Machine learning: the technology companies use to innovate
ICT (Information and Communication Technologies) have been integrated in such a way in our daily lives that it is impossible to imagine what it was like without them. And when it seemed that they could no longer surprise us, the concept of machine learning arises, systems capable of learning from themselves without the need for a human being. Automatic learning, focused on artificial intelligence, opens the door to a new innovative era whose applications are as diverse as they are impossible to imagine.
Machine learning technology creates solutions that learn automatically, in the same way as a person. Artificial intelligence (AI) allows us to define predictive algorithms that enable them to reveal future behaviours, identify patterns and improve the systems themselves, thanks to the data they constantly receive.
And this would not be possible without Big Data. Their ability to collect huge amounts of information and allow agile access to it makes the learning systems extract the full value and integrate it into the software, so that this can perform actions without the need for a person to previously program it. They are thus able to adapt to changes in the environment in real time.
Although these advances seem novel, their applications are not at all. In fact, every time we browse the Internet, we use the voice assistants from Apple and Google, we consult weather information or we look at the Facebook advertising we are using machine learning. The fact is that these technologies, considered cognitive, are so penetrating that we use them without perceiving them.
Prediction techniques for businesses
Until now, technology allowed for a descriptive perspective of the company’s activity based on data that describe possible future trends. This is what is known as Business Intelligence, which collects data from the past and classifies them to analyse the current situation and devise future strategies.
However, machine learning goes much further, because its system is based on the prediction of patterns, and not their classification. The technology no longer focuses on the past, but on the future, anticipating consumer behaviour.
At the same time, it does not focus on general patterns of behaviour, as it has done up to now, but rather individualizes them, from client to client. This supposes a huge potential to establish business strategies, for example, when forecasting the consumption pattern for a very specific market with a reliability of close to 100%.
"Thanks to Big Data, automatic learning systems have been developed to do jobs for themselves"
Machine learning, the best ally in attending customers
The possibilities offered by this technology are so varied that its full capacity is still unknown. Facial or eye recognition systems, the diagnosis of diseases, the creation of drugs or autonomous driving are just some of the techniques based on it.
In the business field, where more practical applications are found is in the customer service department, as it improves the user experience as never before, while making the brand the perfect companion for the consumer.
Customer Lifetime Value (CLV) is one of the most demanded solutions. Focused on the client, it provides a reliable analysis of their relationship with the company, establishing whether they are a lasting user, the investment made in them and whether a specific loyalty campaign needs to be launched. The dream of all advertising department.
It thus becomes a basic tool that makes it possible to predict loss of customers, and to direct the resources of the company towards those that require greater reinforcement. It keeps the users that were going to leave, for example, by creating an automatic system of sending emails with customised offers to those at risk.
Added value for business
The goal of every business is to attract customers and keep them. In this sense, the segmentation of the public, grouping it according to characteristics and similar tastes, to draw up strategies that optimise the service was a business milestone. Now, machine learning goes a step further by offering new products and personalised services, not based on groups but on individual users, and all without the need for a workforce dedicated exclusively to this task, which maximises business efficiency.
Discovering future trends and automating tasks previously carried out by people is an advantage in the company's interactions with the client, enabling it to anticipate the consumer's needs and offer evidence-based answers.
This potential will make a difference in future business. Therefore, the large groups have focused on this technology. Not surprisingly, 2017 stands as the one in which more has been invested in companies specialised in machine learning, 17,000 million dollars, four times that spent the year before.