Maximizing Returns: AI Use Cases for Contact Center Success

The contact center is critical to nailing the customer experience (CX). It is a direct line to an organization's customers, patients, fans and constituents, so there is no room for error; the experience must be flawless. 

We've worked with many clients across industries to mature their contact centers so they can deliver seamless customer service experiences. While every business is different, we've found the same challenges usually appear, including:

• High operating costs: Many contact centers allocate a significant portion of their budget to agent salaries, onboarding, training and management. This investment is often incredibly inefficient due to long employee onboarding times and an average agent tenure of roughly one year. Research shows that more than half of contact center leaders plan to invest heavily in improving contact center operations, technology and the overall CX while also trying to reduce costs.
• Limited insights: Contact centers struggle to analyze customer interactions comprehensively. Only a small percentage (up to five percent) of conversations are reviewed, and when supervisors do review calls, they're prone to human error and biases. 
• Untapped AI: Research shows that contact centers without AI are less efficient. Leveraging generative AI to automate mundane tasks that take up 60 to 70 percent of employees' time and applying AI to various customer service functions could increase productivity at a value between 30 to 45 percent of current costs. 

These challenges can have significant consequences, including low customer satisfaction and retention rates and missed opportunities for revenue growth. By addressing the third challenge and leveraging AI, leaders can evolve their contact center from a cost center to a strategic value enabler.  

This article will help you start your journey to AI in the contact center by identifying essential use cases and providing tips for implementation.  

What is contact center AI? 

Contact center AI refers to the integration of AI technologies, including natural language processing (NLP), machine learning (ML) and predictive analytics, into contact centers, which handle customer interactions via phone, email, chat or other channels. 

For many businesses, the contact center is an ideal starting point for leveraging AI because it can quickly enhance customer service, automate tasks, increase operational efficiency, improve key metrics, drive significant cost savings and unlock actionable insights.

How do I use AI in the contact center? 

Knowing where to begin with contact center AI can be overwhelming. To help simplify the process, I've identified the top use cases that can deliver immediate value and return.

Use case 1: Self-service virtual assistants 

Self-service virtual assistants are AI-driven entities designed to interact with customers and help them find information, resolve issues or fulfill requests without the need for direct human interaction. 

Traditional approaches to self-service in contact centers often fall short of meeting customer expectations and operational efficiency goals. These conventional methods include static FAQs, basic interactive voice response (IVR) systems and limited web-based support portals. 

Self-service virtual assistants can handle a wide range of queries through dynamic, conversational interfaces, making interactions more engaging and effective. AI also uses customer data to provide tailored responses and solutions, significantly enhancing the customer experience.  

Deploying AI-driven self-service solutions in contact centers requires careful planning, development, and continuous optimization. By using advanced AI technologies and integrating them seamlessly with existing systems, businesses can deliver a fresh customer experience, improve operational efficiency and stay competitive in the evolving customer service landscape. 

Use case 2: Predictive analytics for customer behavior 

AI analyzes historical data to predict customer behavior, such as the likelihood of churn, purchase preferences and service needs. 

Traditional analytics approaches in contact centers often fail to meet the demands of modern customer service environments. These approaches typically rely on manual data analysis, basic reporting tools and retrospective insights, which can be inadequate for the complex and dynamic nature of today's contact centers. 

To effectively use predictive analytics in contact centers, AI offers advanced techniques that surpass traditional methods. These techniques provide deeper insights and proactive strategies to enhance customer service and operational efficiency. 

AI-driven predictive analytics offers powerful tools for contact centers to predict customer needs, refine operations and enhance overall performance. By using historical data and advanced ML techniques, contact centers can make data-driven decisions that improve customer satisfaction, reduce operational costs and drive business growth.  

Use case 3: Automated call summarization 

Automated call summarization leverages NLP, ML and other advanced AI technologies to generate accurate, concise and contextually rich summaries of customer interactions. 

Traditional approaches to capturing notes and summaries in contact centers are hindered by manual processes, a lack of standardization and inefficiencies that affect agent productivity and customer service quality. 

By implementing a comprehensive approach that includes data preprocessing, contextual and intent analysis, seamless integration, and continuous improvement, contact centers can significantly enhance the accuracy, efficiency and utility of their call summaries. This leads to improved agent productivity, better customer experience and more actionable insights for continuous service improvement. 

Use case 4: Real-time agent guidance 

Real-time agent guidance in contact centers utilizes advanced technologies like AI and ML to provide agents with immediate assistance and insights during customer interactions. This approach significantly enhances the efficiency, accuracy and quality of customer service. 

Traditional approaches in contact centers often rely on manual processes and static resources to guide agents during customer interactions. Without AI-powered assistance, agents may struggle to find relevant information quickly during interactions, leading to delays and potential frustration for customers. It can also be stressful and demotivating for agents when facing performance targets. 

Real-time agent guidance driven by AI modernizes customer service in contact centers by providing agents with instant support, insights and suggestions during interactions. By leveraging natural language understanding (NLU), dynamic knowledge management, real-time insights, sentiment analysis, compliance checks, CRM integration, continuous learning and agent training, contact centers can improve both the agent and customer experience while streamlining operations and ensuring compliance. 

Implementing real-time guidance systems is a strategic investment that pays off through improved performance and a competitive edge in customer service. 

Use case 5: Automation of routine agent tasks    

Automating repetitive and straightforward tasks frees up agents to handle more complex customer issues. Integrating AI into a CRM system, for example, can automate tasks such as data entry, updating customer records and scheduling follow-up tasks. This reduces the administrative burden on agents and empowers them to focus on providing quality customer service.

Relying on agents to perform manual tasks can hinder operational efficiency, service quality and agent effectiveness. These methods are slow, error-prone, difficult to scale, and offer limited insights into customer needs and behaviors. 

Implementing AI-driven automation of routine agent tasks in the contact center is essential for improving operational efficiency, optimizing resources, enhancing customer experience and empowering agents. By leveraging automation, contact centers can achieve faster response times, consistent service quality, cost savings, scalability and compliance adherence. 

Conclusion 

AI is evolving contact centers into efficient, proactive hubs of service excellence, benefiting both customers and agents. By leveraging AI technologies, these centers can optimize operations, ensure compliance and continuously improve their services, positioning themselves ahead in today's competitive landscape. 

However, embracing AI isn't just about adopting technology; it represents a strategic shift toward reimagining the customer service journey to meet the dynamic needs of today's customers. 

From strategy to execution and adoption, our team can help you take a practical approach to AI into your contact center. We work with contact centers of all sizes — from a few agents to thousands of agents — and across industries, including retail, healthcare, financial services, government and others, to deliver transformative outcomes. Learn more about our services or request a workshop with our experts to develop a plan tailored to your organization's goals and objectives.