Analyzes available case data to zero-in on the user’s sentiment and gauge dissatisfaction enabling agents to empathize and personalize accordingly
The app then taps in a variety of factors such as case sentiment, case scoring, case priority, product group, delta time, comments exchanged etc., to identify cases that are near the red mark and prioritize them over others.
Factors in the customer profile and sentiment analysis data to better understand what the customer wants
Lastly, routes the case to the best agent with expertise on the said topic right off the bat to minimize mean time to resolve (MTTR)
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