Forecast Subsequent Purchase

Requirements Clarification & Assessment

To effectively forecast the next item a new basket will contain, it's crucial to understand the following aspects:

1. Data Availability:

   • Historical Purchase Data: Ensure access to a comprehensive dataset of past purchases, including user IDs, transaction timestamps, and items purchased.
   • User Profiles: Information on user demographics or preferences can enhance prediction accuracy.

2. Objective:

   • Accuracy vs. Speed: Determine if the focus is on highly accurate predictions or rapid, real-time recommendations.
   • Type of Items: Are we predicting a specific category of items or any item the user might purchase?

3. Constraints:

   • Scalability: Consider the volume of data and the computational resources required.
   • Privacy: Ensure compliance with data privacy regulations when using user data.

4. Evaluation Metrics:

   • Define what success looks like. Possible metrics include precision, recall, F1-score, or a business metric like increased sales or customer satisfaction.