“The finest customer service is when the client does not need to call or speak with you. It just works.”
Jeff Bezos, the founder of Amazon
Using machine learning (ML, a type of AI), autonomous customer experience seeks to “independently learn” best practices for customer service. Moreover, develop its capability profile.
At the core of self-service customer support are complex algorithms capable of making intelligent business decisions. They are based on business rules, incoming data, changing situations, and other variables.
AI and automation are becoming increasingly crucial in the customer experience to answer inquiries and solve problems. Many clients increasingly prefer self-service choices rather than speaking with a live representative. They only use human-to-human interactions when self-service solutions fail. And that’s OK. As long as the path to the human agent is simple and fluid, the consumer can continue their trip. Rather than having to restart once they reach an agent.
📌 Steps of Autonomous Customer Experience:
To build better customer care solutions, you should leverage linked intelligence. This is for to determine when and why a client is having a problem. Moreover, you should find the most effective way to solve their problems.
👉 As a first step, interactive, algorithm-driven software programs known as “bots” employ machine learning to communicate with clients via conversation-based human interfaces. This makes customer support more natural, constantly available with no queues, and “zero-touch” for both the client and the service provider.
These bots can communicate with a natural language virtual assistant like Amazon’s Alexa or Facebook Messenger. The goal is to combine the virtual assistant’s natural language capabilities with robust analytics to accurately understand the customer’s intent utilizing sentiment and topic analysis.
👉 The second step toward completely autonomous care is to include this predictive modeling of support processes in any type of care situation. Bots may now provide answers by executing autonomous activities and analyzing past data to find the next appropriate action that will address the problem more precisely or faster.
👉 Finally, predictive modeling of this type may be utilized to construct a fully autonomous customer care capacity. Furthermore, before accepting a call in circumstances when human interaction is still necessary, warn customer service employees about possible concerns, including remedial measures previously done by the bot.
📌 How does this happen at Exairon?
Do you know that coding is not required to start your autonomous customer experience in Exairon? You can create your chatbots in an easy way with us.
In the beginning, creating operators and teams is necessary. Then, you need to assign operators to the teams they belong to. Thus, agents and groups work in an organized way. Moreover, information flow about inbox and chats can be coordinated. This will lead to solving problems faster.
Secondly, virtual assistant Machinas should be built. After the virtual assistant Machinas are ready, the operators and teams will manage or control them.
To build a Machina, you can prepare your chat scenario and create stories from scratch or you can use Exairon’s Dialog Libraries that we create sector-specific templates for you!
Finally, without any coding needed, you can set the Machina to the channels we offer. Furthermore, you can design the widget according to your brand.
Now you are ready to meet your customers’ needs and improve the experience they have via AI chatbots.
