Luminoso Launches Score Drivers for Analyzing Customer and Employee Feedback

Luminoso, an artificial intelligence and natural language understanding (NLU) company for customer insights, today launched Score Drivers, a machine learning-powered solution to help companies automate how they find drivers in qualitative and quantitative feedback from their customers and employees.

"Today's businesses are buried under an intense amount of quantitative and qualitative data, such as surveys and product reviews. It's nearly impossible for analysts and CX professionals to find meaningful insights that impact critical business metrics, such as product ratings and satisfaction scores, without significant amounts of human intervention," said Ying Chen, chief product officer at Luminoso, in a statement. "Score Drivers offers an intelligent way to automate at scale how an organization understands these mixed data sets so they can go beyond the numbers to learn which specific aspects of their product, service, or experience need improvement."

Score Drivers analyzes unstructured reviews and survey feedback and reveals how this unstructured data correlates with quantitative ratings. It can automatically match terms with broader concepts and take into account each concept's relevance, frequency, and importance. Users can prioritize feedback by understanding how strongly elements with positive or negative impact correlate to metrics such as satisfaction scores and numerical product ratings.

Luminoso is offering Score Drivers as part of Luminoso Daylight, an application for analyzing unstructured data like product reviews, open-ended survey responses, and call center transcripts. Daylight is powered by Luminoso's proprietary QuickLearn technology, incorporating artificial intelligence and natural language understanding.

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