Even before being “baptized” and identified as an area of study, Artificial Intelligence was seen as a field with high transformative power. Nowadays, we already see the results of this in all sectors in which it is used, including Digital Marketing.
Although there is a certain fear, due to lack of knowledge, that we will be replaced by machines, the truth is that interaction with them produces much more efficient results. No wonder, between 2018 and 2019, companies that implemented resources with artificial intelligence grew between 4% and 14%, according to a survey by Gartner.
Within this universe full of possibilities, deep learning emerges as a sub-area with great potential for investment, especially when it comes to increasing funding rates and student retention.
Deep learning is available presently including our chatbots, a technology that is still only used by 42.2% of the 500 largest educational institutions in the country. The adoption of extremely responsive virtual assistants capable of adopting natural language has a positive impact on the experience of students and future customers, speeding up service.
Continue reading this article to discover how its use can make a big difference in Educational Marketing.
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Contextualization of machine learning;
Good reading!
Contextualization of machine learning
Before we explain better what deep learning is and how it works, we need to talk about the machine learning, that is, machine learning. In short, this is one of the several branches of artificial intelligence where algorithms collect massive data. And it is precisely from this information that the equipment learns.
With minimal human interference, the machine can modify its own behavior and make predictions. As you go through new experiences, you are able to adjust and offer responses that are more relevant to the context.
The logic is always the same, but some contours vary and give rise to different types of learning. Three, more precisely.
In supervised learning, the machine has a kind of tutor and the process takes place based on labeled data. Basically, the equipment is taught, through classification and regression techniques, into which class or category it should organize the information it receives.
In unsupervised learning, the machine does not receive this initial guidance. The data is not labeled and you have no control over what will be obtained. Through grouping, association and dimension reduction, a strategy is used to identify patterns that are not yet very clear in the data.
And last but not least, reinforcement learning, which differs a bit from previous models. In this case, the process occurs through trial and error. For every hit the machine makes, it is rewarded. For every mistake, she is punished. This makes you adjust your responses and patterns to maximize the results obtained.
As you can see, there is no single way to teach machines, although they all involve the use of algorithms. Delving deeper into machine learning, we ended up arriving at deep learning, which we will talk about in the next topic, specifically about how it can be advantageous for Educational Marketing.
Advantages for Educational Marketing
The 4RevOps works with artificial intelligence and has consistently used deep learning as a tool to promote retention and recruitment of students of partner educational institutions. One Educational Marketing increasingly technological, focused and results-driven is our main objective.
An example of this is the use of systems that qualify leads according to the objective. The software “learns” from the database of students already enrolled at the institution, discovering the most common actions and profile.
Then, and with little or no human intervention, it indicates which contacts have the greatest potential for enrollment. This information is valuable as it saves time and resources in preparing a fundraising strategy.
The same system can make predictions about students who are at risk of dropping out, allowing targeted campaigns to build loyalty and maintenance.
In times of crisis, like the one we are experiencing now, it is essential to invest in what brings a guaranteed return. The use of deep learning tools allows you to discover precisely where, what and how to bet, as there is no time or resources for trial and error.
SEE TOO:
- Artificial Intelligence and its help in student retention;
- Artificial Intelligence in education: future becomes reality;
- How to register using artificial intelligence?
Understanding the deep learning
Deep learning It is also known as deep learning or constant learning. Using this technology allows machines to learn on their own through pattern recognition. So far, nothing new in relation to what we discussed previously. The difference lies in the type of algorithm used in this process.
A base for deep learning lies in the use of artificial neural networks, a specific category of algorithms that was developed to “imitate” biological neural networks. The degree of complexity is even greater because these networks work in layers, each of them with a different interpretation of the data to which the machine was exposed.
This type of neural networks began to be developed in the 1950s. Much more complex today, they are now used in different types of services and products. Two of the most popular applications are voice recognition and facial recognition, which demonstrate the great computational power of this technology.
In practice, to understand deep learning It is necessary to understand how these artificial neural networks work. When the machine receives information, it goes to the input layer and then goes on to processing. Here, the numerous hidden layers contribute different data and then the obtained result goes to the output layer.
While in a simple neural network there is only one processing layer, a deep neural network has several. This translates into a faster and, probably, more accurate response.
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Deep learning no Marketing
There are those who say that deep learning is artificial intelligence in its essence, being truly transformative. And it's still true. Since it began to be widely used, technology has changed dynamics, streamlined processes, reduced costs and even introduced new possibilities in different industries.
In Marketing, more specifically in Digital Marketing, this scenario was no different. Much of this success comes from the fruitful relationship between DL and big data. This expression, increasingly used, refers to the large volume of structured and unstructured data that is generated.
The employment of deep learning in the processing and analysis of big data has proven to be efficient, as long as supervised and unsupervised learning techniques are used together. This makes it possible to reveal more precisely the behavior patterns and build strategies focused on these trends.
Machines are capable of acting quickly, recognizing the most subtle changes and even allowing some predictions to be made based on these pattern changes.
According to a study published in QuanticMind, the market based on these predictive analyzes will generate around US$10.95 billion by 2022. A number that shows the true power of the combination between the use of artificial intelligence and Marketing.
For strategic use of deep learning, it is essential to rely on an experienced company that has a multidisciplinary team to guide the work and interpretation of data. Mkt4edu, despite its young age, already has a lot of experience in the subject, something visible in the more than 3,000 campaigns created in these years of activity.
Here, tools such as Leadscore and Watson Machine Learning are important in measuring results. These models are generated through experiment, with the weights of each field present in the training data. Next, updated data is formulated, creating a new list.
Want to know better how this works? Schedule a meeting with us to know how deep learning can make your institution prosper!
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