, utilizing loyalty data for tailored campaigns, and introducing discount programs to boost regular customer retention. Further exploration of underperforming products and time-specific purchasing trends is advised..

  • View Full Data Documentation in GitHub

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