The "Voice of Customer" (VoC) refers to the process of capturing and analyzing customer feedback and preferences to understand their needs, expectations, and experiences. It involves gathering insights directly from customers to improve products, services, and overall customer satisfaction. 

In Conversational Analytics, the VoC concept is applied specifically to customer-agent conversations in a conversational setting, such as customer interactions on various brand channels – voice calls, live chats, social media, etc. The goal is to track and analyze these conversations to extract valuable information about customer preferences, concerns, and opinions. 

Conversational analytics technology utilizes natural language processing (NLP) and machine learning techniques to automatically transcribe and analyze the content of customer-agent interactions. By analyzing these conversations, the system can identify and extract keywords, phrases, and themes that are relevant to the customer's perspective. 

For example, let's say a customer contacts a company's customer support team to inquire about a product issue. During the conversation, the customer might mention specific keywords or phrases related to their problem, such as "defective product," "shipping delay," or "refund request." Voice of Customer can identify and track these customer-side keywords and phrases in real-time. 

By gauging the customer side keywords, phrases, and themes, companies can gain valuable insights into customer preferences, pain points, and areas for improvement. They can identify recurring issues or concerns that customers frequently mention, allowing them to take proactive measures to address these problems. It can also help identify positive experiences and areas where the company excels, providing opportunities for further enhancement and customer delight.