Retail CX in 2024: The Era of Effortless Conversational Experiences

One of the big lessons retailers learned in 2023 is that consumers want to do it themselves. Some call it customer empowerment. Some call it the self-service economy. Essentially, it involves consumers making decisions about products and services without talking to a human.

As generative artificial intelligence (AI) emerged as the breakout tech tool of 2023, it appeared retailers had all they needed to satisfy the growing need for self-service. AI-driven chatbots could serve as an always-on, nonhuman guide that could be deployed on any digital channel and, thanks to natural language processing (NLP), could provide consumers with conversational experiences.

However, a problem emerged when consumers decided they didn’t like talking to chatbots. According to a 2023 survey, 90 percent of U.S. consumers reported they prefer talking to a human customer service representative rather than their AI-driven counterparts.

The Need for a Better Chatbot

While retailers must address the frustration consumers feel with the customer experience, putting an end to chatbots isn't the best solution. Rather, it’s time for the chatbot to evolve.

A recent survey on consumer self-service uncovered a powerful insight into what it takes to satisfy today’s customers. The survey found that 91 percent of consumers would use an online knowledge base if it were tailored to meet their needs. In other words, chatbots aren't the problem. Instead, it’s chatbots that don’t have the information customers are looking for that are the problem.

Properly Leverage Large Language Models

Chatbot technology grew exponentially in 2023, which is part of the problem that has led to customer frustration. Large language models (LLMs) increased exponentially to provide AI with a wider breadth of knowledge, which in turn empowers chatbots to answer a broader range of questions. However, as the surveys cited above revealed, the answers were often too vague to be helpful.

Building a better LLM involves building it upon brand-specific data and growing it through customer-specific interactions. Consumers come to websites and other digital channels looking for informed brand assistants. Vague information provided by unbranded LLMs won't help consumers make decisions, regardless of how accessible it is or how quickly it's delivered.

Retailers that want to provide a chatbot with relevant and accurate information that guides consumers closer to a conversion can’t rely on LLMs trained on general information. If your chatbot hasn’t been trained on brand-specific content, what option does it have when asked a brand-specific question? It can either offer a fabricated answer or no answer at all, and neither of those responses supports customer empowerment.

AI-driven chatbots, leveraging the power of NLP, have the potential to transform retail by fueling a new era of effortless and conversational customer experiences. However, there is still work to do. Just like with human agents, chatbots must have access to accurate and relevant knowledge sources that are specific to the brand. Until they're trained on that type of knowledge, chatbots will continue to fall short of providing all but the most basic customer service support.

Jay Wolcott is the CEO and Co-founder of Knowbl, an AI solutions company.