Opportunities & Challenges

Evolving consumer behavior and the proliferation of digitally connected technologies are propelling customer-centric services and products to the fore. As per reports, 84% of companies that focus on improving customer experience report an increase in annual revenue. 

Engaging and successful conversations are the most critical factor in enhancing customer experience. However, successful conversations that engage customers for longer durations require a good understanding of intent and sentiments; this can be challenging without using deep learning technologies and neural networks.

The existing voice assistants still have mundane responses; you need to understand the technology like framing questions in a specific predetermined format, usage of predetermined or programmed keywords, etc. A simple combination of tasks like “Turn on the AC and lock the car” is still challenging for the bots to comprehend and execute. Besides, present-day bots cannot derive context or retain context from previous conversations with the same user.

To build an intelligent Conversational Agent, understanding user intent is critical. There are many parts to this challenge, too many variables to solve. Human comprehension of language is complex, and not everything of it is verbal. As human listeners, we consider many things like the speaker’s facial expression, hand, and body movement, which is also called ‘body language that is unfortunately not under the purview of the NLP computing domain. Language understanding has the following vital parts, and each of them needs to be solved separately to figure out the holy grail:

• Understanding semantics (lexical)
• Understanding syntax
• Understanding context (both short and long term)