TELUS Digital's AI Boosts Contact Center Efficiency and Quality
TELUS Digital's groundbreaking 'Agent Performance Loop' interlinks training, real-time assistance, and quality monitoring, leading to a 15% boost in issue resolution rates. This strategic approach redefines the role of AI in enhancing agent performance.
Key Facts
- TELUS Digital's AI boosts issue resolution by 15%, enhancing agent productivity significantly.
- Only 32% of enterprises use AI for quality assurance, revealing a vast market opportunity.
- Two-thirds lack quality monitoring, exposing vulnerabilities in AI deployment effectiveness.
- Continuous data annotation is crucial; poor data leads to agent abandonment of AI tools.
- CX leaders prioritize satisfaction over cost, indicating a strategic shift towards quality service.
Summary
Summary
TELUS Digital deployed a generative AI assistant to over 5,000 customer support agents, resulting in a 15% increase in the number of issues resolved per hour. This initiative aimed to enhance agent performance through a structured approach that integrates training, real-time assistance, and quality monitoring. The deployment exemplifies how effective AI tools can improve operational efficiency in contact centers.
Background
TELUS Digital operates as a customer experience (CX) transformation partner for Fortune 1000 brands. Prior to the AI deployment, the company faced challenges in optimizing agent performance and ensuring consistent service quality across its contact center operations.
Challenge
The primary challenge was to enhance the efficiency and effectiveness of customer support agents, ensuring they could resolve issues more quickly while maintaining high service quality.
Solution
TELUS Digital implemented an agent performance loop that connects training, real-time assist, and quality monitoring. This framework allows agents to receive immediate context and next-best actions during customer interactions, while also enabling supervisors to monitor performance across the entire operation. The AI assistant was designed to integrate seamlessly with existing CRM systems, ensuring agents had access to comprehensive customer information.
Results
The deployment of the AI assistant led to a 15% increase in the number of issues resolved per hour by customer support agents. This improvement demonstrates the effectiveness of the integrated approach to agent performance.
Key Insights
A successful AI deployment in contact centers requires a strong feedback loop that connects training, real-time assistance, and quality monitoring. Continuous data annotation is crucial to ensure that AI recommendations reflect real-world outcomes and adapt to changing customer needs.
Customer Testimonial
"We are not trying to take the human out of the conversation. We are trying to make sure they have everything they need, exactly when they need it, and that a person, not a system, stays accountable for the moments that matter most, the ones that require judgment. That is what moves performance and improves your business outcomes." — Erin Walker, Global VP, CX AI, Business & Delivery at TELUS Digital.
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Key Concepts
Definitions
- Agent Performance Loop
- A framework connecting training, real-time assist, and quality monitoring to enhance agent performance in contact centers.
- generative AI
- A type of artificial intelligence that can generate text or other content based on input data.
- quality monitoring
- The process of evaluating agent interactions to ensure they meet established standards and improve performance.
- real-time assist
- A technology that provides agents with immediate support and recommendations during customer interactions.
- Humanity-in-the-Loop
- An approach that emphasizes the importance of human judgment in AI-assisted processes.
Use Cases
- →Improving issue resolution rates for customer support agents
- →Enhancing training and coaching for new agents
- →Providing real-time customer context during live conversations
- →Aggregating insights from agent interactions to improve AI recommendations
- →Testing AI solutions in a live contact center environment
- →Driving adoption of AI tools on the contact center floor
Frequently Asked Questions
What is the Agent Performance Loop?
The Agent Performance Loop is a framework that connects training, real-time assist, and quality monitoring to enhance agent performance in contact centers. It ensures that insights from one stage improve the others.
How does TELUS Digital ensure the effectiveness of its AI solutions?
TELUS Digital ensures effectiveness by integrating AI solutions with CRM systems and capturing agent interactions to refine recommendations. This continuous feedback loop helps maintain the relevance and accuracy of the AI.
What are the main challenges in deploying contact center AI?
Main challenges include ensuring low latency for real-time recommendations, integrating with existing systems, and capturing data on agent interactions. Many deployments fail to address these issues, leading to stagnation in performance.
Why is outcome-labeled data important for AI guidance?
Outcome-labeled data is crucial because it reflects real interactions and verified business outcomes, ensuring that AI recommendations are relevant and effective. This approach helps avoid the pitfalls of learning from incorrect or unannotated data.
What should buyers consider when choosing a contact center AI partner?
Buyers should look for partners that can demonstrate a connected system of training, real-time assist, and quality monitoring. They should also inquire about how the partner ties agent guidance to verified business outcomes and supports accountability on the contact center floor.