To analyze omni-channel customer feedback pertaining to LivePerson’s AI-powered conversational platform to identify pain points and make improvements.
LivePerson has one set of customers who just use the company’s chat services to help sell products and another set of customers who use LiveEngage. The former group simply logs in and sees a dashboard compiled from chats that analysts could view and pull insights from themselves, while the latter group has a LivePerson analyst completing that work for customers and supplying reports. For both scenarios, LivePerson had previously been using Clarabridge to compile data.
LivePerson wanted more flexibility and features to help support data analytics, so it turned to Stratifyd for a solution since there’s a vast amount of chat volume coming in from its enterprise clients. LivePerson uses Stratifyd’s platform to pick out valuable information from chats and we provide the company with dual channel analytics, meaning it has agent and customer verbatims for more comprehensive insights.
Our unique analytics have identified ways to improve in the areas of agent response time, which responses were most and least helpful to customers, and when customers had difficulty finding something on clients’ websites. These insights have led to improved customer experiences across the board.
Our platform’s capabilities include unsupervised machine learning to remove human bias from reporting, predictive intelligence to fill in gaps of missing CSAT scores, visualizations for more powerful insights, and ease-of-use so changes to the modeling can be made quickly.
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