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Applications and Contributions of Machine Learning for E-Commerce and Retail Sectors

The development of new technologies positively affects human life, especially the way of doing business. Today’s sectors that benefit from the blessings of technology include e-commerce and retail. The concept of electronic commerce, which has come to life with the spread of the Internet, obtains a more advantageous position than physical commerce every day thanks to machine learning and other dynamic technologies. Although there are many technologies that contribute to the e-commerce sector, in this article we will especially touch on machine learning technology and the contributions of this technology to the e-commerce sector.

The Place of Machine Learning in Electronic Commerce

Machine learning has a place in the e-commerce and retail sectors that cannot be ignored. According to the WORLDEF Use of Artificial Intelligence in E-Commerce report published in 2021, the volume of machine learning in the field of e-commerce is over $ 300 billion. In the same report, it is stated that this volume is expected to rise to over $ 1 trillion in the coming years.

Machine learning technology, which helps retail firms by developing new strategies to reach customers, allows all companies equally to reach customers. Machine learning technology increases competition in the retail industry by changing the business methods used and reducing costs. In addition to creating a more competitive environment for the industry, machine learning technology also makes e-commerce transactions much safer, more profitable and predictable thanks to the convenience it offers. Machine learning technology that enables them to learn customer behavior and strategize accordingly makes it easier for merchants to run tailored advertising campaigns to customers.

The biggest convenience that artificial intelligence algorithms offer in machine learning is that they can easily learn and imitate customer behaviors and take action according to the possible future behaviors of users. When it comes to advertising or marketing, it’s not hard to see how advantageous this type of technology is. For example, machine learning, which detects a common product purchased by a certain group of users, can make its target audience more specific based on this information, and it can more often deliver the product it advertises in front of interested users. With this technology, the target audience behaviors and habits are analyzed, which products people may be interested in, and personalized ads are shown to users in a way that will facilitate the seller’s work.

Machine Learning Applications in E-Commerce and Retail Industries

Although we tried to summarize it simply above, machine learning applications have multiple applications in the e-commerce and retail sectors. It is possible to list the main ones from these applications as follows:

  • Price listing: Every consumer wants to buy the products they buy at the most affordable price. This desire has led to the creation of websites that compare the prices of products on different e-commerce platforms. Using a form of machine learning, these sites record the descriptions and prices of certain products on different pages and group them on their own pages. Thus, users can compare the prices of products on different e-commerce platforms through a single platform.
  • Setting a price: Have you ever searched for a hotel online? Almost all online ticket sites, including the company that owns this famous advertising phrase, determine prices with machine learning technology. Many details such as how many people searched for the tickets on the pages, how many people clicked on the add to cart button, how many of the users who clicked completed the purchase process are effective in dynamic pricing. For this reason, when you search in incognito mode or on a different device, the prices you see may be cheaper. Such technologies are especially preferred by sites that sell hotels and flight tickets, or platforms that offer certified online training.
  • Site search results: Search results on e-commerce sites are directly linked to the purchasing habits of customers. Typically, a customer buys products related to that product as well as the product they purchase. This means that when you search e-commerce sites, you will see other results related to the product you are looking for. For example, considering that a large part of the users who buy a dog collar also buy dog food, users who search for a dog collar may be faced with dog food options.
  • Customer support: Thanks to machine learning, large companies can offer live support to their customers with live chatbots. Thanks to chatbots, companies that do not have to hire extra staff for customer support both save costs and make it easier for their customers. These chatbots, which benefit from machine learning technology, can solve customer problems efficiently by detecting customers’ problems and trying to produce solutions.

Contributions of Machine Learning to Electronic Commerce Sectors

As you can see, machine learning technologies contribute to the e-commerce and retail sectors. Thanks to machine learning, customers’ demands, needs and problems are more easily identified and solutions are quickly produced for them. We can list a few of the contributions of machine learning to the e-commerce sector as follows:

  • Ensure a more efficient sales process
  • Responding more effectively to the wishes and needs of the customer
  • Dynamic determination of prices on websites
  • Conducting advertising activities in a targeted audience oriented manner
  • Accelerate procurement processes by determining which products will be needed
  • Helping customers solve their problems

In today’s world, where new technologies are constantly being developed, it is possible to say that machine learning will contribute to the e-commerce sector in the future and will have a more widespread use. The contributions mentioned above can only be seen as a beginning.

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