Sentiment analysis allows you to understand agent and customer sentiment, sentiment over time, sentiment by channel and sentiment around entities like brands, locations or custom products. You can combine positive, negative and neutral scores with other data to derive knowledge of what correlates to emotions within your conversations.
How does it work? Sentiment analysis listens for specific words and phrases, as well as understands customer sentiments during live conversations. That data is fed real-time into an AI-powered application that’s capable of taking any number of actions including:
- Offering virtual assistant to customer during self-service or an agent
- Texting or emailing supervisor or subject matter expert
- Flagging the interaction for QA and/or follow-up
So rather than only assessing your call center operations after-the-fact, use the power of AI to understand each interaction as it’s happening – and interject with the best course of action – no matter if a customer is talking with an agent or trying to self-serve. Understand what was said, what was meant, and what was felt throughout the conversation and across every channel. With these new tools, you can rethink your conversation strategies, improve agent effectiveness, and transform digital conversations with this deep contextual understanding across the contact center.
Equipped with the right toolset, you can identify how people feel about their interactions with your company and ways you can assist agents real-time.