IVR Call Centers News: Increase IVR Containment 

IVR Containment in Call Center Automation 

IVR or Interactive Voice Response systems are the backbone of modern call center AI and call center automation. They facilitate self-service without human intervention. However, despite their potential, IVRs often fall short in achieving First Call Resolution (FCR). It is primarily due to inadequate understanding of customer intent. This IVR shortfall is usually a symptom of limitations within the system’s Natural Language Processing (NLP) or Natural Language Understanding (NLU) capabilities. Enhancing NLU can significantly improve IVR containment, but how exactly can this be achieved? 

Understanding NLU: The Key to IVR Containment 

NLU is what allows AI systems to interpret human language. It’s the NLU engine behind Conversational AI and virtual agents to grasp the nuances of customer interactions. By enhancing NLU, we empower Contact Center AI to not only comprehend but also accurately respond to customer queries, boosting FCR rates and minimizing the need for live agent intervention. 

IVR Containment Explained 

IVR containment measures the ability of an IVR system to handle calls from start to finish, directing customers to appropriate solutions without human aid. Effective IVR systems increase self-service rates and ensure customers are routed correctly, embodying the essence of efficient call center operations and call center automation. 

Strategies to Enhance IVR Containment 

Improving IVR containment hinges on several key metrics related to Call Center Automation: 

1. Assess the current NLU accuracy of your AI platform. 

2. Evaluate NLU accuracy for brief customer inputs. 

3. Explore avenues to further refine NLU for better IVR containment. 

NLU Engine Accuracy: A Comparative Overview 

The performance of various Conversational AI vendors is often measured in NLU accuracy, with Teneo leading at over +95% end-to-end accuracy:  

• Sprinklr 90,6% – accuracy by virtue of recall and F1 macros 
• Ultimate AI 86% – accuracy and the F1 score 
• IBM Watson 81% – precision, recall, and F1 
• Cognigy 80 % – precision, recall, and F1 
• Google Dialogflow 76% – precision, recall, and F1 
• Microsoft CLU 74% – precision, recall, and F1 

Each vendor has their unique precision and recall metrics. This data underscores the importance of selecting an NLU engine that aligns with the operational needs of your call center. 

Why Teneo for IVR Containment? 

Teneo’s NLU engine is enhanced by the Teneo Linguistic Modeling Language or TLML™, a unique proprietary that significantly improves intent detection accuracy. This deterministic approach to NLU not only understands complex customer queries but also excels in scenarios where traditional machine learning might falter, ensuring unparalleled IVR containment and FCR rates. 

The Impact of NLU Accuracy on IVR Containment 

Improving NLU Engine accuracy can lead to substantial cost savings and operational efficiencies. For instance, a +10% increase in NLU Engine accuracy for a call center receiving 1 million calls monthly can translate to savings of up to $500,000. Implementing Teneo’s OpenQuestion has shown to reduce call handling times by 30% and operational costs by 20%, directly enhancing customer satisfaction and loyalty.  

The TLML-technology leverages advanced machine learning algorithms to refine the understanding of human language, enhancing the capability of contact center AI to conduct more effective and natural conversations. 

The Future of IVR Containment and Call Center Automation 

As we navigate the evolving landscape of call center automation, the importance of IVR containment cannot be overstated. By prioritizing NLU improvement, call centers can unlock new levels of efficiency and customer satisfaction. Teneo’s innovative solutions, particularly the NLU Accuracy Booster™ and TLML™, represent a leap forward in realizing this potential, offering cost-effective, high-performance enhancements to existing systems. 

FAQs  

What specific challenges do call centers face when integrating new NLU engines into their existing IVR systems? 

Integrating new NLU technologies into existing IVR systems can present several challenges, including technical compatibility, data privacy concerns, and the need for significant training data to achieve high levels of accuracy. Technical compatibility issues may arise due to the differences in the architectures of the IVR system and the NLU technology. Ensuring that the NLU engine can seamlessly integrate and communicate with the IVR system, as with Teneo OpenQuestion, is recommended. Additionally, call centers must navigate data privacy regulations to use customer interactions as training data for the NLU system, ensuring compliance with laws such as GDPR or CCPA. Finally, achieving the high levels of NLU accuracy mentioned in the blog, such as those provided by Teneo, requires accuracy boosters to accurately understand and respond to a wide range of customer queries, no matter which language your customers speak or dialect they upheld. 

How does Teneo’s technology compare to traditional machine learning approaches in terms of implementation and maintenance costs? 

Teneo’s TLML™ (Teneo Linguistic Modeling Language) technology offers a more efficient and potentially cost-effective approach compared to traditional machine learning methods. Especially in the context of NLU for IVR systems. Traditional machine learning approaches require large datasets for training and continuous retraining to maintain accuracy. This can be resource-intensive and costly. In contrast, TLML™, with its deterministic approach to understanding and processing language, reduces the reliance on extensive datasets and minimize the need for frequent retraining. This approach yields a lower cost of ownership. Furthermore it speeds up the implementation process but also lowers maintenance costs by simplifying the update process when adapting to new customer service queries or changes in language use over time. Contact Teneo.AI for a quote. 

Can Teneo’s NLU solutions be integrated with IVR systems from different vendors, or are there compatibility limitations? 

Teneo’s NLU solutions are open architecture, adaptable and integrable with a wide range of systems. It includes IVR systems from all popular IVR vendors. Teneo emphasizes seamless integration and operational excellence and the technology is built to work within diverse technological ecosystems. This adaptability is crucial for ensuring that call centers can upgrade their existing systems without the need for complete overhauls. Contact us to discuss your call center infrastructure to ensure a smooth integration process. 

How does Teneo leverage AI to enhance IVR systems, improving customer experience and call resolution rates? 

Teneo harnesses the power of Generative AI to transform IVR systems from basic menu-driven interfaces into dynamic, conversational experiences. By integrating Teneo’s Copilot and NLU capabilities, IVR systems can now understand and process complex, natural language queries. This allows customers to speak freely. Just as if they were conversing with a human agent, rather than navigating through rigid, predefined options. The result is a significant improvement in the customer experience. This is marked by more intuitive interactions, quicker resolutions, and a reduction in call transfers to human agents.