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What Is Conversational AI

                                                         

Conversational Artificial Intelligence solutions can communicate with people in their natural languages. The interactions happen via speech or text – our most common forms of interaction.

The most popular example of a conversational AI solution is chatbot.

The chatbot popularity began in 2016 with Facebook’s announcement  of a developer-friendly platform to build chatbots on Facebook messenger. Soon, chatbots became the buzz of the technological community and spread across various industries. As a next step, toolkits that helped build a bot in five minutes grew popular, companies raced to the market with new bot announcements and the world woke up to a new chatbot-based reality.

A well developed conversational AI chatbot is able to interact on a near-human level. If we think about it, most companies’ customer service and sales centers deal with a core of 6-12 repeating issues. conversational AI software allows companies to develop an intelligent response channel that can cover the most common customer interactions.

Another advantage in using Conversational AI is in the marketing and branding domain. Chatbots allow the companies to stay on their message without veering off course . With AI, the scripts are all written and approved in house. Even when the AI system learns, when the appropriate training techniques are implemented, the system will adhere to the required profrssional verbiage.

 

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Social Marketing is Simple

                                                           

In its very essence social marketing is based on one simple foundation - give first, take later.

This concept of giving to the community is hardly possible to overestimate. It defines the way social networks operate and goes even deeper, to the basic principles of social interactions among humans.

In fact it is a much healthier foundation for business than traditional one, based on advertising.

Yet it runs contrary to what many entrepreneurs and business people perceive as a proper marketing approach.

Traditional marketing, such as billboards, radio ads, posters, banners, emails blasts, etc is based on two principles, a) the statistical law of big numbers, aiming to reach out to as large audience as possible while knowing that only a small percent would become interested, b) message of self-promotion and self-advertisment.  

Social marketing negates both of these principles.

Social marketing is personal, it operates individually, and in a personalised way. Which makes perfect sense from a common perspective. Would you rather be bombarded by the generic ads that in most cases have nothing to do with your interests and desires, or approached on a one-on-one basis with a chance to discuss your specific needs?

Social marketing is directed towards promoting the interests of others, not yours (or your business). Again it makes sense as we are a social species, we live in societies and rely on communication. The most successful communication strategy is the one that takes care of the needs of your communication partner.

And so, opposing the traditional marketing approach, social marketing is based on the idea of giving to the community. Which makes it more efficient than traditional marketing, if measured against the effort applied. In other words, taken 100 random prospects, we are more likely to convert them into customers if using social marketing than traditional marketing.  

But is it scalable?

(to be continued)

 

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When Big Data is not so big anymore

                                                   

We are inundated with information. There is so much information around us they coined a special term - Big Data. To emphasize the sheer size of it.

It is, of course, a problem - to deal with a large amount of data. Various solutions have been created to address it efficiently.  

At nmodes we developed a semantic technology that accurately filters relevant conversations. We applied it to social networks, particularly Twitter. Twitter is a poster child of Big Data. They have 500 million conversations every day. A staggering number. And yet, we found that for many topics, when they are narrowed down and accurately filtered, there are not that many relevant conversations after all.

No more than 5 people are looking for CRM solutions on an average day on Twitter. Even less - two per day on average - are asking for new web hosting providers explicitly, although many more are complaining about their existing providers (which might or might not suggest they are ready to switch or looking for a new option).  

We often have businesses coming to us asking to find relevant conversations and expecting a large number of results. This is what Big Data is supposed to deliver, they assume. Such expectation is likely a product of our ‘keyword search dependency’. Indeed, when we run a keyword search on Twitter, or search engines, or anywhere we get a long list of results. The fact that most of them (up to 98% in many cases) are irrelevant is often lost in the visual illusion of having this long, seemingly endless, list in front of our eyes.

With the quality solutions that accurately deliver only relevant results we experience, for the first time, a situation when there are no longer big lists of random results. Only several relevant ones.  

This is so much more efficient. It saves time, increases productivity, clarifies the picture, and makes Big Data manageable.  

Time for businesses to embrace the new approach.

 

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