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Text Analytics

Text analytics platforms rely on Natural Language Processing (NLP) to make sense of unstructured data captured from a range of sources: verbatim comments in surveys, reviews posted in forums, posts in social media, comments transcribed in call centres etc. Key features include sentiment; categorisation or topic analysis; entity extraction (eg to identify brands); and visualisation – usually in an online dashboard. Text analytics capabilities are also built into some platforms in other categories (Social Listening, Surveys).

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    Heartbeat AI

    Customer decisions are driven by EMOTION - not reason. People express emotions using their facial expressions, body language, and tone of voice. They also describe emotions using natural language: in conversations, open-ended survey questions, interviews, social media, and customer phone calls. Heartbeat AI platform transforms text input from....

  • Wordstat

    WordStat is desktop software for content analysis and text mining. It features rapid extraction of themes and trends,  integration with SimStat for statistical data analysis and QDA Miner for qualitative data analysis. It is used for content analysis of open-ended responses from interview or focus group transcripts; business and competitor intelligence; information extraction from incident reports and customer complaints; automatic tagging and classification of documents; and taxonomy development and validation.

Showing Text Analytics 31-31 of 31
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