CallMiner Enhances AI-Powered Conversation Intelligence Platform


CallMiner’s new and updated platform features include semantic search that empowers users to search via natural language to return results where exact or similar language might appear in omnichannel customer interactions.

CallMiner, a provider of conversation intelligence, at its annual LISTEN user conference today introduced new and enhanced artificial intelligence features in the CallMiner platform.

“Given the massive scale of structured and unstructured data that many organizations are collecting and analyzing via their customer service centers and other sources, AI-powered technologies offer a wide range of potential benefits,” said Jeff Gallino, CEO and co-founder of CallMiner, in a statement. “CallMiner’s recent platform enhancements are focused on meeting specific organizational needs and challenges and ultimately delivering meaningful outcomes and transformational results for our customers.”

CallMiner’s new and updated platform features include the following:

  • Semantic search that empowers users to search via natural language to return results where exact or similar language might appear in omnichannel customer interactions.
  • Expanded agent guidance to chat via CallMiner RealTime, which can now provide real-time agent guidance on chat interactions. With these updates, users can create alerts and provide agents with contextual guidance on multiple chats and assign different alerts depending on the interaction channel with natural language understanding (NLU), customized for both chat and voice interactions.
  • An expanded contact center-as-a-service (CCaaS) integration ecosystem, supporting audio acquisition from providers like NICE, Genesys, Five9, TalkDesk, and Amazon Connect.
  • An improved user experience in CallMiner Coach, with new features, including dashboards, modules, reporting capabilities, filtering capabilities, and optimized search. Supervisors can now configure CallMiner Coach to display and explore the contact center and performance metrics most important to their organizations. This includes machine learning capabilities that display how agents are performing since their last coaching interaction, specific areas that need to be addressed, and how supervisors can most effectively coach individual agents. Example interactions and coaching tips are automatically delivered to make training interactions between supervisors and agents more effective.
  • Updated reporting dashboards within CallMiner Analyze, with the ability to create multiple dashboards based on role and need, as well as edit, duplicate and share those dashboards.
  • Enhanced reporting capabilities, including customized notifications based on AI-driven categories, data trends and deviations from baseline numbers.

“Our innovation over the past year, including these new and enhanced features, affirm CallMiner’s depth of analytics and position as a leader in AI in the conversation intelligence industry,” said Bruce McMahon, chief product officer of CallMiner, in a statement. “AI has always been at the center of the CallMiner platform, and I’m proud to continue to deliver AI-driven capabilities that prioritize ease of use, cross-departmental value, and overall ROI for our customers.”