This study aims to develop a structured analytical framework that extends the conventional descriptive use of the Net Promoter Score (NPS) toward diagnostic, confirmatory and institutionalized customer experience improvement.
A reproducible analytical-computational framework with four stages is proposed: Observe (control charts and capability analysis), Explore (causal segmentation using Gini-weighted decision trees, conditional probabilities and the Five Whys method), Confirm (non-parametric hypothesis testing with bootstrap procedures) and Institutionalize (standardization through structured templates and pedagogical strategies). The framework was validated in two organizational contexts, one service-based and one manufacturing-based.
The results of this study demonstrate that the proposed framework enables organizations to move from static NPS measurement toward a structured analytical workflow that supports diagnostic explanation, formal validation of interventions and systematic organizational learning. Across both cases, the framework showed methodological robustness, cross-sector applicability and pedagogical value.
This study offers a novel analytical–computational framework that transforms NPS from a passive indicator into a dynamic mechanism for explaining, validating and institutionalizing customer experience improvements. By integrating exploratory, confirmatory and learning-oriented analytics within a unified structure, the framework advances the methodological role of NPS in both customer experience research and practice.
