Digital Island Exclusive Pt 2: Technology Integration in NZ Contact Centres with Brad Cleveland

Welcome back to part two of our series on the insights gained from Digital Island’s Business Executive Luncheon, where we brought together senior contact centre experts from across Aotearoa. The highlight, of course, was having Brad Cleveland, a world leader in customer experience (CX) and contact centre management, join us via live stream from California.

In this second instalment, we’re exploring the power of technology integration and innovation in contact centres. Brad’s extensive experience with industry leaders like Apple and American Express, combined with his influential writings in The Wall Street Journal, provided us with deep insights into the future of contact centres in New Zealand and abroad.

This session focused on how integrating new technologies, including Generative AI, can revolutionise contact centre operations. We discussed how integrated systems enhance efficiency, the dual impact of AI on workloads, and the importance of robust knowledge management.

There’s a lot to unpack here, so we’re excited to share these valuable insights. Let’s explore the key points discussed and exactly how they can help lift your contact centre’s performance in New Zealand’s digital age.

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1. The Importance of Integrated Systems in NZ Contact Centres

One of the major themes was the adoption and integration of new technologies within contact centres. Senior leaders in the group emphasised the urgent need to upgrade to more integrated systems that streamline operations. Here’s why integrated systems are a game-changer for contact centres of all sizes in New Zealand:

  • Reducing Platform Overload: Many contact centres in New Zealand still rely on multiple platforms for different tasks, which in most cases, is cumbersome and almost always inefficient. By using integrated systems, contact centres can cut down the need for agents to switch between platforms, making their work smoother and easier, while reducing errors.
  • Enhancing Efficiency: Integrated systems allow information to flow naturally and efficiently, giving agents access to all the data they need from a single interface. This hugely speeds up response times and makes sure agents have everything they need to resolve customer issues quickly.
  • Improving Service Delivery: With and integrated cloud systems, agents can offer a more cohesive and personalised customer experience for every customer. They can easily access customer history, preferences, and previous interactions in one place, helping them provide tailored solutions faster.

2. Impact of AI on Workload on NZ Contact Centres

One of Brad’s key discussion points at our luncheon was the impact of AI on NZ contact centre workloads. This dichotomy — where AI reduces certain types of workload while creating new ones — presents both challenges and opportunities for contact centres.

Reducing Routine Contact Centre Interactions

AI has the remarkable ability to automate a variety of routine tasks, which significantly lightens the load for human agents.

  • Automating Simple Tasks: AI can handle straightforward interactions such as answering common queries, processing simple requests, and providing basic information.
    • Example: Chatbots that can answer FAQs or direct customers to self-service options for simple issues.
  • Streamlining Workflows: AI helps streamline workflows within the contact centre by efficiently managing routine tasks. This improvement in workflow allows for faster response times and more consistent service delivery.
    • Example: AI-driven systems can sort and prioritise customer emails, making sure that urgent issues are addressed promptly.

Creating New Contact Centre Interaction Types:

However, while AI reduces the burden of routine tasks, it also brings in new types of interactions that need more nuanced human input, and potentially, extra training.

Handling Escalated Issues: AI can identify and escalate complex issues to human agents, making sure that customers get the appropriate level of support. This shift means agents are dealing with more challenging (but interesting) problems.

  • Enhancing Service Quality: With AI managing simpler tasks, agents can focus on interactions that require empathy, critical thinking, and problem-solving skills. This focus enhances the overall quality of customer service.
    • Example: Agents can use the extra time to build rapport with customers, offer personalised solutions, and address unique issues that AI cannot handle.

Embracing the Dichotomy

Ultimately, the shift brought about by AI integration is not just a reduction in workload but an actual transformation in the nature of the work itself.

  • Developing New Skills: As AI takes over routine tasks, agents need to further develop skills to handle the complex interactions that AI cannot manage. This skill development, when done correctly, should lead to more fulfilling and engaging roles for agents.
    • Example: Providing training on emotional intelligence and advanced problem-solving techniques to prepare agents for their evolving roles.
  • Balancing AI and Human Workloads: It’s crucial to get the right balance between AI and human workloads. AI should handle tasks it’s best suited for, while agents focus on interactions that benefit from human intuition and creativity.
    • Example: Regular feedback loops where agents share their experiences with AI tools can help fine-tune the balance and improve the overall system.

