Purchase Behavior Prediction

Understanding the Problem

• Objective: Develop a machine learning model to predict if a customer will make a purchase today based on their profile.
• Data Provided:
  • Residential location
  • Income level
  • Gender
  • Occupation
• Target Variable: Binary (Purchase Today: Yes/No)

Key Considerations

• Temporal Data: The challenge lies in using static data (location, income, etc.) to predict dynamic behavior (daily purchase decisions).
• Additional Data Needs: To improve model accuracy, additional features such as browsing history, cart status, or recent interactions could be beneficial.
• Data Quality: Ensure that the data is clean, complete, and representative of the customer population.

Assumptions

• The customer profile data is up-to-date and accurately reflects current customer attributes.
• The purchase behavior is influenced by the provided attributes.