Customer insights platform HumanListening has added two new features, time series analysis for qual AI, and a new way to measure the effectiveness of qualitative outputs.
HumanListening's offering includes communities, quant survey insights and AI-driven qual. EVE Qual Pro (launched in April) embeds proven qualitative techniques like laddering, projective methods and storytelling directly into Qual AI conversations.
The new time series analysis for Qual AI is designed to provide an explanation for trends and movements emerging from tracking studies: users can track how topic mentions and sentiment shift across the life of a study, for a picture of how people's thinking evolves. The feature includes Gen AI summaries and statistical testing of key findings.
The second update assesses the quality and usability of data coming back from open-ended responses, and includes two new scores, Text Quality Score and Human Insights Factor. The former evaluates reading ease, conversation length, and offers detection of 'AI or gibberish.' The latter evaluates the number of topics, network edges and density within a response. Combined, these promise teams 'a consistent way to judge whether their qualitative data is rich enough to act on.'
Managing Partner Chris Barry (pictured) says the updates are about 'giving research teams a real answer to what's really driving the changes in my study and how robust is the qualitative data to support my decisions?'
Web site: www.humanlistening.com .
All articles 2006-23 written and edited by Mel Crowther and/or Nick Thomas, 2024- by Nick Thomas, unless otherwise stated.
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