Artificial intelligence (AI) has entered virtually every industry to assist with tasks. Effective call centers leverage AI daily to improve their operations, from translating customer conversations in real time to minimizing excess tasks for agents with the goal of boosting productivity.  

Whitepaper

How to Operationalize AI Workflows in the Contact Center

Gain insights into AI-driven conversation intelligence workflows and their impact on efficiency and effectiveness

In this post, we explore 10 AI use cases for call center performance and effectiveness, including:  

• Real-time agent feedback and coaching 
• Redacting sensitive information 
• Translation 
• Multichannel customer journey mapping 
• Sentiment and emotion analysis 
• Transcription 
• Customer conversation organization 
• Learning customer behavior trends 
• Improving workflows 
• Offering self-serve tools to customers 
• CallMiner’s AI-driven technology helps contact centers make the most of customer conversations 
• Frequently asked questions 

AI Use Case #1: Real-time agent feedback and coaching 

AI helps call centers identify areas of opportunity for agents to upsell, provide personalized offers, or assist customers better by listening in on conversations using conversation analytics technology. Conversation analytics captures specific words and phrases that trigger real-time coaching and feedback for agents, including positive reinforcement, agent empathy scoring, and compliance scripts. 

AI Use Case #2: Redacting sensitive information 

Customers shouldn’t need to worry about their sensitive information provided over the phone or email getting into the wrong hands. AI can listen for and redact sensitive information when it’s provided across multiple customer contact channels, allowing agents to get the information they need without having access to sensitive data. 

AI Use Case #3: Translation 

AI-driven call center platforms with language integrations can help agents understand customers from all over the world. AI tools listen to or read customer conversations as they happen, translating them in real time for agents to serve customers as efficiently as possible. 

AI Use Case #4: Multichannel customer journey mapping 

Customer journey mapping helps businesses understand how customers find and interact with them and their services or products. Using AI-powered tools, organizations can analyze the customer journey along every touchpoint, from email to website to social media and beyond, and use that data to improve customer experiences.  

AI Use Case #5: Sentiment and emotion analysis 

Understanding how customers feel about products, services and brand is hard. But these indicators can help you gauge satisfaction, monitor brand reputation and improve #CX.

Learn more about the importance of sentiment analysis and tips for choosing the right solution.

— CallMiner, Inc. (@CallMiner) March 20, 2024

Sentiment analysis and emotion analysis use AI-driven algorithms to determine customer opinions and feelings during their interactions with a call center. Call centers can use this information to understand how a conversation is going in real time, learn how well products or services are serving customers, and improve brand experience.  

AI Use Case #6: Transcription 

AI tools can transcribe phone conversations between agents and customers to text, providing a full transcription to share with other agents when escalating calls. Then, AI processes can analyze the transcription to uncover insights about the conversation, such as customer sentiment, emotion, and customer experience.  

AI Use Case #7: Customer conversation organization 

AI automates the process of organizing customer conversations in call centers. For example, AI tools can detect specific words and key phrases to categorize conversations by type, such as refunds, product complaints, fraud, or praise. Or, AI-driven technology can organize conversations by sentiment, contact method, length, or whatever metrics make the most sense for your call center. 

AI Use Case #8: Learning customer behavior trends 

By analyzing customer data, like where customers call from, what times they’re likeliest to call, or what words and phrases make them feel most appreciated, AI can help call centers identify patterns in customer behaviors. As a result, call centers can staff more efficiently, offer support where it’s needed most, and give customers more of what they want and expect from the support team. 

AI Use Case #9: Improving workflows 

AI can connect multiple tools together, keeping the entire call center’s workflows streamlined and productive. From speech recognition software to CRM integrations, connecting all tools to one another through one AI-powered system allows each member of the team to access relevant data and insights and provide a more cohesive customer experience.  

Discover CallMiner’s integration partners.  

AI Use Case #10: Offering self-serve tools to customers 

Thanks to automation processes, AI allows customers to serve themselves when it makes sense, like when they need a quick answer from a chatbot or want to request their account information over the phone. For example, interactive voice response (IVR) systems have become a critical part of the call center. IVR systems move customers through an automated phone system that listens for customer responses and provides helpful information based on those responses.  

CallMiner’s AI-Driven technology helps contact centers make the most of customer conversations 

CallMiner’s AI-driven technology is a leader for increasing sales, improving customer experience, and boosting agent efficiency. CallMiner uses AI-powered coaching, call center performance analysis, and numerous other tools to create consistent customer experiences and happy customers and agents.  

Learn more about enhancing contact center efficiency with CallMiner.  

Frequently asked questions 

How can AI help my contact center? 

AI digs into customer conversation data to provide contact centers with insights that improve conversations and customer experiences. AI-powered tools can redact sensitive information, provide real-time agent coaching, detect customer sentiment, and understand customer behaviors, resulting in a cohesive, effective support experience.  

What are the key things contact center AI can do? 

Contact center AI tools identify trends in customer behaviors and help agents and managers find areas of opportunity to create and enhance customer experiences. AI can also offer self-service tools to customers, translate and transcribe conversations, hide sensitive information, improve workflow, and map customer journeys across multiple channels. 

Will call centers be replaced by AI? 

AI is meant to assist call centers rather than replace them. Many customers prefer a human touch when interacting with businesses, which AI can’t replace. Instead, call centers can welcome AI-driven tools into their workflows to help them understand their customers' needs and wants, leading to better customer service practices.