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Machine Learning. How Does It Influence Digital Marketing?

Artificial Intelligence technologies have been an important advance in marketing

For example, through machine learning marketers have the opportunity to make accurate and fast decisions based on big data.

Machine learning is an artificial intelligence technology that is characterized by applying training systems to machines to find solutions that improve the development of human tasks.

This technique provides the machine with initial data for the machine learning system to analyze and learn to classify situations based on known solutions. For example, a common case is when our email marks certain messages with similar characteristics as spam.

Types of Machine Learning

There are two types of Machine Learning.

There is supervised and unsupervised machine learning, the differences of which center around how data is analyzed.

  • Supervised machine learning involves the human inclusion of data and labels. Thus, the machine detects patterns and generates projections or forecasts

  • In unsupervised learning, the algorithm modifies itself and does not contain any data or have been labeled.
Why apply Machine Learning in Digital Marketing?
In digital marketing, machine learning is used above all to analyze user information and find patterns in the activities that determine their tastes, preferences, and needs.

This can take the customer experience to higher levels because if we can predict the future behavior of our audience, we can optimize advertising campaigns based on accurate data.

Machine learning in marketing means simplifying the task of specialists who must constantly evaluate and analyze customer data. Although it seems simple, this work is long and complicated, and often incorrect results can be obtained because the information is constantly changing.

Machine learning acts by considering unlimited behavioral parameters in minutes, reaching highly accurate results, which is an alternative to changes in the quality of the traffic generated by campaigns.
Uses of Machine Learning for daily work in Digital Marketing
We have already explained some of the most frequent uses and the advantages of machine learning applied to digital marketing.

Let's see other tasks that this technology simplifies:

  • Recommendation systems
A recommendation system uses predictions derived from machine learning to generate the products that a customer is most likely to buy. With this information, personalized offers of "recommended products" and "similar products" are sent to the public on the web.

  • Segmentation
The segmentations allow you to create that target audience that is more likely to buy the products offered by the business.

Thus, we allocate the advertising budget to generate content of interest aimed at those users who are more likely to buy our product or service.

Segmentation allows you to show ads to users after they perform a certain action or search.

  • Churn Rate Forecast
To understand the revenue loss associated with customer churn, we use machine learning. This generates percentage or monetary terms.

But these predictions also allow responding to a customer's intention to abandon your product or service through loyalty actions, to prevent that from happening.

  • Time optimization
The system predicts when the time is right to do a specific task, based on the context data it analyzes. For example, it can warn us of the cessation of production of a certain product, the increase in sales, etc.

  • Voice and text customer service
Through machine learning patterns, words or phrases can be identified, and then the appropriate response to them is generated.

  • Information security and anti-fraud
Fundamentally in e-commerce sites, machine learning helps us detect fraudulent users through their access, profile, historical data, etc. It also predicts cybersecurity breaches and allows you to reduce the percentage of thefts through false credit cards.