LivePerson had 16 patents in future of work during Q2 2024. LivePerson Inc filed patents in Q2 2024 for a system that analyzes conversation data between users and agents to identify intents, contexts, and elements, and generate recommendations for addressing these intents. Another patent discloses a framework for automated bots to determine whether to present opt-in offers for supplemental communications during real-time messaging exchanges with users, facilitating a seamless process for obtaining user consent for further communication. GlobalData’s report on LivePerson gives a 360-degree view of the company including its patenting strategy. Buy the report here.
LivePerson had no grants in future of work as a theme in Q2 2024.
Recent Patents
Application: Intent analysis for call center response generation (Patent ID: US20240137444A1)
The patent filed by LivePerson Inc. describes a system that analyzes conversation data between users and agents to identify intents, contexts, and elements within these conversations. Based on this analysis, the system generates recommendations for improving agent performance and monitors adherence to these recommendations during new conversations. The system also compares client performance metrics to target performance metrics, generates insights, and provides diagnostic information using a trained machine learning algorithm.
The computer-implemented method and system outlined in the patent focus on enhancing agent performance by analyzing conversation data, calculating performance metrics, and generating recommendations based on identified intents and elements. The system also anonymizes target performance metrics, monitors adherence to recommendations during new conversations, and provides insights into agent issues and corresponding recommendations. Additionally, the patent includes provisions for generating diagnostic information and comparing client performance to target performance using a trained machine learning algorithm. Overall, the patent aims to optimize agent performance through data-driven analysis and actionable recommendations derived from conversation data.
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