Consumers have become significantly more demanding in recent years. People expect 24/7 availability, self-service options and seller-free experiences, not to mention personalization, convenience and speed. And although chatbots have gotten significantly better over the past several years, customers will still scream, “Speak with an agent!” as soon as they hear the automated voice of a virtual assistant.
With customer service departments struggling from ongoing staffing shortages, leaner budgets and legacy processes in the form of outdated chatbot technologies, it’s time they implemented generative AI to reenergize the stagnating customer experience (CX), boosting loyalty and increasing agent productivity.
Traditional AI and Generative AI: What’s the Difference?
The current customer service environment is rigid and analogous to a scripted choose-your-own-adventure game. Traditional AI-powered chatbots don’t create new answers when engaging with a customer. Instead, it searches for the best possible choice out of various ranked options and presents it to the caller. However, these answers don’t leave room for change, causing the customer journey to be nothing more than multiple static, inflexible decision trees.
Likewise, legacy chatbot environments attempt to take the customer as far along as they can in the journey until they have gathered enough information to hand them off to a live agent. As expected, customers find these interactions to be drawn-out and unhelpful. Chatbots also have the bad habit of wandering off-topic or coming to a “dead end,” ruining CX.
Alternatively, businesses could infuse their customer service environment with generative AI. This technology, when augmented with an authoritative source, synthesizes data to create a curated response, and, in the case of a customer service interaction, it would provide a trustworthy answer to the person’s inquiry based on available information. Essentially, Generative AI enables customer service departments to interface with their customers in more life-like, dynamic and meaningful ways, massively expanding what customers can ask and expect to get in return, significantly improving CX.
How Generative AI Revolutionizes CX
Ensuring an ideal CX is vital. Research reveals that 80% of customers consider their experience with an organization as important as its products or services – specifically, consumers value a business’s ability to provide personalized interactions. By pairing generative AI with a communication automation platform, companies can gather insights into customer preferences, opinions and purchase behaviors, enhancing CX through better recommendations and tailored experiences.
Not only do customers value personalization, but they also want interactions to be fast and convenient. To that end, generative AI can extract insights from big data much faster than a human agent, allowing it to deliver unique marketing promotions and relevant suggestions in real-time. Additionally, generative AI has the unique ability to “learn” as it gets exposed to new information. While its first few responses might be broad or slightly off-topic, it will eventually be more familiar with the individual customer and be able to right-size answers, increasing completion and conversation rates.
Moreover, properly implementing generative AI into the customer service environment allows companies to boost agent productivity. This technology can better automate the repetitive customer requests that enter a call center, allowing human agents to focus on the more complex customer issues, value-added tasks and revenue-generating opportunities. And, since automation is at the core of AI-powered services, businesses can increase productivity with even lower staffing requirements. Similarly, modern consumers appreciate 24/7 support and service options. Generative AI increases the ability for customers to engage with various channels regardless of the time or day of the week.
Using Generative AI with Care
Customer expectations are changing, with emerging trends including the desire for speed, self-service options and personalization. These changes highlight the necessity of generative AI within the customer service environment. Nevertheless, there are some pitfalls businesses need to avoid when implementing generative AI into their contact centers.
For example, generative AI can sometimes create a response to customer questions that might sound correct but are actually incorrect. Another bad habit companies must avoid is the desire to trick customers into thinking they are interfacing with a human when, in actuality, they are speaking with a machine. AI trained on flawed data could also lead to bias and discriminatory outcomes. If deployed unscrupulously, generative AI could alienate customers and devalue CX.
When combined with an authoritative source for accuracy, generative AI provides the correct tone, style and brevity that aligns with industry-specific CX principles. As such, brands need to put the proper guardrails, guidelines and authoritative data sources in place to ensure that generative AI, like any technology, enhances CX rather than degrades it.
About the Author
Matt Edic, Chief eXperience Officer, IntelePeer. Matt serves as the Chief Experience Officer. In this role, he and his team ensure the highest level of support in customer interactions. Previously, Matt served as Senior Vice President, Customer Experience and Vice President, Enterprise Sales and Business Development for IntelePeer. Matt brings to IntelePeer more than 20 years of leadership experience and a strong passion for serving customers, continuous improvement, and teamwork. Prior to IntelePeer, Matt worked for NexTone, JP Morgan Chase & Co., and Qwest Communications. He holds a Bachelor of Science in Computer Science from the United States Naval Academy in Annapolis, Maryland.
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Your insights on the evolving landscape of customer expectations and the capability of generative AI in customer service are each timely and notion-scary. It’s plain that purchasers nowadays demand a seamless and personalized revel in, and your exploration of how generative AI can be a game-changer in assembly those expectations is illuminating.
The distinction you draw among traditional AI-powered chatbots and generative AI is mainly noteworthy. The analogy of the present day customer support surroundings being akin to a scripted choose-your-personal-adventure sport aptly captures the restrictions of the former. Generative AI’s ability to create dynamic and meaningful responses, synthesizing records for curated answers, certainly looks like a promising bounce forward.