Customer service is only getting more time consuming as customers’ expectations and behaviors change. Organizations must live up to those expectations across all platforms and time zones and deliver consistently excellent experiences even as customers’ expectations for ”excellent ” rise higher and higher.
Traditional conversational bots do not live up to what modern organizations need from them, said Aurélien Caye, principal technologist at Sprinklr. Caye helped launch Sprinklr’s first conversational AI product four years ago, and since then he has been involved with all iterations of the product. His experience gives him a unique perspective on the current state of customer service technology, how it’s improved over time and where it’s headed.
The State of Today’s Conversational Bot
Organizations today can use AI to understand the customer journey and guide customers in the right direction in brand interactions. However, the journey itself is generally mapped out by a person who creates detailed decision trees for a conversational bot to follow.
One challenge with today’s bots is that it’s difficult for organizations to find a solution that provides a more human customer experience while also being scalable and easy to manage, Caye said. Accomplishing both at once is not easy.
Bots will have to improve if organizations want them to address today’s trends and challenges, Caye said. For example, organizations must react to messages in a timely manner, manage conversations and optimize customer experiences across more channels than before — from traditional channels such as email to modern channels such as TikTok.
In the past few years, ChatGPT has also impacted how brands must deliver customer service and what customers expect brand interaction to look like, Caye said. He added that because of the impact of ChatGPT, organizations should seek to improve their own customer interactions. “It should be more human, it should provide more context and it should be less rigid.”
Today’s Best Technology Solutions
With the acceleration of generative AI over the past few years, most organizations want to learn how to drive efficiency through conversational AI. The technology offers a huge opportunity for organizations.
“What’s you’re seeing — and this has been a trend already for years, and COVID accelerated it — [is that] every organization is looking more aggressively into how they can drive efficiencies leveraging AI,” Caye said. “Demand is constantly increasing across industries and across different markets.
Sprinklr’s latest customer service offering, Sprinklr Digital Twin, gives organizations a more seamless, simple way to leverage AI. Organizations can have multiple Digital Twins and can choose whether each will represent the brand as a whole, or a specific team or employee. They train each one as they’d train a human agent, by giving it access to all the data its needs and the rules it must follow to interact with customers according to brand guidelines. Organizations can also give Digital Twins unique personalities. For example, they can decide whether it should speak more professionally or casually or if it should be industry-specific. Since Digital Twins speak for different teams and individuals, these personality differences make them feel more human.
Sprinklr uses generative AI to simulate conversations with Digital Twins as part of the testing process. This helps ensure that the time-consuming task of testing individual conversational bots is completed in the most efficient way possible.
Conversational AI is just one of many use cases of Sprinklr’s latest customer service solution. The new offering also helps drive automation and aid users in creating assets or copy. “Because the Digital Twin is built as part of [the] Sprinklr unified customer experience management platform, it can also be used to drive much more automation within the front office,” Caye said.
What Makes Digital Twins Stand Out
Customers don’t like robotic conversational bots, and Sprinklr uses a powerful strategy to ensure that Digital Twins converse more naturally. Rather than teaching the bot how to speak through decision trees, Sprinklr trains them through prompts. This teaches them how to be more responsive to the way people actually speak and how to respond accurately to queries asked in different ways.
“It’s much more nimble, and it feels much more human in terms of how it interacts with the customer because it has this flexibility versus being hard-coded within the tree,” Caye said.
Sprinklr also carefully considered security features because compliance is one of the most important considerations for organizations as they invest in tools imbued with generative AI. For example, some Digital Twins know information that is more sensitive. Since they can share information with each other when necessary, a Digital Twin with private information will not share sensitive information unless it’s explicitly allowed to. Another benefit is that Digital Twins are designed with prompt-based and procedural guardrails to avoid bias, hallucinations and out of policy processes.
The layers of Digital Twins also make the solution especially useful for organizations. While the traditional bot focuses on the brand layer, Sprinklr’s newest offering gives team and individual options as well, giving organizations the choice to use a unique Digital Twin that has been trained is such a way that will be most effective for a specific customer query or purpose.
The Digital Twin Advantage
A conversational bot doesn’t need to be one-size-fits all, especially when various teams and individuals have different purposes for using tools like this in customer service. The best solution for organizations is something like Sprinklr Digital Twin, which gives brands more flexibility to respond to customer service queries with the right conversational bot — one that has been trained with carefully chosen data and guidelines so that it can excel at specific interactions.
Sprinklr also recognizes that for a more human interaction, sometimes people have to step in, as well. “There is always the possibility to have a human in the loop and to provide feedback,” Caye said.
