Your company can access more customer data than ever before, especially in the contact center. But how do you know what to do with all that data? Two solutions that can help are voice analysis and voice analysis. Both solutions analyze phone conversations to provide customer and business insights, but in significantly different ways. Understanding how they differ will help you choose the best call analytics solution for your business.
Speech analysis solutions focus on real words from recorded phone conversations. This technology analyzes the content of agent-customer interactions by converting speech to text and constructing the content. Speech analytics users can search all customer interactions for a specific keyword. When users find calls that contain those keywords, QA managers can quickly get an overview of how agents are handling calls related to a specific topic.
Voice Analysis In Action
There are countless ways to use speech analytics. Here is a simple example. A customer calls and asks if the order has been shipped and when it is expected to arrive. A quick search for the words “order” and “shipped” finds all currencies containing that keyword. The call center manager can then examine each call to determine whether the customer has received the information they need.
Businesses often use speech analytics to gain CX insights and identify trends in customer sentiment. Advanced speech analytics solutions include scorecards to help managers formulate coaching initiatives and provide consistent feedback to agents. Now companies can use all of this data to make informed decisions, improve agent performance, and ultimately deliver exceptional customer experiences.
Speech analysis focuses on what was said in a conversation, while speech analysis focuses on how it was said. Speech analysis technology analyzes audio patterns for specific features such as tone, pitch, stress, tempo, and rhythm. Speech analysis, also known as sentiment analysis, reveals sentiment within the transcript of a call. This more accurately reflects the mood of the customer.
Run Speech Analysis
Speech analytics are most often used to improve the customer experience. For example, a customer might use the word “great” to indicate a generally positive emotion. However, most solutions cannot detect clues like satire or anger that could completely change the meaning of a word. Understanding your customers’ emotions is critical to creating a better customer experience strategy. That’s why modern speech analytics solutions include the ability to provide context.
It is easy to confuse speech analysis with speech analysis. The most important thing to remember is that these automated solutions save time and money spent on the QA process. Whether you run a large call center or a regional franchise, implementing an automated quality monitoring solution can benefit you.