Outsourcing Web Hosting Support: 6 Reasons Why It Makes Sense
Posted on Sep 13, 2020
byDev Kumbhare (Sr. Manager Business Development)

4 Key reasons why your Chatbot should be NLP (Natural Language Processing) enabled

While businesses are starting to realise the importance of Chatbots, these are becoming the ‘ManFriday’ of any business aiming to enhance customer experience. Technology organizations are constantly making improvements to make the Chatbots ‘smart and intelligent’ that could mimic different functions of the human brain. Natural Language Processing or NLP as it is commonly known, is a highly valuable addition to the arsenal and adds a different flavor to the Chatbot. NLP helps in not only improving customer service but also effectively helps in conversation analysis.

Adding NLP capabilities to your Chatbot is easy and cost-efficient. There are many chatbot technologies such as Google Dialogflow, Rasa, Google TensorFlow or Dr. Watson which enable us to develop AI/NLP based Chatbots.

NLP works through Machine Learning (ML). Machine learning systems store words and the ways they come together just like any other form of data. Phrases, sentences, and sometimes entire books are fed into ML engines where they’re processed based on grammatical rules, people’s real-life linguistic habits, or both. The computer then uses this data to find patterns and extrapolate what comes next.

Here are 4 key reasons why your chatbot needs upgrading and how NLP could help:

1.   Overcome Natural Communication Barriers: Leveraging NLP will enable natural conversations thereby helping to understand language and speech structures, track morphemes across languages, and even interpret language idioms and slang to derive meaning. Advanced Natural Language Processing (NLP) capabilities can identify spelling and grammatical errors and allow the chatbot to interpret your intended message despite the mistakes.

2.   Improvised Customer Experience: The Chatbot can be trained to address multiple customer queries as well as analyze and prioritize user questions based on intent and context. Thus the response time could be reduced making for efficient communication with the customer and improve the overall experience.

3.   Focus on Mission Critical Tasks: NLP based chatbots could reduce the human efforts in operations like customer service or invoice processing dramatically so that these operations require fewer resources with increased employee efficiency.

4.   Research and Analysis: The information received from the Chatbot NLP helps in structuring the unstructured content and draw meaning from it. One can easily understand the meaning or idea behind the customer reviews, inputs, comments or queries. One can also get a glimpse at how the user is feeling about your services or your brand which could help in critical decision making and improvements in processes within the organization.

Conclusion:

As AI/ NLP based chatbots are still an emerging technology, mature enough to be useful, yet novel enough to offer an edge to whoever utilizes it, you can look into ways to implement an AI powered chatbot system in your organization. Aress can help you identify the business case of such an investment, while also provide you with the technical expertise, to NLP undertake the implementation of such a system.

Category: Analytics, Artificial Intelligence, Big Data and BI

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