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GroupSolver Is First to Give Online Research The Intelligence It Needs To Automatically Translate Free-Text Survey Responses Into Actionable Insights

There is a growing need to understand consumer sentiment with the same depth of insights as moderated in-person focus groups but more quickly and without their high cost or, more recently, challenges of convening study panels in a global pandemic.

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GroupSolver, a leading provider of intelligent market research and digital collaboration solutions, today announced a feature for its online survey platform that solves this challenge by enabling researchers to ask the same “what,” “why” and “how” questions used in focus groups and quantify actionable results in real-time without requiring any additional data preparation or processing.

“The addition of this AutoTheme™ feature makes it possible to process data from unstructured free-text answers using our online survey platform’s unique combination of machine learning algorithms and crowdsourced respondent intelligence,” said Rasto Ivanic, GroupSolver co-founder and CEO. “

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By allowing participants to answer open-ended questions in their own words and simultaneously collaborate on quantifying the collective responses, we get researchers to the heart of issues faster and less expensively than any other approach. We will continue to offer online researchers new and powerful ways to combine, correlate and visualize our high-value free-text natural-language data in their surveys.”

GroupSolver’s AutoTheme feature goes beyond the platform’s previous ability to clean, filter and organize all qualitative free-text data in real time. The new algorithm provides the additional intelligence to automatically group answers that are not identical to each other but meet user-configurable parameters for thematic commonality. The researcher chooses the desired grouping sensitivity level from least to most specific with a slider scale to obtain the desired level of granularity of insights. This further accelerates the delivery of valuable insights in situations where timely understanding of the voice of customer at large scale is critical, for example in media campaigns evaluations or when collecting product feedback.

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