Metamorphosis of Chatbots using Natural Language Processing

NLP enabled bots are trained with comprehensive data, thus generating a precise solution to the customer's queries.

With the advent of Chatbots, the process of solving customer's query has transformed. It has become amongst the highly valued entity in the industry. Every sector is seeking to enhance operations and reduce human dependency through Chatbots. The global chatbot market size is forecasted to grow from US$2.6 billion in 2019 to US$ 9.4 billion by 2024, at a CAGR of 29.7% during the forecast period.

Trained using machine learning models, chatbots are fed static information to ease out customer experience. However, a drawback of machine-learned chatbots is the inability to understand the context of user queries, which ensures their failure to answer certain questions. This pertains confined customer use-cases.

To acknowledge this challenge, organizations are promptly opting for the Natural Language Processing enabled chatbots. These chatbots overcome the pre-existing challenge of language variations, thus understanding the context of the problem and providing a customized solution to the customer's inquiry.

Based on the deep learning algorithms, natural language processing comprehends the meaning of the text and generates answers by conceptual analysis, like human beings. The chatbots are trained over multiple and varied interactions with conversations that they can possibly encounter while dealing with customers. The data from surveys, complaints and emails are fed to NLP-enabled chatbots so that they can be trained. Additionally, these chatbots break down the question of the user into individual entities and conceptually analyze the syntax of the language. For example, if someone asks, 'Best Burger Place in New York', the chatbot breaks down the sentence as per the conjugation, plurality, words, capitalization, nouns and verbs. It analyzes each word of the sentence and then formulates a response.

The engine of NLP-enabled bots is governed with machine learning and fundamental meaning that relieves the concerns associated with a machine-learned bot. It entails accuracy with limited false-positive outcomes. Moreover, unlike machine-learned bots, NLP enabled bots asks additional questions to gain information, in instances of its failure to generate an accurate response to the user. This makes them more customer-centric. Additionally, NLP-enabled bots fill the communication gap between the users by resolving the disrupted idiomatic phrases in the sentences.

Faster Bot Training using Natural Language Processing

A machine-learned bot requires a huge amount of time, data and practice to get trained for generating accurate answers. This makes the training time-consuming and labor-intensive. NLP enabled bots on the other hand are trained with comprehensive data, so that precise solution can be generated. The NLP-enabled bots are explicitly trained in an intelligible and complete understanding of verb tenses through conjugation, singular and plural proper nouns, adjectives, adverbs, and structure so that definite response can be generated for the queries of the customer. Moreover, through fundamental meaning installed in these chatbots, the synonyms stored assists in identifying the missing element or context of the user query.

Additionally, NLP enabled bots understand the language semantics and phrases, analyze and makes sense of the unstructured data generated through customer interaction. It also comprehends and interprets slangs and abbreviation, thus contributing to sentiment analysis.

Profitability using NLP enabled chatbot 

Enterprises invest huge money to amulet the properties of chatbots, so that customer experience can be expanded. NLP-enabled bots accumulate all the features that organizations possibly want to establish in chatbots, thus eradicating unnecessary investment. Moreover, since these bots do not necessarily employ human intervention, human skills can be employed on tasks that require the use case.

Market Research through Natural Language Chatbots

The natural language chatbots deal with exponential unstructured data, which can be in the form of comments, queries, inputs, reviews and surveys. By converting them into meaningful insight, natural language chatbots provide a broader perspective in understanding the preferences of the customers.

Conclusion

The organizations need to be more vigilant and comprehensive with the growing demand of customers, as they want solutions readily. By deploying NLP enabled chatbots, organizations can improvise their services and aim for enhanced customer satisfaction.