Fcharm_prin_foc_si_prin_apa_feat_aris Apr 2026

Assign a weight based on the high-value nature of that focus (e.g., Purchases = 1.0, FAQ views = 0.2).

Identify the primary interaction type (e.g., "Online Purchase", "Support Call", "Mobile Login") with the highest frequency per customer. fcharm_prin_foc_si_prin_apa_feat_aris

Calculate the inverse of the frequency of this behavior across the entire population (lower population frequency = higher prin_apa score). Step D (Arising - feat_aris ): Normalize the final score. 3. Interpretation Assign a weight based on the high-value nature

This feature measures the . It identifies the core activity a customer engages in, determines its importance, and calculates how rare (distinct) that behavior is compared to the overall population. 1. Conceptual Formula Step D (Arising - feat_aris ): Normalize the final score

To make this feature actionable for your specific dataset, I can:

Principal/Primary Apartness (measures how distinct this behavior is from the norm). feat_aris: Feature Arising (the resulting generated score). Definition: Principal Focal Significance Apartness Feature