Conversational AI, along with natural language processing (NLP), automatic speech recognition (ASR), advanced dialog management, and machine learning (ML), are changing the way humans relate and communicate with machines. Conversational AI and its associated technologies enable humans to have conversations with machines in much the same manner as they do with one another.
A recent report from Markets and Markets revealed that the global conversational AI market size is expected to grow from $4.2 billion in 2019 to $15.7 billion by 2024. The evolution of AI over the last decade has produced applications that are capable of convincing a person that they are having a conversation with another human, aka the Turing Test. It’s not just the “human” level of interactions that makes conversational AI so important, but rather the ability for the AI app to make informed decisions based on the actionable insights it has gathered from data. This article will look at the ways that conversational AI is improving the customer experience.
Conversational AI Is Not Rule-Based or Scripted
Traditional chatbots were based on a set of rules, much like traditional programming techniques. “If this, then that, else this” was essentially how they worked. If the customer asked what time store hours were, the chatbot would respond by looking through its rules, finding the appropriate rule, and responding with the scripted reply. By using keywords it gleaned from the customer’s text, it was able to match it with keywords in its memory, go through its rules and select the proper response (i.e. the customer mentioned “store hours” so the appropriate response will include the hours of operation).
This was fine for simple queries, but since the chatbot was not truly understanding the whole conversation, the communication between the customer and the chatbot was limited in scope. Conversational AI is not limited to using keywords and scripts — it is able to have a complete conversation through either text or voice. Additionally, it has the ability to provide real-time translations, facilitating a conversation in the customer’s own language. According to Michael Ringman, CIO of TELUS International, a global customer experience digital solution provider, conversational AI enables brands to communicate with their customers globally. “Customers want to interact with brands in their native language and embedding chatbots with real-time translation capabilities allows customers to do just that,” said Ringman. “Beyond translation, these bots can also intelligently pick up on the context of conversations in order to ask for clarifications as needed, and then search for the most relevant answers from a substantial knowledge database.”
Through the use of associated technologies, conversational AI is able to determine the nuances of speech that humans inflect to describe how they are feeling, and respond accordingly. “For instance, many of today’s chatbots are equipped with NLP and can detect customer frustration by their choice of words to then automatically and seamlessly route callers to the appropriate human support to get resolved,” said Ringman.
Related Article: How Conversational AI Works and What It Does
Conversational AI Facilitates Hyper-Personalization
Conversational AI and ML have been integrated into many CRM platforms and customer data platforms (CDP). CRM platforms including C2CRM, Salesforce Einstein, and Zoho have integrated AI providing functionality that includes real-time decisioning, predictive analysis, and conversational assistants, which help sales teams more easily understand and engage customers.
CDPs including Amperity, BlueConic, Adobe’s Real-Time CDP, and ActionIQ have also integrated AI into traditional CDP elements, with the goal of unifying customer data and providing real-time functionality and decisoning for marketers. Conversational AI has enabled marketers to gain a deeper understanding of what their customers want, how they are feeling, and what they are likely to do.
Additionally, these AI-enhanced platforms and the real-time decisioning and predictive analysis they facilitate enable them to take the “next best” action that is personalized specifically to each customer based on the current interaction, purchase and browser history, past customer service inquiries, and demographics.
Ross Daniels, chief marketing officer at Calabrio, a customer experience intelligence company, thinks many brands are focused on the time and cost savings that AI and automation can provide, however the potential returns for improving the customer experience are even bigger and more meaningful for both brands and customers. “From providing near real-time feedback on customer and employee insights and stress predictors to voice-of-the-customer innovations, AI-driven analytics can quickly analyze the sentiment of customer interactions equipping contact centers with the visibility they need to help optimize the customer experience,” Daniels explained.
The seamless, hyper-personalized experiences that conversational AI can provide across all channels may make all the difference to customers in a post-vaccine world, and AI-enhanced call centers where AI is being used to provide human agents with intelligent, real-time decisioning based on historical and behavioral data are being used to create the “next best” action in the customer journey.
