Contact center business leaders are challenged to equally optimize for operational efficiency, customer satisfaction, employee retention, and risk and compliance, yet are forced to make tradeoffs as improvements to one call center metric results in decrements to the other KPIs
SambaNova Contact Center Intelligence enables enterprises to overcome the contact center productivity paradox by seamlessly integrating generative AI into existing contact center workflows, with no need to rip and replace existing tools.
Receive detailed, real-time guidance to enable contact center employees to focus on the customer and guide them to deliver a better experience, without the need to worry about administrative overhead
Summarize the conversation transcript at the end of each call for the agent to tweak and save for improved call logging
Automatically extract customer provided information (e.g. email addresses) for manual and automated workflows
Integrate real-time sentiment classification in agent consoles to guide the agents on the “best way” to respond
Classify customers’ utterances to improve call routing, provide next-best-action recommendations, and more
Help agents find answers/procedures to address the customer questions by retrieving relevant document, passage, and answer from internal knowledge base
Understand every customer interaction with consistent, scalable, detailed, and accurate reporting of all contact center customer engagements
Tag each call automatically with attributes such as topics, issues, action items, and sentiment for easy discovery of calls
Identify exactly when the customer sentiment changed and analyze root cause
Identify who said what and when, with high accuracy
Identify exactly when the agent sentiment changed and analyze root cause
Develop complete nuanced understanding of customer conversations such as talk time between agent and customers, nature of dialog, and more
Provide greater security and privacy for customers and their data
Add an additional layer of security to caller identification through matching callers with their unique voice print
Identify PII data to apply masking rules before storing customer conversation transcripts