Is Conversational Analytics Powered by AI the Future of Business?

by July 27, 2020

Conventional Analytics

Why conversational analytics is becoming integral to those businesses who take great interest in the customer journey?

Today, the world is rapidly transforming with the development of technology. This is not only changing the way businesses deliver products and services to customers, but also revolutionizing the way they interact with them. And this ability to converse and communicate is continuously evolving. Organizations always look to deliver newer conversational experiences to their clients and so that they increasingly leverage new technologies such as chatbot solutions powered by artificial intelligence and other voice-enabled solutions.

Enter conversational analytics driven by AI. Conversational analytics is swiftly becoming a business need in order to get to know audiences and provide a better user experience. It typically transcribes speech and translates it into data using a transcription engine. This data is then used to structure conversations that can be organized and assessed for extracting insights.

With conversational analytics, businesses can target audience demographics to know about what they are talking to a bot, then view and analyze every step of the conversation to deliver better service.

As conversational systems have altered how consumers interact with a brand while purchasing things, these systems are also set to transform enterprise IT and the way employees access and interact with data. According to Gartner, a majority of enterprise IT organizations by 2021 will adopt conversation first as the most important new platform paradigm, overriding cloud first, mobile first.

Rapid advancements of AI and natural language processing (NLP) are the major factors driving conversational analytics forward, exclusively for enterprise use.

 

AI-Based Conversational Analytics to Change Business Landscape

Conversational analytics has the potential to assess business performance metrics holistically. As it is particularly beneficial for user segmentation by recognizing their needs and requirements based on conversational data, it assists in providing the exact products or services that customers are looking for. An e-commerce chatbot, for instance, can learn what its users are most interested in, and based on that it pushes notifications in the same environment where they are actively browsing products.

For example, Qlik Insight Bot, an AI-powered conversational analytics, offers a fast and easy way to ask questions and discover insights using natural language. The business intelligence leader had announced its acquisition of CrunchBot and Crunch Data to boost its augmented intelligence and cognitive capabilities in regard to conversational analytics.

Since conversational analytics are already assisting businesses perfect their chatbots and voice applications, AI-powered analytics assistants are taking things a step further by automating data collection.

Moreover, conversational analytics has the ability to perform as a member of a team within an organization. Many companies operate on collaborative messaging platforms like Slack. Significantly, this AI-driven system would transform businesses by offering an efficient way to interact with business data in an accessible system using natural language. In the upcoming years, conversational interfaces like Facebook Messenger, Slack, Alexa, Google Home, etc., will be getting more and more popular as the mobile-first era has completely placed the world at the fingertips.