It’s so good that humanity came up with a live chat. If you still have memories of endless phone numbers starting with 0-800, you should realize how good it is. However, sometimes when you talk to an operator answering questions about changing the food delivery address or the characteristics of a dust meter, you get a suspicion in your head: am I talking to a live person or a robot?

AI has long been present in our daily lives.

Very few people understand what artificial intelligence is and how it works. The name brings to mind humanoid machines, the movie “Me, Robot” and the capture of the planet. Few people would think of voicing it as a Netflix association or personalized Spotify playlists.

Marketers have been using AI tools for a long time, from improving personal performance to fully automating the SMM sphere. The latter isn’t much use, but it already works. And in the coming years, the marketplace for marketers’ software promises to provide even more impressive tools.

Imagine a to-do list, automatically prioritized and based on your work habits. Or personalized content, the output of which is determined by what you write on social networks. And these are just the easiest examples.

The most important thing is what we need to understand:


SMM players are probably familiar with this concept thanks to a system where Facebook, Twitter and installations determine which news to display on the news feed. SEO marketers regularly encounter search engine algorithms that determine a site’s ranking and search position.

Simply put, the algorithm is the result of data analysis, which allows you to predict the user’s behavior and offer him something that will interest him exactly. In this way, you can select titles for blogs, article titles, visual and text content.

Artificial Intelligence

In the most general sense, artificial intelligence belongs to the field of computer science, which allows computers to perform tasks that require human intervention.

However, it is not so easy to do. The human brain is a unique system where each neuron is tied to another. Scientists are trying to create computers with flexible algorithms that allow them to make creative decisions that increase the chances of success in achieving a particular goal.

AI – a generic term for many different technologies, ranging from chat bots, which we will talk about below, and ending with programs that create relevant text for visitors to your site.

Bots / Bots

Bots are text-based programs that help automate communication. They usually “live” in another messaging application such as Facebook Messenger, WhatsApp or Telegram.

You can place such a program on your website so that users can get answers to frequently asked questions in real time. Unlike the FAQ page, such a bot can collect statistics on requests and supplement the list with up-to-date information.

Cognitive Science

If we consider artificial intelligence as part of the scientific discipline, we get cognitive science as it is. It is a discipline that studies the mind and the processes occurring in AI, bringing together elements of philosophy, psychology, linguistics, anthropology and neurobiology.

The creation of artificial intelligence is just one way of applying cognitive science, which demonstrates how human thinking can be modeled in machines.

Computer Vision

Computer vision is one of the applications of deep learning, which helps the computer “understand” digital images.

For people, conscious perception of images is a basic function. You see a ball thrown at you, and you catch it. But for a computer to “see” a picture, and then describe it, is quite difficult, because this process involves a combination of eye and intelligence. A

Deep Data Analysis / Data Mining

Intelligent Data Analysis – the process of selecting the necessary information from large data sets by a computer.

For example, the e-commerce company Amazon. It can use the collected data to analyze customer information and create a recommendation line “those who buy it also takeā€¦”.

In-depth training / Deep Learning

At the heart of any artificial intelligence, in-depth learning is a very advanced subset of machine learning. It is unlikely that you will need to understand its internal processes, but here’s what to pay attention to: in-depth learning can find the most confusing and complex data in huge databases, passing through many layers of relationships.

This is another chance for marketing to create a system of ideal advertising. Software capable of in-depth analysis will be able to give the user not only the information he wants to see, but also the information he needs.

Machine Learning

Of all the sections of artificial intelligence science, the most fascinating achievements were made as part of machine learning. In fact, it is the ability of the computer to learn by collecting a huge amount of information and creating predictable algorithms based on them. Since the amount of data is constantly growing, the computer corrects its behavior, which allows it to perform its tasks even more effectively.

The data can be anything: marketing software clogged with e-mails, or information about average baseball stakes. Since machine learning allows the computer to improve without the frames set by the program (like most bots), this process is often compared to the process of teaching children – at their own experience.

Natural Language Processing, NLP

Processing the natural language makes bots a more complex system, allowing them to understand voice commands or text. For example, when you speak to Siri, it transforms your voice into text, guides the question through a search engine, and answers using human speech.

Imagine, in the very near future thanks to such technology nobody will have to work in a call-center and answer all day long similar questions. No problem with rough operators and dissatisfied customers is a paradise for marketers.

Semantic Analysis

This term refers primarily to linguistics and to the process of combining phrases, phrases, sentences and paragraphs into a meaningful text. It also refers to the construction of language systems in the context of human culture.

That is, if the computer has the ability to semantic analysis, it can understand human language even taking into account such complex details as idioms, metaphors and other figures of speech.

Supervised Learning

This is one type of machine learning where the human operator enters certain data sets and controls most of the process – hence the name. In controlled training, typical datasets are processed and the results are very concrete. In this case the marketer himself establishes a clear scheme of actions.

Training data / training data

In machine learning, training data is data that is initially entered into the program to study and compile examples. The more data, the more accurate the resulting verification samples are.

It immediately comes to mind a complete characterization of the target audience – age, gender, education, hobby and a million more data that can not be kept in the head. Well, now it’s not necessary.

Self-learning / Unsupervised Learning

Unattended learning is another type of machine learning with minimal human involvement. Programs are allowed to pick up data for study and draw conclusions themselves.

It is, in fact, a work in reverse to supervised learning. The program itself must understand that if we offered the first user products in a 1+1 bundle at a 50% discount, then the next user must also. And here what product will be more actual, the program will already decide itself on the basis of the data received about the buyer.