An Algorithmic Approach to Quickly Identifying the Most Useful Survey Comments
Most large organizations struggle to understand and use their open-ended comments. Hundreds or even thousands of comments can be difficult to wade through, analyze, and act on.
OrgVitality has solved this problem with a supervised machine-learning system that classifies, identifies, and predicts the most useful or actionable survey comments - within seconds.
OV VOICE, or, the Value-Optimized Intelligent Comment Extractor works on high-volume datasets with text in any language. Each comment is assigned a score, or Usefulness Quotient (UQ) of 0-100. The higher the score, the more useful or actionable the comment is likely to be. The comments and their respective UQ are fed into user-friendly, interactive reports that allow comparison by topic, opinion, and employee segments. Survey users can identify the most important comments for different groups of stakeholders to read, and which to prioritize based on usefulness.
Just released! A new book by OrgVitality Partner and Vice President, Dr. Victoria Hendrickson
Needle in the Haystack provides the results from Dr. Hendrickson's multi-year research projects that defined, profiled, and ultimately led to the prediction of the survey comments most likely to drive organizational change. Readers will find practical advice on designing qualitative surveys, analysis of text data, and reporting of comments.
Email email@example.com to see how the OV VOICE can help you.
OrgVitality Approach to Comments
Are you buried underneath a stack of comments, unsure how to find the best ones? Or not even sure you received any useful ones?
OV continues to lead the research into soliciting quality open-ended comments:
Asking the right questions: Our research has identified how to structure open ended questions to get the most useful feedback
Nudging for usefulness: We’ve identified how to introduce the open ended comment section of the survey for up to five times more useful comments
Identifying useful comments: The OV VOICE, a machine learning approach powered by our research findings identifies the likelihood that each comment will be actionable
User friendly reporting: Certain combinations of employee segments and opinions elucidate unique findings across groups