Emerging Conversational AI and Customer Channel Trends

Today, the rise of digital transformation has accelerated with New and Exponential technologies and 2019 will be an inflection point for Conversational AI. Gartner estimates that 25% of all customer service support channels will be augmented with interactive virtual assistants by 2020. During 1990s, telephone dominated as a customer support channel followed by the wave of email and web at the start of 21st century. The next disruption in social media gave customer a networked platform to voice their concerns regarding products and services. Meanwhile, the enormous amount of generated data and advances in computational power has given a boost to machine learning and natural language processing techniques to start simulating human-like conversations and contextual dialogues. Moreover, businesses have been piloting use cases on various conversational AI technologies on multiple interaction channels to deliver a seamless customer experience.

Types of Conversational AI Bots technologies and challenges

Conversational AI technologies in industry are mainly classified with the scope of use cases that it can deliver.

  1. Open ended Bots: These bots are neural network driven which can answer open ended queries. These bots sponsor low accuracy when it comes to accomplishing business processes with a high complexity in obtaining the domain conversation data and training the bot.
  2. . Scripted Bots: These are programmed with a certain algorithm and rules but cannot understand any variation given in the query. These are useful only if the business process is highly repetitive with clearly defined steps.
  3. Domain Machine Learning Bots: These bots are evolved with natural language processing capabilities. They can be trained on variation of user queries and are contextual to understand the narrow scope of industry based use cases. These bots can understand the ontology of the sentences, user queries in different variations of synonyms, accents, languages and can help execute industry specific use cases with higher accuracy.Some use cases that are expected to be built on domain based machine learning bots are given in the table (see table 1).

Complexities to truly becoming Omnichannel

Digital transformation started on a rise with building websites and e-commerce portals with a contact centre support. Then, it extended to a mobile app economy when revolution of iOS and android with affordable smartphones swept the market. Social media and search engines started opening the platform to businesses to establish their presence generating a huge volume of traffic from networked platforms. The current wave of channels such as voice assistants, wearables are surely adding to this complexity. This complexity has been depicted in a typical customer journey below (see table 2):



The above channels are getting siloed and are impacting customer satisfaction. Customer must repeat the query in every channel and spend efforts to get in touch with business to fulfil holistic customer expectations for products and services.

Zensar’s Point of View on Omnichannel Approach to Conversational AI Bots

“Create once, channelize everywhere” is the concept that truly drives this match of Omnichannel approach to Conversational Bots.  However, what makes this approach better is that it gives a consistent seamless experience of Why-is-AI-enabled-Omnichannel-Conversation-the-need-of-the-hour-for-a-seamless-Digital-Customer-experiencehaving conversation with AI based virtual assistants with context across channels.

We at Zensar hold a view in integrating these channels with ML and NLP driven bot platform for our clients. This will drive specific business use cases for their end customers to enrich omnichannel experience with added functionalities such as Voice, Conversation journey analytics to deliver a holistic picture of customer journey to management (See table 3).


Having an Omnichannel bot strategy will not only make it easier for companies to converse with their customers but will also help customers to undergo better experiences. Customers of today hold more knowledge than ever before and expect a high degree of personalization to meet their real needs. An omnichannel bot strategy satiates this desire in the most natural way possible.

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Posted by Sanjay Jambhale and Aditya Bolabandi

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