CloudCherry Enhances Predictive Analytics Product

CloudCherry, a customer experience management company, has enhanced its CX platform's predictive analytics engine, reducing the time required to analyze customer feedback at scale, reveal insights, and predict trends.

"Brands around the globe are under ever-increasing pressure to understand and get ahead of customer needs, tackle churn, and drive profitability," said Arvi Krishnaswamy, vice president of products at CloudCherry, in a statement. "With the help of machine learning and deep learning, we've been able to achieve up to 98 percent accuracy in our classification of customer sentiment. This represents a significant milestone, giving companies the power to listen to their customers at scale, across a multitude of channels, mine their words for meaningful insights, and identify trends faster and more accurately than ever before."

CloudCherry's advanced analytics engine uses machine learning and deep learning to crunch billions of unstructured customer feedback datapoints across a multitude of channels, in real time, revealing key trends, a deep understanding of customer sentiment, and the underlying themes and drivers of customer experience. The enhancements allow users to create multilevel classification hierarchies for key driver analysis and drill down as needed.

CloudCherry's insights not only reveal how customer conversations are shaping brand experiences but empower employees with a prioritized list of actions to take to deliver outcomes.

To cater to agrowing global customer base, CloudCherry has also expanded its international coverage with data analysis now supporting more than 50 languages.