AI’s integration into contact centres shouldn’t just be seen as reducing workload — it should be about genuinely reshaping the role of human agents. By embracing the dichotomy of AI’s impact, contact centres can enhance service quality and create a more dynamic and rewarding work environment for their agents. When done properly, it truly is a winning situation for all involved.

3. Generative AI and Knowledge Management in NZ Contact Centres

The other major point of Brad’s discussion at our luncheon was the critical role of knowledge management — especially when it comes to having robust systems to make sure AI tools provide accurate and helpful information.

Without proper management, AI can (sometimes) “go off the rails”, as evidenced by instances where chatbots have provided incorrect or even unsettling responses, like this infamous case with a journalist.

Importance of Robust Knowledge Management

Quality AI depends on accurate and comprehensive knowledge bases. Poor knowledge management can lead to AI tools providing incorrect or harmful information, damaging customer trust and satisfaction.

To avoid these pitfalls, it’s essential to develop strong knowledge management tools and processes. This includes:

  • Regular Updates and Maintenance: Keep the knowledge base updated with the latest information and remove outdated content. This makes sure your AI system gives accurate and relevant responses.
    • Example: Scheduling regular reviews and updates of the knowledge base to include new product information, policy changes, and common customer queries.
  • Training and Support: Make sure that your team understands how to manage and update the knowledge base effectively. Offer training sessions on knowledge management best practices and the importance of maintaining accurate information.
    • Example: Giving workshops on how to identify outdated information and the process for updating the knowledge base.
  • Ensuring Accessibility: Make sure the knowledge base is easily accessible to AI systems. This integration ensures all information is up-to-date and consistent.
    • Example: Implementing a centralised knowledge repository that integrates with AI tools.

Establishing Guardrails

As well as robust knowledge management, it’s crucial to establish guardrails that protect both customer data and brand reputation.

  • Privacy and Security: Protecting customer data is absolutely vital. Establish clear guidelines on how customer information should be handled and be certain that AI systems comply with these standards.
    • Example: Implementing strict data privacy protocols and regularly auditing AI systems to ensure compliance.
  • Brand Reputation: Maintain your brand’s voice and standards in all AI interactions. Make sure that the AI responses align with your brand’s values and communication style.
    • Example: Customising chatbot scripts to reflect the brand’s tone and ensuring they provide a consistent customer experience.

Making the Most Out of Generative AI Engagement

Finally, to squeeze as much benefit out of Generative AI as possible, make sure you are leveraging quality content and identifying self-service opportunities.

  • Quality Content is Key: For AI to perform well, it needs to be based on high-quality, accurate content. Make sure your knowledge base is filled with detailed and correct information that AI can use to provide effective responses.
    • Example: Developing comprehensive content that AI systems can use to respond accurately to customer queries.
  • Identifying Self-Service Opportunities: Use AI to analyse short calls and identify opportunities for self-service. This can help reduce the workload on agents and provide customers with quick, efficient solutions.
    • Example: Implementing sentiment analysis tools to identify common contact drivers and create self-service options for frequent queries.

Where to Next With Digital Island

The insights shared at our business luncheon made it very clear that integrating new technologies and innovative strategies is one of the single biggest improvements you can make for your contact centre and the wider business. These advancements, when done properly, can genuinely boost efficiency and service quality, driving better outcomes across the board.

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1. What are the benefits of integrating systems in contact centres?

Integrated systems in contact centres streamline operations by reducing platform overload, enhancing efficiency, and improving service delivery with real-time analytics and AI-driven insights.

2. How does AI impact workload in contact centres?

AI reduces routine tasks like answering common queries and sorting emails, allowing human agents to focus on more complex interactions that require empathy, critical thinking, and problem-solving skills.

3. Why is knowledge management important for AI in contact centres?

Robust knowledge management ensures AI tools provide accurate and helpful information, preventing the spread of incorrect or harmful data and maintaining customer trust and satisfaction.

4. How can contact centres balance AI and human workloads?

Balancing AI and human workloads involves assigning routine tasks to AI while human agents handle complex issues. Regular feedback and training help fine-tune this balance, enhancing service quality and efficiency.

5. What are the key takeaways from Brad Cleveland’s insights on technology integration?

Brad Cleveland emphasises the importance of integrated systems, the dual impact of AI on workloads, and the critical role of robust knowledge management in enhancing contact centre operations and customer experience.