Jul

Why Keywords Do Not Cut It on Social Search

Most of the online search is keywords-based. Same in social domain, a vast number of analytical tools, networking platforms and mobile apps use keyword-based technologies as well.

There is a difference, of course, between traditional internet search and social search. The former finds websites. The latter finds conversations, messages, posts. Keyword-based internet search is doing a decent job for us for over 20 years. Keyword-based social search is not doing a decent job at all.

Consider a basic example: finding on Twitter who is interested in buying jeans. We can start by typing ‘jeans’ but that brings up too much noise. Maybe ‘need jeans’? Less noise but then we  people who use expressions like ‘looking for jeans’ or ‘want jeans’ or shopping for jeans’. Not to mention those who use ‘denim’, or brand names. So we have to run multiple searches or create a complex search string using logical AND and OR and hope it works. Neither option is simple, or convenient, and certainly not efficient.

The above example highlights the major flaw with keyword search - it does not capture the meaning of social conversations, and therefore cannot be a reliable source of information about conversations.

It does not provide too much of correct information. And it does provide lots of incorrect information. But the biggest problem is that it has extremely limited potential for improvement.  

So as long as we stick with keyword-based social search the results are destined to be limited.

Why, then, we stick with keyword-based search in social search? Simply because there is no good alternative. Until recently, that is.  

The advanced semantic technologies capable of capturing the meaning, or intent, of conversations are now offering an exciting alternative.

I will discuss these technologies on my next blog.

Interested in reading more? Check out our other blogs:

AI unmasked: Why long-term success of your business depends on conversational AI



For a business to grow successfully, it needs to scale its sales, customer service, marketing.

The only sustainable way to do this is to introduce an automated sales and customer experience service.

Conversational AI is the single available method to automate customer experience without reducing the quality of service. It comes in a variety of forms such as a chatbot, voice bot, virtual assistant, cognitive agent. They all share the scaling ability and the ability to deliver human-level quality of conversations. 

 
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nmodes Introduces Arabic language support for Advanced AI Solutions

nmodes recently introduced new feature for our family of Advanced AI solutions – Arabic language support. 

nmodes provides conversational AI solutions to address the needs of customers around the world. We deliver chatbots, integrated AI solutions, omni-channel AI systems and more. Our solutions are professional, efficient, scalable. 

We believe this is the beginning in the marketplace for advanced conversational AI solutions that help improve and scale current sales and customer service business process. With Arabic support, we’re creating new opportunities for an important, fast-growing market segment.

Additional native language support is an integral part of our strategy of bringing a full spectrum solution to the AI market.  We continue to define new solutions, add new languages to enable businesses and organizations around the world more easily benefit from the advantages of  using solutions powered by advanced AI technology.

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