Voice analytics is a technology that captures, transcribes, and analyzes a spoken conversation. In addition to translating speech into text, voice analytics can identify the emotion and intent in a speaker’s words by measuring and analyzing audio patterns. By transforming unstructured information in spoken language into structured data that can be searched and analyzed, voice analytics enables businesses to extract insight and intelligence from vast amounts of conversations at scale.
Voice analytics software combines all the technologies required to capture, transcribe, and analyze spoken conversations. These include:
- Tools for capturing and recording audio interactions
- Voice recognition technology that translates spoken text into structured data
- Technology that identifies a speaker’s emotion by measuring and analyzing speech acoustics
- Machine-learning classification tools that identify words, phrases, intent, and meaning
- Scoring tools that use weighted rules to score conversations on various criteria
- Analytics tools that enable users to search, analyze, and draw insight from conversations at scale
How does voice analytics work?
Voice analytics solutions use recording technology to capture spoken conversations, speech recognition technology to convert sounds into text, and acoustic analysis to measure characteristics such as tempo, agitation, and silence. This information is then transformed into machine-readable data that can be analyzed to identify language patterns and to tag certain language or characteristics that help interpret the meaning and intent of speech.
What is voice analytics used for?
Voice analytics is most often used to extract insight from conversations with customers in a contact center. While contact centers engage in millions of hours of conversations with customers each year, it has traditionally been difficult to extract insight from these interactions at scale. By using voice analytics to capture and analyze 100% of conversations with customers, businesses can gain deeper insight into what customers want, what’s driving their behavior, and how they feel about the brand and its products and services. Voice analytics can also help to improve the performance of contact centers and agents, empowering companies to serve customers more effectively.
In terms of transcribing speech correctly, the best voice analytics technologies today have accuracy rates of 90% or better. Accuracy can be improved with technology that uses speaker-separated audio, where the speech of each person in the conversation is captured and analyzed separately. When it comes to accurately understanding the wants, needs, opinions, and behavior of customers, voice analytics is far more accurate than traditional methods like surveys and focus groups that sample only a very small fraction of customers.
What are the benefits of voice analytics?
By helping companies better understand their customers, superior voice analytics solutions increase customer satisfaction and loyalty. Companies can use voice analytics to improve the effectiveness of contact centers and sales teams, and to increase compliance with regulations that govern what must and must not be communicated during customer calls.
What is speech analytics vs. voice analytics?
Many consider speech analytics and voice analytics to mean the same thing. Some draw a distinction by using speech analytics to mean technology that determines what is said in a conversation and voice analytics to mean technology that determines how something is said.
What is text analytics vs. voice analytics?
While voice analytics analyzes spoken conversations, text analytics captures and analyzes written conversations in email, chat, social media, documents, and other text-related media.
Conversation analytics solutions combine both text and voice analytics, providing businesses with a comprehensive view of interactions with customers, employees, patients, and other audiences.
Omnichannel conversation analytics captures and analyzes conversations that happen across all channels where companies interact with customers – phone, email, chat, surveys, web, social, SMS text, and others. With an omnichannel analytics solution, companies can track and measure the quality of customer experience at every touchpoint on their buying journey and throughout their relationship with the company.
Conversation intelligence refers to the insights and information that is gleaned from conversation analytics technology.
How does CallMiner use voice analytics technology?
CallMiner combines voice analytics and text analytics technology in the CallMiner Eureka conversation intelligence platform. By capturing and analyzing 100% of conversations across all channels, CallMiner delivers greater insight into the mindsets of customers as well as the performance of contact center agents. Powered by AI and machine learning technologies, CallMiner Eureka automatically transcribes, redacts, classifies, analyzes, and scores every interaction to help interpret interactions at the deepest level and identify patterns that shed light on new areas of opportunity. CallMiner’s real-time analytics can provide next-best-action guidance during conversations to help improve the outcomes of customer conversations and increase opportunities for cross-selling and upselling.