Why IBM Watson Contextual Capabilities Make It A Winner?
When Watson emulated the success of Brad Rutter and Ken Jennings on Jeopardy! (the famous American quiz show), it became clear that IBM was on the verge of yet another tech revolution — and this time, it was going to be gigantic.
Fast forward to ten years and, as it stands, almost everything about Watson still garners an “awe-inspiring” reaction. And it’s no longer constrained to a piece of hardware (actually, it never was); in fact the glittery supercomputer now resides in almost everything that qualifies for smart technology.
Talk about sophisticated DNA analysis, wealth management, legal counsel, personality analysis, or purchase customization—Watson’s contextual capabilities make it the go to AI for business applications across different sectors.
In many ways, Watson is set to become the underlying framework scaling AI-driven opportunities from Finance to Manufacturing to even Retail.
IBM Watson’s Semantic Analysis is Spot On
Literally, everyone across the world expects an AI to understand and respond in the natural language. That’s precisely what Watson is able to facilitate with massive success.
Its natural language processing (NLP) abilities allow it to perform advanced text analysis, which results in a profound understanding and subsequent extraction of entities and relationships within the content.
Such entities and relationships are then successfully employed for the identification of semantic context. Simply put, advanced text analytics works absolutely like a human brain — divide the content into parts and derive the meaning of those parts to comprehend the greater meaning.
Consider this; Watson’s NLP skills, equipped with advanced sentiment evaluation, make it possible for the AI to understand idioms like “out of the woods” or perhaps a simile like “as brave as a lion.”
This is a great achievement as far as applications for businesses are concerned.
As of 2021, Watson APIs are helping applications the intricacies of human communication thus, providing an opportunity for businesses to contribute to an unparalleled and unprecedented user experience.
Here’s How IBM Watson Is Changing the Business Landscape
The Profound Analysis of Unstructured Data
Businesses are now inundated with data. Sensors, devices, wearables, customer emails, social media posts, phone calls to the contact center, and walk-in visits to customer service centres are generating millions of data points, all of them with the potential of revealing startling new insights to drive the business forward. It has long been said that customer data has the solution to every customer problem. Nevertheless, the analysis of such massive, unorganized data is no piece of cake because this data is all unstructured. But, with Watson’s unique capabilities of churning through chaotic knowledge bases, it becomes relatively easy to gather insights into what customers are actually talking about.
IBM Watson Knowledge Studio is a go-to tool for realizing industry specific unique data within the unstructured text. To that end, let’s say a smart city entity trying to figure out the frustration over the safety concerns associated with cycling. Based on surveys, you’ve come to realize that such a problem exists. For mitigating it, you’re planning to improve the cycle’s and the road’s quality. But as you consult Watson it reveals that people are frustrated because cyclists often ride on footpaths and don’t slow down even when they see people crossing.
Note the difference? You thought that the frustration was due to unsafe bicycles and roads, whereas, in reality, it is the cyclists who are causing problems to the citizenry.
Imagine how many customer service issues can be solved if Watson’s contextual capabilities are utilised to the utmost extent.
The Support to Virtual Assistants
Ever had a chat with an AI-powered chatbot? Their responses often blur the differences between a human and a robot. And that’s what the customer wants — he/she aspires to save time and resources and get the queries resolved before it gets too complex with the human agents.
Watson Assistant is specifically designed to emulate human interactions. It would be more plausible if we don’t term it as “emulation” since it goes beyond what an AI bot would usually manage.
The new FAQ Extraction feature furthers the capability of virtual assistants since they understand what to search for, when to search, and how to answer using the knowledge acquired through these searches.
So, for a business deploying Watson Assistant, you can expect the chatbot to answer just like you would but more promptly and accurately. What’s even better is that the probability of misunderstandings is relatively low since the Virtual Assistant’s NLU capabilities and the related delivery of answers are absolutely crystal clear. In short, an elevated customer experience is here for all.
The Torch Bearer of Personalized Marketing
When brands have data, they have the key to understand the audience’s persona, i.e., their likes, dislikes, preferences, attitudes, and interests. Through real-time data personalization, IBM Watson presents itself as one of the most viable interventions to revolutionize branding and marketing efforts.
This AI system is ideal for marketing automation where campaigns can be created using real-time data — no guesswork, no biases, no fluff. Marketers can use the actionable insights courtesy of the cognitive capabilities of IBM Watson.
In concrete terms, you’d be able to go through the shifting market and social media trends, identify the solutions to generate more leads and drive higher conversions, reflect upon the adoption probability of an innovative product or service, and quite simply growth-hack your business.
In a Nutshell
IBM Watson satisfies expectations businesses have that AI can solve complex market problems and it does so in the most complex and nuanced application space around. IBM Watson’s contextual capabilities empower it to help businesses cater to massive audiences with diverse personas in myriad ways. Its ability to understand context and derive insights about intent makes it valuable in areas that are otherwise rife with complexity due to the many subtleties of human interaction. The contextual capabilities of IBM Watson make it a winner there!
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