intent managerStart with intent recognition, end with business results
Intent Manager uses our industry-leading natural language understanding (NLU) engine for intent recognition, to identify conversations ideal for an automated chatbot, and to inform critical business decisions.
Get a demoIntent Manager transforms how you run your business
Add efficiency with a user intent-driven automated chatbot.
Optimize operations with intent-based performance data.
Make informed business decisions based on what consumers are saying.
Understand consumer intents and automate conversations
LivePerson’s proprietary NLU engine enables real-time intent detection, so you can determine the best conversation flows to add to your automated chatbot in Conversation Builder — our intuitive chatbot builder. We’ve used over a billion conversations as training data for machine-learning algorithms that power our AI. Our NLU outperforms many competitive benchmarks related to accuracy, precision, and recall across a variety of industries.
Optimize contact center operations with intent-based performance data
Identify intents with poor consumer sentiment and take action. Route intents to the automated chatbot or agent best equipped to resolve them. Improve agent training and tune bot performance to improve intents with low sentiment.
Make informed business decisions
Intent Manager’s real-time intent detection helps brands discover emerging needs related to customer needs, from product defects to service disruptions, billing and payment issues, and more. Use this information to improve products and services, form new policies or outbound sales processes, and improve the quality and availability of important consumer information.
Easily map new, misunderstood phrases to existing user intents
Turn human insights into actionable feedback to improve intent comprehension with AI Annotator. Together with Intent Manager, this makes labeling conversation data and providing performance feedback stress-free — helping agents be more productive and your automated chatbot a lot smarter.
Get up and running quickly with intent recognition starter packs for your industry
Intent Recognition
Retail
LivePerson’s natural language processing, machine-learning algorithms, and deep learning neural networks analyzed over a billion conversations to classify the top intents for a variety of industries. Proprietary large-scale, pre-trained language models (ELMo) were used to preconfigure these intents. This makes it possible for Intent Manager to automatically recognize up to 65% of intents with little-to-no configuration.
Intent recognition
Financial Services
LivePerson’s natural language processing, machine-learning algorithms, and deep learning neural networks analyzed over a billion conversations to classify the top intents for a variety of industries. Proprietary large-scale, pre-trained language models (ELMo) were used to preconfigure these intents. This makes it possible for Intent Manager to automatically recognize up to 65% of intents with little-to-no configuration.
Intent Recognition
Insurance
LivePerson’s natural language processing, machine-learning algorithms, and deep learning neural networks analyzed over a billion conversations to classify the top intents for a variety of industries. Proprietary large-scale, pre-trained language models (ELMo) were used to preconfigure these intents. This makes it possible for Intent Manager to automatically recognize up to 65% of intents with little-to-no configuration.ents with little-to-no configuration.
Telecom
Intent Detection
LivePerson’s natural language processing, machine-learning algorithms, and deep learning neural networks analyzed over a billion conversations to classify the top intents for a variety of industries. Proprietary large-scale, pre-trained language models (ELMo) were used to preconfigure these intents. This makes it possible for Intent Manager to automatically recognize up to 65% of intents with little-to-no configuration.
Airline / Travel
Intent Detection
LivePerson’s natural language processing, machine-learning algorithms, and deep learning neural networks analyzed over a billion conversations to classify the top intents for a variety of industries. Proprietary large-scale, pre-trained language models (ELMo) were used to preconfigure these intents. This makes it possible for Intent Manager to automatically recognize up to 65% of intents with little-to-no configuration.
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