Why can cognitive computing transform the entire e-commerce market?

Aug 23, 2019 250 views

In the current market scenario, the use of AI for data analysis is practically a must. With the amount of data generated by current systems, it is impossible for a human operator to analyze everything without the help of machines. But while using techniques such as Business Intelligence (BI), deep learning (DL) and machine learning (ML) are already relatively common even in small businesses, it is a new type of information analysis that should define the entire data market in the next years: cognitive computing (CC).

CC is the closest technology to the functioning of a human brain, being able to learn, reason, argue, analyze, and make decisions all in real time. In addition, it is able to do something that none of the other AI methods can: analyze the so-called "dark data" (name that receives the unstructured information that is discarded from the analysis of other AI systems because of excess data, and that according to an estimate of IBM can correspond to almost 90% of the data generated by sensors and other devices of conversion of analog functions in digital answers, and about 80% of all the digital information that circulates around the world.

Because it is not analyzed by any of the methods used today, IT experts believe that starting to take these data into account during the analysis can revolutionize our use of technology. According to a recent IBM report, the company expects that by 2020 90% of all information circulating in digital form will be composed of the so-called "dark data," and developing cognitive systems that can handle that demand should be the difference between dominate the market or be dominated by it.

This is not to say that no one has ever tried to access this information, but the limitations of other methods of analysis have made access to the dark data very difficult. Even among researchers who were able to create BI, DL, or ML-based systems to analyze this kind of information, they saw their algorithms fail if there were any unforeseen ones in the system, since the collection and analysis could only function correctly in preprogrammed scenarios.

This is the great advantage of cognitive computing over others: by imitating the functioning of the human brain, these systems can adapt themselves to any unforeseen occurrence during the process, not requiring the intervention of human hands during the operation.

But that does not mean that these systems will replace workers in the industry. To prevent the information analyzed by these systems from being free from any political bias or position, it will always be necessary to have a human operator not only checking the machine's work, but also deciding how that information will be used, managed and protected.

A New Era for Marketing

According to a survey conducted by IBM among CEOs of various companies around the world, 75 percent of them believe that cognitive computing techniques are likely to change the entire industry in the coming years, and one of the sectors that will make the most difference is marketing .

Today, the marketing industry is one of the most used IAs to analyze customer and market information, allowing the creation of campaigns that will not only reach a certain audience, but can already quantify the success they will have before even started. But with the use of CC, all this can reach another level.

With the new technology, it will be possible to extrapolate the information provided by social media, e-mail communication and site access metrics, allowing the development of experiences that meet exactly the needs and the highest desires of the audience, as well as the detection of trends that would be imperceptible to human capacity.

And the use of this technology should happen sooner than you think: the same UBM survey also revealed that 73% of the CEOs surveyed want to install CC systems in their companies as early as 2019. But, despite this interest in technology, it should be an exclusivity only for large companies in the coming years.

This is because, to create such an IA (such as IBM's Watson), it took not only decades of research but also hundreds of millions of dollars in investment, something that should take all those who are not "Big players" of the market and technology.

Nevertheless, any company that has the opportunity to use such a system should not be afraid to risk: more than just an increase in profit, the use of such systems should positively impact the entire trading system of the company, and be primarily responsible by a complete transformation in the whole working mode of the sector.