Teaching computers to think like us

Picture this. A package arrives on your doorstep. It’s the mirror you ordered for your daughter’s bedroom. Unfortunately, there’s a big crack in it. What do you do? You have a couple options:

1. Call customer service, listen to an endless array of automated options, get frustrated when you don’t hear the reason for your call, yell “speak with agent” into the phone and then sit on hold waiting for the next available agent. 
2. Interact with a bot on the retailer’s website and repeatedly type your problem into the chat hoping to hit on a keyword the bot will actually understand. Input your order number, SKU number and other seemingly arbitrary pieces of information that the bot requires to move through the steps

Neither option is great, but time and again, we find that customers will choose the phone call with a human over the automated process because it’s easier. With a human, you can say, “The mirror I ordered arrived with a crack. Can you send me a replacement?” That kind of plain language rarely works when interacting with a bot. 

The problem is that we’re being forced to think like computers.  Why do you need to know so many seemingly meaningless numbers? Because that’s how the computer thinks. You only need information like that when you talk to a computer, and it’s a frustrating customer experience.

Generative AI and low-code tech can create more natural customer experiences

The good news is that we can now train computers to understand natural human language. The better news is that we can do that in a low-code environment with the help of generative AI and large language models (LLMs).

With a generative-AI enhanced chatbot, you use the same type of language that you would with a human (“The mirror I ordered arrived with a crack. Can you send me a replacement?”). The LLM is what makes this level of human-like interaction possible. 

Until recently, LLMs hadn’t been easily accessible, but that’s changing. With technologies like Microsoft Copilot Studio and Power Platform, you can develop generative AI-powered chatbots that make the customer experience easier and more natural. And you can do it in a low-code environment, which means you don’t need to know how to write code. Instead, you can use words to create and train your bots. 

Sounds pretty easy, right? It is and it isn’t. 

But technology can’t improve customer experience on its own

While it’s never been easier to create a customer service bot, the stakes have never been higher if you get it wrong. Despite growing investments in customer experience technology by companies, customers aren’t happy with their interactions with many brands. Forrester just came out with their 2024 Customer Experience Index  and they found that average customer experience quality in the U.S. now sits at an all-time low. 

That dissatisfaction translates into real dollars. According to a Qualtrics 2023 Global Consumer Study, 51% of poor experiences result in consumers decreasing or cutting their spending entirely. 

Essentially, what these statistics are telling us is that you can’t afford to get customer experience wrong at any point in the customer journey – even when customers are interacting with a bot.

On the flip side, Forrester also found organizations that do get customer service right experience 41% faster revenue growth, 49% faster profit growth, and 51% better customer retention.

So how do you make sure you get it right? Technology can improve the customer experience by increasing personalization and decreasing friction – but it can’t do those things on its own. Without holistic operational, data, and change management strategies driving technology adoption, you risk creating detrimental experiences for customers.

The key is balancing innovation with strong CX strategy

My advice is to think experience first, technology second. Start with an outside-in approach by evaluating your customer experience from your customer’s perspective. Programs like voice of the customer (VoC) can help you understand your customers’ needs and pain points.  When you understand the ideal state for the experience you can map the journey to the right technology and channels. But that’s just the beginning. 

Microsoft and other innovators will continue to create disruptive technologies that can help you create even stronger connections. The key is to capitalize on those disruptions while maintaining a consistently positive customer experience. A strong CX consulting partner can help you balance innovation with long-term customer experience strategy. At TTEC Digital, this is what we do every day. If you’d like to learn more, please reach out.

If you’ll be attending the Power Platform Community Conference, I’ll be presenting “Next-Gen CX: Leveraging Generative AI and Copilot Studio for Intelligent Conversations” on Thursday, September 19 where I will cover in more depth how these new tools and solutions are innovating and modernizing the customer experience. If you plan to be there in Las Vegas, please check out this session and stop by the TTEC Digital Booth, #216 so we can connect!