Predict customer purchasing behavior

Trigger: A marketing campaign planning cycle begins or a periodic sales forecasting request requires updated customer propensity scores.

1. Extract historical transaction and behavioral data
2. Segment customers based on demographic and past interaction attributes
3. Apply predictive models to identify patterns in purchase frequency and volume
4. Calculate propensity-to-buy scores for targeted segments
5. Validate model accuracy against historical holdout datasets
6. Distribute purchasing predictions to sales and marketing systems

Outcome: A validated dataset or dashboard is delivered containing future purchase probabilities and product affinities mapped to specific customer segments.