Machine Learning in digital marketing
Posted: Sun Jan 05, 2025 5:59 am
Machine Learning, Artificial Intelligence, big data… Not only are these terms increasingly present in our daily lives, they are also part of our routine even if we don’t realize it.
In this post, we will talk more specifically about Machine Learning and the role of this technology in the digital marketing universe. Are you ready?
Machine Learning vs. Artificial Intelligence: What's the Difference?
First of all, it is important to explain the difference between Machine Learning and a term that has been familiar to us for a long time.
The term Artificial Intelligence (AI) is already familiar to us, whether in science fiction films of the past or in real-world applications in today's world, such as the GPS app you use on your cell phone. Artificial Intelligence is, after all, a computer imitating human intelligence, that is, when the machine can learn from previous experiences and make more assertive predictions, just like the human mind would.
Machine Learning falls under the umbrella of AI and is characterized by being automatic learning, where the machine can learn without necessarily being programmed. Furthermore, the more data it is exposed to, the more it learns and improves, and it does not need humans to make certain changes.
And how do machines do this? With algorithms and big data, they create data patterns and learn to perform tasks without human help. In addition, statistical analyses can calculate the best answers with less chance of error.
And how does this technology work in marketing?
One of the main advantages of Machine Learning is that there are no limits to data input, and it is possible to feed information and adjust the message based on needs. And all of this in real time. In other words, the machine can display an offer to a specific customer and, an hour later, after analyzing more information based on their behavior, it can display another, more assertive offer.
Machine Learning also achieves better results in customer retention and conversion, as it understands the ideal time to get in touch. In fact, one not-so-easy task that these machines are bulgaria phone number data capable of doing is segmenting customers based on certain behavior patterns that you probably wouldn't be able to identify. This helps to display more appropriate communication with a higher chance of conversion.
Another important piece of information is the calculation of the customer's “useful life” within your business, which allows you to identify the right moments to deliver appropriate messages and optimize their interactions and purchases within their period of connection with the brand.
All of this really does seem incredible and, to a certain extent, magical! After all, in addition to making work easier, Machine Learning delivers much more efficient and assertive results, wasting less time (and money) and reaching levels of improvement and details much deeper than humans could achieve.
But, from the moment everything is automated, don't we run the risk of having extremely standardized advertising?
To avoid this, one solution would be for companies to invest more in brand language, relevant criteria and attributes, incorporating these guidelines into communication algorithms. Machine Learning will probably not completely replace creative teams, which should work together with data and automation teams, bringing the brand's most important values to the machine.
In this post, we will talk more specifically about Machine Learning and the role of this technology in the digital marketing universe. Are you ready?
Machine Learning vs. Artificial Intelligence: What's the Difference?
First of all, it is important to explain the difference between Machine Learning and a term that has been familiar to us for a long time.
The term Artificial Intelligence (AI) is already familiar to us, whether in science fiction films of the past or in real-world applications in today's world, such as the GPS app you use on your cell phone. Artificial Intelligence is, after all, a computer imitating human intelligence, that is, when the machine can learn from previous experiences and make more assertive predictions, just like the human mind would.
Machine Learning falls under the umbrella of AI and is characterized by being automatic learning, where the machine can learn without necessarily being programmed. Furthermore, the more data it is exposed to, the more it learns and improves, and it does not need humans to make certain changes.
And how do machines do this? With algorithms and big data, they create data patterns and learn to perform tasks without human help. In addition, statistical analyses can calculate the best answers with less chance of error.
And how does this technology work in marketing?
One of the main advantages of Machine Learning is that there are no limits to data input, and it is possible to feed information and adjust the message based on needs. And all of this in real time. In other words, the machine can display an offer to a specific customer and, an hour later, after analyzing more information based on their behavior, it can display another, more assertive offer.
Machine Learning also achieves better results in customer retention and conversion, as it understands the ideal time to get in touch. In fact, one not-so-easy task that these machines are bulgaria phone number data capable of doing is segmenting customers based on certain behavior patterns that you probably wouldn't be able to identify. This helps to display more appropriate communication with a higher chance of conversion.
Another important piece of information is the calculation of the customer's “useful life” within your business, which allows you to identify the right moments to deliver appropriate messages and optimize their interactions and purchases within their period of connection with the brand.
All of this really does seem incredible and, to a certain extent, magical! After all, in addition to making work easier, Machine Learning delivers much more efficient and assertive results, wasting less time (and money) and reaching levels of improvement and details much deeper than humans could achieve.
But, from the moment everything is automated, don't we run the risk of having extremely standardized advertising?
To avoid this, one solution would be for companies to invest more in brand language, relevant criteria and attributes, incorporating these guidelines into communication algorithms. Machine Learning will probably not completely replace creative teams, which should work together with data and automation teams, bringing the brand's most important values to the machine.