5 Ways to Use Machine Learning for E-commerce

5 Ways to Use Machine Learning for E-commerce

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It goes without saying that artificial intelligence (AI) and machine learning (ML) have become an essential part of the e-commerce industry over the last few years. Many companies understanding the significance of the role of this new technology have already started the adaptation of it in their own structures. When it comes to the e-commerce world, machine learning can be used for various purposes that include a better understanding of customer’s choices and behaviors, selection of the most relevant offer for the given person, or making the right business decisions at the right time.

 In this article, we are going to take a look at five crucial aspects of machine learning in e-commerce. What can be found on our list?

Enhanced personalization

Artificial intelligence has enabled the e-commerce industry to provide customers with a personalized shopping experience. With the use of AI-powered systems, companies can monitor customer’s references in real time and adjust displayed products according to them. Information such as analysis of past shopping carts, purchasing history, and searches turns out to be of great value when it comes to shopping experience personalization. Moreover, personalization can also be used to improve email marketing campaigns and newsletters. And both of these tools are extensively used in the e-commerce sector.

Pricing management

Knowing the best prices for the products in your offer is one of the main qualities online retailers should have. Luckily, nowadays, thanks to machine learning, e-commerce companies are able to identify accurate pricing patterns and, basing on them, set the optimal prices for specific products and even predict possible future prices of them. Automated pricing also helps to reduce the amount of manual work that would have to be done while tracking the prices of competitive companies.

Chatbots and virtual assistants

Another significant  AI application that is often used in e-commerce revolved around chatbots and voicebots frequently referred to as virtual assistants. These AI-fueled systems interact with customers through text or voice interface. Consumers can either type their messages via the chat box or send voice messages. In both cases, the AI system should not have problems with understating the message. Additionally, they are usually able to adapt to the language spoken by the customer.

Another benefit concerning chatbots is that they are available 24/7 and answer immediately. Thanks to them, customers do not have to spend long hours on the helpline and can receive answers to their questions directly and accurately. What is more, your company can reduce the number of employees hired in the contact center to deal with customers, which results in cutting down internal costs.

Stock management

AI also helps in keeping the right amount of products that will fulfill market demands without creating overstocking. AI algorithms analyze information like sales trends in previous years, possible changes in product demands, and issues that could impact it. The application of AI that goes with inventory management is warehouse management. Companies can create automated warehouses supplied with robots that can dispatch orders and retire stocks 24/7. This way, AI once again proves itself to be especially useful in cost reduction and work optimization.

Gathering information to make proper business decisions

AI is irreplaceable in identifying opportunities in data that a human eye could skip. ML algorithms use internal and external information such as customer behavior and preferences, market trends, companies’ revenues, consequences of previous business decisions. What makes this application more appealing is the fact that AI constantly learns from new data and updates recommendations in a very short period.

AI is undoubtedly the technology of the present and the future. Companies need it to survive in a constantly changing competitive environment. Ones who have not implemented it yet, should immediately these options in order to not stay far behind the competition and acquire market advantage. Ultimately, investment in better customer experience, offer personalization, and internal processes optimization cannot turn out to be a bad decision. For more information, visit https://addepto.com/machine-learning-consulting/.

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