Voice Segmentation in Social and VoC Data

This technical report discusses the critical importance of voice segmentation in social listening and voice of customer (VoC) data. It outlines the challenges associated with isolating relevant data for analysis, particularly the noise created by spam, promotional content, and bots that complicate the extraction of genuine stakeholder voices. The report emphasizes that effective data cleaning and classification are essential for accurate social and media insights. It details how new AI technologies can enhance data relevance and stakeholder segmentation, addressing issues such as data volume, source ambiguity, and limitations of traditional analysis methods. The document also presents a case study illustrating the impact of inaccurate sentiment analysis on brand metrics, highlighting the necessity of precise data segmentation to avoid misleading consumer intelligence. Overall, the report aims to provide insights into improving data quality and relevance in social intelligence practices.