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The e-commerce industry is developing rapidly. To satisfy all customers’ needs, you should know what they want. In brick-and-mortar shops, you may simply ask them. When it comes to the online eCommerce industry, Machine Learning is the solution.

Artificial Intelligence and Machine Learning are popular terms to use nowadays. However, not many people actually understand their meaning. Before we move on, SapientPro development team offers you to have a look at how these two terms are different from each other:

Artificial Intelligence - is a machine capable of performing a task, imitating human intelligence.

Machine learning is defined as the study of computer algorithms that allow computer programs to automatically improve through experience.

ML is your solution to understanding the behavior of the target customers, reduce cart abandonment rates and as a result increase sales.

Nowadays there are different ways in which ML can affect eCommerce business:

Smart Product Recommendations

Recent research held in the USA showed that 63% of consumers are interested in personalized recommendations. Those are the vivid result of Machine Learning implementation.

Online shoppers are already tired of being presented with the products they are not interested in. Specific algorithms can figure out what the customer is really targeting to purchase, based on the analyzed data, and studying the buyer’s behavior.

Now there exist two types of algorithms for creating personalized recommendations:

The collaborative filtering technique is based on what other customers prefer to have. If one buyer chooses two products, there is a chance that the other buyer would like those things together too.

Content-based filtering takes into account the personal information about the client like gender, age, purchasing preferences; and the product’s characteristics.

Customer Support

The customers are becoming fed up with long waiting for the support to answer to their queries. Sometimes the employees are unable to help clients solve their problems due to their low competence or inability to find the relevant answer quickly.

Chatbots have evolved drastically and sometimes you don’t even pay attention to the fact that you are asking a robot for help. That’s ok, regarding how far the ML got so far.

Pricing optimization

The high competition enables users to choose the best price on another website if they are not satisfied with what your e-store offers. To avoid losing customers, we recommend you implement price optimization.

Dynamic prices presuppose not only lowering the price, but you can also make the products more expensive if the demand is higher. The price can also depend on the time, day of the week, season, competitive prices and many others.

Price optimization sometimes may have a negative effect on the customers, so this question has to be taken up pretty seriously, considering all the sides of the question.

There are still more fields where you can apply Machine Learning to boost your eCommerce business. Those may include the following:

Inventory forecast – can help figure out how man products should be manufactured or ordered, based on the analysis of market demands.

Churn prediction – uses algorithms to define the customers who are apt to terminate the cooperation with a business.

Product categorization – by the automatic grouping of the products, the organization process becomes easier and navigation more user-friendly

Customer segmentation – can create groups of clients, based on their preferences and personal characteristics like age, gender, etc. to improve the target marketing

Machine learning becomes available to a larger number of e-commerce business owners. The data-driven technology advances and it’s a great benefit to use the opportunities the times bring to you. 



The e-commerce industry is developing rapidly. To satisfy all customers’ needs, you should know what they want. In brick-and-mortar shops, you may simply ask them. When it comes to the online eCommerce industry, Machine Learning is the solution.

Artificial Intelligence and Machine Learning are popular terms to use nowadays. However, not many people actually understand their meaning. Before we move on, SapientPro development team offers you to have a look at how these two terms are different from each other:

Artificial Intelligence - is a machine capable of performing a task, imitating human intelligence.

Machine learning is defined as the study of computer algorithms that allow computer programs to automatically improve through experience.

ML is your solution to understanding the behavior of the target customers, reduce cart abandonment rates and as a result increase sales.

Nowadays there are different ways in which ML can affect eCommerce business:

Smart Product Recommendations

Recent research held in the USA showed that 63% of consumers are interested in personalized recommendations. Those are the vivid result of Machine Learning implementation.

Online shoppers are already tired of being presented with the products they are not interested in. Specific algorithms can figure out what the customer is really targeting to purchase, based on the analyzed data, and studying the buyer’s behavior.

Now there exist two types of algorithms for creating personalized recommendations:

The collaborative filtering technique is based on what other customers prefer to have. If one buyer chooses two products, there is a chance that the other buyer would like those things together too.

Content-based filtering takes into account the personal information about the client like gender, age, purchasing preferences; and the product’s characteristics.

Customer Support

The customers are becoming fed up with long waiting for the support to answer to their queries. Sometimes the employees are unable to help clients solve their problems due to their low competence or inability to find the relevant answer quickly.

Chatbots have evolved drastically and sometimes you don’t even pay attention to the fact that you are asking a robot for help. That’s ok, regarding how far the ML got so far.

Pricing optimization

The high competition enables users to choose the best price on another website if they are not satisfied with what your e-store offers. To avoid losing customers, we recommend you implement price optimization.

Dynamic prices presuppose not only lowering the price, but you can also make the products more expensive if the demand is higher. The price can also depend on the time, day of the week, season, competitive prices and many others.

Price optimization sometimes may have a negative effect on the customers, so this question has to be taken up pretty seriously, considering all the sides of the question.

There are still more fields where you can apply Machine Learning to boost your eCommerce business. Those may include the following:

Inventory forecast – can help figure out how man products should be manufactured or ordered, based on the analysis of market demands.

Churn prediction – uses algorithms to define the customers who are apt to terminate the cooperation with a business.

Product categorization – by the automatic grouping of the products, the organization process becomes easier and navigation more user-friendly

Customer segmentation – can create groups of clients, based on their preferences and personal characteristics like age, gender, etc. to improve the target marketing

Machine learning becomes available to a larger number of e-commerce business owners. The data-driven technology advances and it’s a great benefit to use the opportunities the times bring to you. 

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