Checklist to determine best NLP Chatbot in 2020

NLP Jul 08, 2020
It would be counterintuitive to some of the readers if we say robotization has created more employment. Flip the coin and you will see another dimension, where millions of job opportunities have been flourished in the market, spiking the demand of professionals possessing logical skills.

It is absurd not to leverage technological advancement for productivity and “social” growth. Our motive behind tossing the term “social” here is to support the ideology of removing every being from its professional comfort zone and crave for self-development.

Automation is not a threat; it is a knock on your door to get up & brush your skills.

The world has learned from Musk’s mistake that you need to have a balanced diet when it comes to automation. Also, privileging only physically aligned automation is not the solution.

On one end we can see some business revolutions marching towards productivity with their AI-enabled army of logical components designed for unleashing the real potential of technology.

The world is being questioned with a concern regarding “What is preventing the rest of businesses to implement automation for rocket boosting their production, sales, revenue & client support?”

Kevit’s analysis concludes that businesses which are deprived of AI-Tech often do not have a lead for what to look out while hunting for the best automation. And that made us draft this one-stop checklist for enlisting crucial qualitative factors to look forward while dealing with the bloodline of any business, which is none other than “End-Consumer”.

With staggering 30,000+ Google searches per month on US soil only, the booming industry of Chatbot development has made a great contribution in handling customer service, that too at its best!

Still, yup there is a still a “still”, most medium scale organization have a doubt in their mind “can a piece of code handle their customer as efficiently as their experienced employees?”. The straightforward answer is “NO”, that piece of code will easily outrank their so-called experienced employees with far better efficiency, no fatigue, and handling tons of threads at any given time. That is the unmatched magic of automation.

Along with all these promises, a Chatbot’s neural engines incorporating NLP – Natural language processing, ML-Machine Learning & AI helps in reaching the horizons extensively smooth assistance and much higher conversion rates.

What is all that "Natural Language Processing" fuzz about?

The Chatbot must be a digital version of a business team that requires a great sense of communication skills. With computational linguistics Chatbots have evolved to represent an enterprise to the respective audience and understand what the user has to say, irrelevant of the language, tone, or fashion.

This was possible with NLP, juiced with BID-DATA, complex algorithms & neural engines we have successfully bridged the gap between human to machine communication. Your business will always be backed-up with technology that not only understands your consumer but also provides a sensible response to the consumer’s highly complex or natively languaged query.

Without further ado, lets quickly analyze what an NLP based chatbot must have:

Time to Crosscheck your "Bot's" Quality

NLU - Natural Language Understanding

This form factor is present only in few highly advanced conversation automation platforms where Chatbots can be trained to effectively address a query filed by an individual who has no domain expertise. NLU helps in giving correct assistance to the user’s query which is often misspelled or mispronounced along with consideration of other factors which are discussed below.

Entity Extraction

Every card has its importance while building a palace of cards, one of the most underrated yet necessary cards of Chatbot is its quality of entity extraction from a user query. This enables the algorithm to funnel out and deliver responses that are fulfilling every aspect of the query.

Sentiment Analysis
Chatbot in its developing stage was lacking the most essential part of communication that was hard to recognize without human taking over and it was, sentiment analysis of the user on the other end. Proactively knowing that the user is angry, happy, neutral, calm, or panicked provides an advantage to the business in conversing accordingly for utmost customer satisfaction. Make sure your bot has this feature so that every interaction with the business ends up in a satisfactory manner.

Speech Recognition
In this internet era, our typing has drifted towards speaking, which has enabled more usage of smart speech recognition technology in entertaining user queries. Alexa, Cortana, Siri, or Google are the most well-known example of it. To stand out in your business competition your Chatbot needs to have a verbal form of communication apart from the textual conversation. Soothe your audience with hassle-free speech recognition for observing sustainable business productivity.

Anomaly Detection
This feature has overclocked the usability of Chatbot where it becomes necessary to identify or rectify an occurrence of anomaly observed apart from the expected pattern. This unnatural reference in the Dataset might result in saving monetary value for business and clients too. Mostly used by Chatbots in banking sectors anomaly detection is a quality that every AI-conversational entity must possess.

Knowledge Graph Analysis
The best way to represent real-world problems is with a knowledge graph.

This is a self-explanatory concept in the world of Chatbots. Disruptions in the field of AI technology has to lead us to mimic the human thinking in its digital form, Chatbots can now make a real-time knowledge graph of entire conversation for plotting nodes out of user query and helping to deliver most relevant answers. Processing this kind of abstraction enables us to step up our Chatbot's level for delivering far better conversions.

Predictive Analysis in AI
Every business houses crucial data and it doesn't matter whether it is in an unstructured or structured form. This data if fed to AI can have some surprising results, where it will train itself for predicting the further situation. So, in case if you have a ton of audience data make sure your Chatbot entertain a functionality to inherit it for analysis purpose and predict user behaviour, quality leads, suggestions, and interest-based offerings.

Geo Analysis

AI-Assistant deployed by your organization must be featured with knowing the precise location of the person whom it is dealing with, this will add in improvisation of understanding the contextual references made by the end-user. It also helps in determining the language a bot must pursue the conversation with.

Image Recognition
In this mediatic world if your bot is deprived of image recognition feature than you must consider it for a change, as the end-user is not tech-savvy they will try to narrate their problem via pictorial representation. If your bot on the frontline has capabilities to recognize objects, barcodes, textual data, or even multiple languages within the images, will add value to your business impression.

How did the checklist went for you?

If your bot comprises of all the above-mentioned quality check than Congratulations! You made a great choice and if not, here we are! At Kevit we furnish Chatbots which are business tailored to meet your specific domain requirements. Do visit and browse our AI offerings at https://www.kevit.io/ or contact us at coffee@kevit.io.