Organizing Data with AI for Better Speech Analytics Insight

Much of the value AI delivers within a speech analytics solution comes from its ability to perform categorization with machine learning.

Every company understands that you need to listen to customer feedback for insight into your success and failure points within your contact center. This feedback is most commonly acquired from survey response. Customer feedback from other sources such as conversations between your customers and agents can offer an even richer repository for capturing intent, action, and emotion as unsolicited feedback. Artificial intelligence (AI)-fueled speech analytics can be applied to capture dialog from the voice of the customer (VoC) and the voice of the employee (VoE) to provide real insights in real time.
So, you say you have captured thousands of hours of speech conversations, transcribed, and analyzed them. Now what? How can you viably organize all these words and put them into actual use?