Eric Jang, CEO of Deepbrain AI, an AI-enhanced blockchain-based computing platform provider, spoke with CMSWire about the use of conversational AI and real-time video synthesis. Unlike most conversational AI applications, Deepbrain AI uses real-time video synthesis, which enables interactive conversations with customers along with an accurate sync of lips and mouth, which creates an enhanced user experience through immediate responses. “Conversational AI and thousands of pre-recorded lines (such customer’s names and provided details) can be utilized in real-time, which makes the interaction feel like a personal conversation,” said Jang.
Related Article: What’s Next for Conversational AI?
Conversational AI Enhances Conversational Marketing
Conversational marketing is based around one-on-one real-time omnichannel interactions, and enables brands to build customer relationships and improve the customer experience through effective communication and personalization.
Conversational AI chatbots are able to enhance conversational marketing by using one of the customer’s most preferred channels — chat. They are able to automate the data gathering process, provide information about products and services, and help to turn leads into customers. Additionally, conversational AI chatbots are able to interact with customers 24/7/365, which helps to build trust and brand loyalty, as well as enhance engagement. That said, conversational marketing is not limited to chatbots, but rather, conversational AI is just one tool in the conversational marketer’s toolbox.
“’Conversational AI Humans’ enhance conversational marketing because they’re more trusted than static chatbots, so customers engage with them,” said Jang. “They can also respond in real-time and adapt the information depending on the conversation. AI humans can also integrate with existing solutions like chatbot, speech synthesis and video synthesis technologies for a full customer interaction experience.”
Related Article: Conversational AI Needs Conversation Design
Conversational AI Enhances the Employee Experience
According to Devin Pickell, growth marketer at Nextiva, by using chatbots to put data and tools in the hands of employees when they can be most effective, conversational AI chatbots are able to vastly improve the ease with which employees can handle customer service calls, which vastly improves the overall customer experience. “Most chatbots are able to answer typical questions customers ask and tap into a customer’s prior purchasing history in order to provide personalized customer service,” Pickell said. “It’s hard to land on a SaaS website today without seeing a chatbot pop up and greet you. Chatbots play an increasingly important role in customer service, support and sales.” Pickell reflected that 95% of customer interactions are expected to take place via an AI chatbot or live chat by 2025. Additionally, a Gartner report indicated that by 2022, 70% of white-collar employees will interact daily with conversational platforms.
Chatbots do not eliminate the requirement for human interactions and must be balanced with the ability to recognize when to refer a customer to a live service representative for additional details or more complicated inquiries. Chatbots are able to provide a personalized response to basic inquiries such as providing customers with a tracking number or letting them know when an order shipped, leaving customer service representatives to tackle more serious issues.
Related Article: Designing Effective Conversational AI
Conversational AI Makes the Best Use of Customer Data
Chris Bergh, CEO of DataKitchen, Inc., a DataOps consultancy and platform provider that manages analytics creation and operations, shared his thoughts on the use of conversational AI and DataOps to tame the data beast. “When companies interact with customers, they need a unified view of all interactions and data related to that customer. This means integrating all of the various operational systems that collect customer data as well as any third party data feeds. The problem is that none of these enterprise systems talk to each other,” explained Bergh.
“Customer data in different databases can be difficult to match and combine on the fly.” Bergh said that by using DataOps, marketers are better able to leverage all the data that is coming in. “DataOps provides the methodology, architecture, and workflow automation that can break down data silos. DataOps helps you take control of your analytic database across the board, making integration of newer data channels like conversational AI easier to leverage,” he said.
AI is capable of taming the beast that massive amounts of data has become. “Add AI to the equation and the amount of data that comes pouring in is like a fire hose. Speech and automated conversational technology are arguably the most critical, efficient, and fastest-growing data acquisition channels for marketers,” said Bergh.
In the post-pandemic world we are slowly emerging into, conversational AI is able to provide the hyper-personalized experiences that customers expect. Since conversational AI is not scripted or rule-based, it is able to facilitate actual conversations with customers, which tremendously enhances conversational marketing.
Conversational AI is also able to provide customer details to service representatives in real-time so they can more effectively and efficiently handle larger, more complicated issues, improving both the customer and employee experience.