Digital VoC analysis for product/service quality tracking in the era of Quality 4.0

Purpose – This study aims to explore how organizations can leverage digital voice-of-customer (VoC) data to effectively monitor and enhance the quality of products and services. Specifically, it investigatesthe application of the KA (key attribute) VoC Map, a novel analytical framework designed to systematically extract insights from digital customer feedback, categorize key product and service attributes and support continuous quality improvement in line with Quality 4.0 principles. Design/methodology/approach – The KA-VoC Map leveragestopic modeling algorithmsto analyze customer feedback from digital platforms, identifying key attributes and categorizing them based on their frequency of discussion (mean topical prevalence) and associated sentiment (mean rating proportion). A case study involving smartwatch feedback collected from 2021 to 2024 demonstrates the practical implementation of the methodology. Findings – The results reveal the utility of the KA-VoC Map in identifying and prioritizing key quality attributes, monitoring their evolution over time, and supporting continuous quality improvement. Originality/value – This study introduces a novel methodological enhancement of the KA-VoC Map, demonstrating its use for dynamic quality tracking over time. This approach enables continuous monitoring of customer sentiment evolution, providing actionable insights for proactive quality management in the era of Quality 4.0.