Artificial Intelligence (AI) allows enterprises to automate the customer experience (CX) via an intuitive conversational interface. That means companies are able to provide customers with 24/7 access to personalized services and information. But unlike a static web interface, an AI-powered virtual agent allows customers to engage with enterprise systems just as they would directly with humans. Not only does this functionality enhance CX and potentially contribute to an improved Net Promoter Score (NPS), it also benefits companies via a powerful new avenue of data collection and processing.
At this year’s Digital Workforce Summit (DWS) in New York City on May 8th, attendees will hear from top executives from Bank of America, Telefonica, BNP Paribas and more about how they’ve used AI to optimize their organizations. There will be industry-specific breakout sessions including ones which explore the multitude of ways that businesses can use AI to create new value.
In addition, DWS presenters will discuss the ways that conversational AI opens new opportunities for companies by automating and optimizing every step of the customer journey. In this post, we will explore some of the ways that conversational AI can create stronger customer relationships by keeping satisfactory consumer experiences center-stage.
It’s Not Just Good Conversation, It’s Good Data
At last year’s DWS, an entire panel was dedicated to exploring the business truism that “data is the new oil.” Fast forward and this concept has only proven itself to be more relevant as the use of conversational AI continues to accelerate (a trend that will be even more prevalent as we enter the era of 5G and IoT). While AI systems rely on data for training and refinement, they also provide a new source of data and information that allows companies to become more familiar with customers on a potentially granular level.
Conversation is inherently rich in useful data points. When automated through AI, conversation can be used to gather information (e.g., “What is your preferred email address?” or “What is your reason for calling today?”) and to transform natural language into useful data. More advanced virtual agent (VA) solutions such as Amelia include features like sentiment analysis, which can translate less tangible elements including human emotion into actionable data. For example, a solution could automatically identify and notify a company about an increase in customer social posts expressing frustrations with a new product or service.
Creating Stronger Customer Loyalty
This new data can be automatically processed and utilized by companies to grow their businesses through automated marketing and messaging campaigns. For example, if a user engages with their bank’s VA for a quickly resolved issue like ordering new checks, the system could also recognize that the user is a longtime customer, and therefore during the course of the interaction up- or cross-sell new products at a discounted cost or rate. This data gathered by a VA can also be used to maximize messaging and marketing campaigns after the fact.
Case in point: One of Japan’s largest telcos tapped the Amelia solution as the basis for a chat-based virtual agent enabled on the company’s account on LINE, Japan’s most popular social messaging platform. Through this automation, the company was able to expand sales of phones and SIM cards beyond regular business hours, where more than 50% of inquiries take place, and it dramatically increased traffic to the company’s product site. The solution’s automated log analysis engine also greatly improved efficiencies in the company’s social marketing through automatic customer segmentation.
Conversational AI allows users to have natural language engagements with digital systems. As a result, customers have better overall experiences and companies can build consumer loyalty for the long term. We look forward to joining you at this year’s DWS to explore this topic in even greater detail.