Voice analytics assesses and records spoken conversations through speech recognition, natural language processing (NLP), and natural language understanding (NLU).
By harnessing these technologies, voice analytics assesses audio patterns, converting speech to text and assessing multiple factors. In some cases this includes intent, sentiment, and resolution success.
As these use cases evolve, the voice and speech analytics market is expected to grow by $1.73 billion between 2020 and 2025, with an annual growth rate of almost 16 percent - according to Technavio.
The following top trends are perhaps supercharging this growth and characterizing the future of call center voice analytics.
Biometrics Built on Voice Analytics
Voice biometrics is a system that deciphers the distinctive qualities of a speaker's voice to authenticate them by comparing real-time audio to pre-recorded audio tracks.
By digitizing a person's speech profile, this method creates a sample voiceprint or template for storage. Each uttered word is broken down into hundreds of fundamental properties to identify the speaker's unique speech characteristics.
Call centers record voiceprints in databases similar to fingerprinting and other biometric data.
By doing so, operations gain significant security advantages over authentication methods that rely on something the user knows, such as passwords or security questions. As such, it helps to overcome cumbersome ID&V processes.
Agent Performance Insights
Voice analytics is starting to transform audio from recorded phone conversations into structured information for search and analysis.
By leveraging other relevant data from various enterprise systems - including the CRM - and connecting insights, businesses may soon uncover fascinating insights into the performance of each agent.
A highly versatile search engine may also aid contact center management in conducting searches quickly and efficiently.
Using free-form keywords, utterances, and acoustic measurements via retrieving calls, team leaders can improve agent performance via targeted coaching.
AI Edits Customer Conversations
When adopting contact center voice analytics, preserving and protecting the privacy of valuable customer billing information is critical.
By using AI to redact audio recordings, the system could remove sensitive information and payment details from all contact center interactions.
Consider the applications of such a technology across industries that necessitate the careful management of sensitive data.
