As Artificial Intelligence (AI) continues to transform industries, a popular use case for AI is in call centers. AI is becoming increasingly prevalent in most areas, but the first place that many businesses start is in customer service. In our blog, we cover how to get prepped for AI call center use cases with the right data, and then cover AI use cases you can unlock. 

Type of Data Needed For For An AI Call Center

When it comes to the best data needed for an AI call center, look for a system that supports accurate real-time data, data compliance, and the ability to activate your data.

High-Quality, Real-Time Data

At the core of any successful AI model is high-quality data. AI models rely on accurate, complete, and consistent data to generate reliable insights and predictions. The better the quality of the data, the better your AI model will perform

Real-time data allows AI systems to make faster, more accurate decisions by processing the most current information available, enhancing responsiveness in dynamic environments. It also enables continuous learning and adaptation, improving the AI’s performance over time as new data is constantly integrated.

Privacy-Compliant Data Collection

In today’s world, data privacy is non-negotiable. AI models must be trained on data that is collected in accordance with global privacy regulations, like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) with CPRA. Failure to comply can lead to hefty fines and damage customer trust (which is not only expensive but hard to regain).

Actionable and Available Data

For AI models to work effectively, the data must be understandable and actionable. This is where contextual intelligence, metadata, and labels come into play. By adding this layer of understanding to your data, you help the AI model “learn” faster and perform better. Contextual information allows AI to make more informed decisions, while metadata and labeling ensure the model recognizes the nuances within the data.

3 Artificial Intelligence (AI) Call Center Examples and Benefits

3 examples of AI call centers are chatbots, call routing, and sentiment analysis. 

AI Chatbots and Voice Assistants

Today, the most popular AI call center use case is a chatbot or voice assistant. AI-driven call centers often utilize chatbots and voice assistants to handle basic customer inquiries such as account information, troubleshooting, or FAQs. These systems are available 24/7 and can engage customers in natural language conversations.

Benefits of AI Chatbots and Voice Assistants

  • On-Demand Availability: Customers can get support anytime, reducing wait times.
  • Cost Efficiency: Automation reduces the need for human agents in repetitive tasks.
  • Consistency: Provides uniform responses and minimizes human error in routine interactions.

AI-Powered Call Routing

AI systems in call centers can route customer calls to the appropriate departments or agents based on their queries, history, or customer profile. Natural language processing (NLP) allows the system to understand the customer’s needs and direct them accordingly.

Benefits of AI-Powered Call Routing

  • Improved Call Resolution: Directing calls to the most suitable agents, reduces handling time and boosts customer satisfaction.
  • Personalization: AI can tailor the experience by analyzing customer history and preferences before connecting them with an agent.
  • Resource Optimization: Ensures that agents with specific expertise handle the right queries, improving operational efficiency.

Sentiment Analysis & Real-Time Agent Support

AI can analyze the tone and sentiment of customer calls in real-time. This enables AI to offer live suggestions or responses to agents, helping them manage sensitive interactions or resolve customer frustration more effectively.

Benefits of Sentiment Analysis & Real-Time Agent Support

  • Enhanced Customer Experience: By providing insights into customer emotions, agents can handle calls more empathetically.
  • Reduced Escalations: AI-driven support helps agents resolve issues faster, reducing the need to escalate calls.
  • Training Support: New agents receive real-time assistance, helping them improve their performance and customer handling skills.

Recommended AI Tools For Call Centers

With Tealium for AI, your call center will have the best AI-ready customer data to drive real-time outcomes and value.

AI models are only as good as the data they’re trained on. With Tealium, you can collect real-time, high-quality, and privacy-compliant data, while adding contextual intelligence to make it actionable. 

Tealium helps you collect consented data, ensuring that your AI models are trained on legally acquired information. By staying compliant, you not only protect your business from fines but also build trust with your customers.

Tealium supports real-time collection of data, delivering you the best data to feed your AI models. Real-time data is essential for AI applications that require immediate responses, such as real-time customer service bots, supported by the most up-to-date customer interactions.

Post Author

Natasha Lockwood
Natasha is Senior Integrated Marketing Manager at Tealium.

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