Targeting Recommendation System Based On Machine Learning

Machine learning, discovering hidden patterns in data
In fact, machine learning is an old discipline and technology that was created over 50 years ago, but it has been difficult to use because it has been difficult to have infrastructure and computing power.

However, the recent explosive development. Of computing technology, the accumulation of theoretical and practical. Knowledge for effective application, and the advent of the big data. Era have sparked interest in machine learning. In particular, new technologies are need as companies use big data that could not be dealt. With in the past, and problems that cannot be solv with existing. Statistics and analysis technologies arise. Machine learning, which consists of various algorithms, applies various things. Such as data mining, clustering, and association analysis.


STP Strategy, Segmentation/Targeting/Positioning

The advantage of machine learning is Kyrgyzstan Email List that it discovers patterns hidden in data. This allows them to extract value from massive amounts of data that exceed human thinking and analytical capabilities to enhance the customer experience, provide product recommendations, or even deliver more personalized content.

In the field of marketing, which took the lead in utilizing big data, machine learning is being introduced one after another, and machine learning-based automatic targeting recommendation system was one of the representative fields where it was expected to be used.

Machine Learning Increases the Reliability of Recommendation Systems


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A recommendation system is a system that automatically searches for and provides products that a user is expect to purchase in the future bas on the CH Leads user’s previous behavior. This recommendation system has already been introducby most e-commerce companies and is seeing many effects. However, the accuracy was low because it did not reflect the user’s product evaluation criteria or factors that affect purchase decision-making. To overcome these limitations and increase reliability, various algorithms and statistical machine learning were introduc.

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