Conversation analytics platforms enable service departments to extract insights by processing natural language interactions between customers and the organization. Conversation analytics platforms focus on voice and text interactions, whether postcontact or real-time, by telephone, chatbot, virtual assistant, live chat, messaging, and email channels. Extracting insights from natural language customer interactions is crucial for optimizing customer service. Conversation analytics allows customer service leaders to identify opportunities to improve customer and agent experience. It helps track process improvements, customer sentiment and service department compliance with regulatory and quality assurance guidelines; reduces the cost of agent training; and provides agent assistance to improve productivity.
Gartner defines speech-to-text (STT) platforms as business applications that process speech content, either live or in batch to produce: A transcript of the conversation Metadata about the call, the callers, attributes of call, emotional context Value-added services (e.g., biometric, legal) Workflow tools to support downstream work (e.g., intent detection, CRM updates) The capabilities of STT solutions vary. At a minimum, providers can offer a set of generic APIs with no tailored industry offering. More advanced solutions support complex deployments of edge technologies tailored to specific industries such as medical and legal. As natural language experiences are rapidly adopted by customers, users and employees, STT solutions must address a number of deployment configurations and be tailored for end-user domain knowledge to improve their accuracy.