In this era of hyper-automation, customer experience is becoming the biggest differentiator for organizations. Product companies used to design products to deliver a better experience and more value for money as compared to their competitors. That used to be, and largely, still is – the differentiating factor. However, in the age of the internet and omnipresent connectivity, a large proportion of focus has shifted to how customer experiences the brand prior, during, and after the acquisition stage of the journey.
In a market where product differentiation based merely on available features is becoming very narrow and pricing is becoming commoditized, brands both product and service-oriented have realized that ultimately, what experience they deliver to their customers and prospects may be the ultimate key to high sales and market share. The role of digitalized Omni-channel, with speed, efficiency, and accuracy becoming the core traits that must be offered to customers. Companies are seeking well-balanced offline to online strategies as the consumer journey shifts from offline to online. Companies that use these methods are winning the digitization race, gaining more customers, and increasing sales.
There is a wide range of conversational AI applications
currently being experimented with or actually being deployed at scale across all
industries. From customer service to marketing to security, these algorithm-powered intelligent programs are helping organizations connect with customers
and employees in a wide variety of formats and ways. In fact, conversational AI
has become a centerpiece for many organizations’ digital transformation in the
wake of the global pandemic.
Conversational AI, as one of the most promising methods, is a technology that enables humans and computers to communicate clearly and
effectively through speech or text. Conversational AI, while being complex in
the background (evidenced by the time it has taken to reach this stage of maturity),
works by recognizing a user’s speech or text patterns, predicting their intent, and responding with an adaptive, automated script. While, there are many
platforms, the best conversational AI platforms today can create truly natural,
human-like interactions. Conversational AI’s rise in popularity is based on its
“friendliness” factor – being flexible to work with (and enhance) other
technologies, and also by enabling a frictionless, human-like, end-user
experience.
Chatbots were brought into CX as part of this digital
approach, and they are one of the most advanced and promising forms of
human-machine connection. Conversational AI has been transformed by a
combination of diverse AI types such as natural language processing, machine
learning, and semantic understanding.
Unstructured data in the form of guided dialogues guide
conversational AI, although it may also be passed off to a human worker if
necessary. Conversational AI enables the delivery of a tailored customer
dialogue at scale across many channels, resulting in a seamless customer
journey.
Simultaneously, RPA appears to be emerging as a potential
option that employs robots to automate repetitive operations and manual
processes with the goal of speeding up CX processes while lowering operational
costs. RPA (Robotic Process Automation) Robots are guided by structured data
inputs in a bottom-up, process-centric way. Even if customer contacts are
routine, they are never the same in each transition. It also lacks the ability
to respond swiftly to changes or handle exceptions.
Combining Conversional AI with RPA, which mimics user
actions and conducts task-based activities, might be termed a self-serving
engagement model. In such a case, RPA may effortlessly interact with chatbots
and assist the chatbot in completing a CX task, accessing, or storing
information. The requirement of prompting RPA “bots” to further commence and
complete the process can be satisfied by the bidirectional data flow between
chatbots and RPA.
As a result, RPA and conversational AI can be regarded ideal
partners, as each picks up where the other leaves off in the process. When both
are used together, CX can provide speedy, tailored encounters and customer
assistance at scale. This integration's super-intelligent design will not only
help consumers get their questions answered faster, but it will also provide
the company an edge over its competitors by providing great digital branding.
While dealing with sophisticated requests and queries in
real-time, an RPA-enabled chatbot can interface with not one, but numerous
back-end enterprise systems. Chatbots combined with RPA and AI will provide
your customer service a competitive edge by streamlining processes, increasing
productivity, and lowering operational expenses.
The convergence of conversational AI and intelligent
automation is part of an extended omnichannel experience meant to facilitate
faster, more personalized, and responsive customer service
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