The generative AI contact center has transformed the world of customer experience.
While generative AI can have a powerful impact on various business processes, it’s particularly compelling in the contact center. McKinsey suggests implementing generative AI contact center strategies into your business, which can lead to a 45% productivity cost improvement and other benefits.
However, as interest in generative AI solutions continues to grow, the market competition is also evolving. Virtually every contact center innovator and tech giant is now exploring new ways to bring LLM-powered solutions to business leaders. This means finding the right solution for your company can be complex.
Fortunately, we’re here to help. Here’s our behind-the-scenes guide to comparing generative AI contact center solutions in 2024.
Step 1: Define Your Generative AI Contact Center Goals
The first step to choosing the right generative AI contact center solutions is deciding what you want to achieve. Today’s ultra-flexible generative AI technologies can address a variety of use cases. Agent assistant tools empowered with generative AI can improve team productivity and efficiency. They can automate repetitive tasks and coach staff in real-time.
Chatbots and virtual assistants for consumers, built with generative AI, can deliver personalized self-service experiences. Companies can use bot builders to design incredible virtual agents capable of offering 24/7 support to customers on a range of channels.
There are even comprehensive generative AI toolkits available in CCaaS platforms, which can assist with everything from call summarization to KPI analysis. Setting clear goals for your new solution will help you decide what generative AI system you need.
Step 2: Examine Your Current Ecosystem
Like most innovative contact center tools, generative AI solutions work best when aligned with your existing technology stack. At a basic level, if you’re using generative AI for customer service, you’ll need to ensure your system can integrate with your contact center.
This could mean leveraging the “bring your own AI” options some CCaaS vendors offer or working with vendors that provide their proprietary solutions. For instance, Microsoft offers Copilot for Sales and Copilot for Service, which integrates with Teams and Dynamics.
Alongside your contact center, it’s worth looking closely at the other tools you want to align with your generative AI strategy. Do you want to connect AI coaching bots with tools like Microsoft Viva? Are you using CRM and customer data platforms that can help you train your generative bots with proprietary insights? The more flexible your chosen solution is, the better.
Step 3: Consider Customization Needs
Like all forms of AI, generative AI contact center tools rely on data to deliver exceptional results. Some pre-built solutions are already trained on vast volumes of service-focused data, like DialpadGPT.
However, they’ll learn, adapt, and improve over time based on the data they can access about your business and customers. With this in mind, before implementing a new generative AI solution, it’s worth ensuring you have the correct data ecosystem.
