With so much news about the promise of AI and all the ways you can use AI in contact centers, it can be hard to know where to start.
While a recent IBM study found that 74% of executives say AI will fundamentally change how they approach CX, it also found that “many companies lack a strong foundation of key capabilities, such as CX governance and clean customer data.” They may be overestimating their company’s ability to transition quickly to AI, IBM stated.
Without a stable footing to build on, AI technology to enhance customer experience will fall flat. A poor AI experience will be worse and destroy customer loyalty more than if there was no AI. Plus, customers won’t care if an AI is used in customer support as long as their issue gets resolved.
Before diving into an AI initiative that impacts customers, your organization must have a strong customer experience foundation. Here are 5 CX building blocks needed for AI excellence.
1. A deep, accurate knowledgebase
This is table stakes. AI is only as successful as the quality of data that is input into the model. Without accurate, clear, up-to-date information about products, services, technology, and contact center associate training, an AI model will “hallucinate” with wrong or misleading answers to questions.
Many current contact center knowledgebases are antiquated or inaccurate. Static information might live in the system forever alongside new information, or bad information might remain without ever being replaced. Before moving to an AI program, make sure the information going into your Large Language Model (LLM) for AI is dynamic, accurate, and there is a plan to keep it fresh. Humans in the loop will be essential to keeping the knowledgebase at its highest quality and effectiveness.
2. Active digital channels for customer engagement
It’s easier to launch AI tools to replace interactions in digital channels like chatbots, text, social, and others than it is to replace a voice-based interaction. So it’s critical that customers are already comfortable and confident using digital channels for customer service and sales before introducing them to AI versions of the tools.
Yet the reality is that many customer service organizations still rely primarily on voice channels, while their digital channels are secondary or non-existent. For those organizations, jumping from voice service to AI is not realistic. Take steps to solidify digital customer engagement channels before moving to an AI model. Having the right “plumbing” already in place will make AI deployments for customer-facing activities and associate augmentation more efficient and frictionless.
3. Integrated data systems from across the CX ecosystem
Critical to a successful customer experience program is data to create a 360-degree view of each customer. CRM, ERP, CCaaS, telephony, and many other data systems all house information relevant to gaining customer understanding and giving organizations insight to make the right customer decisions. This will only accelerate with AI technology. AI needs data to generate correct information. It can work at enormous scale and speed, so more information leads to a more perfect output.
If the data systems in your organizations are not yet integrated, more time will be needed to connect disparate systems so that AI tools can categorize and apply them appropriately. Take steps now to build that 360-degree view so AI can start immediately leveraging this valuable insight. Migrating to the cloud first is a good first step.
4. Unstructured customer data and recordings
Just like a robust knowledgebase is critical to input data into an AI LLM model, customer interaction recordings are extremely valuable to help a language model learn the right ways to interact with customers and associates.
Recordings of actual calls also give the model guidance about tone of your brand and ways to sound more human in its responses. The more unstructured recordings to learn from, the stronger the AI model. Recording and storing interactions now is something brands can do well before deploying AI.
Not all recordings are equal, however. Humans in the loop are critical here too, to score the best interactions and train the model for success on what a great interaction looks like. More than just QA, it’s a way to score for brand voice, resolution, empathy, and provide ongoing feedback for any AI technology that is used.
5. Voice IVR
Because voice is still so dominant in the contact center, voice IVR is an important tool that can be applied to an AI program. Hearing actual customer voices and how they maneuver to solve an issue helps train the AI on how to deliver a great experience.
Customers will tell you that many conversational IVRs don’t work as well as intended, and there are improvements to make in the IVR journey, voice recognition technology, and getting to issue resolution. Optimizing the voice IVR before applying an AI layer will reduce risk and friction when you’re ready to make the move.
Find your AI footing with rock-solid CX
No matter how deeply into AI your organization will go, it can benefit from enhancements to each of the five CX building blocks listed above. They will result in reduced cost to serve, higher customer satisfaction, and deeper efficiencies, even before any AI is introduced. It’s a winning strategy to set your organization up now for the AI future ahead.
