E-commerce: How Machine Learning can help you sell more products to your customers

With machine learning becoming more and more popular in this era of digital transformations, it is finding its way into nearly all industries. The e-commerce industry is no different, and online e-commerce businesses can advantage significantly by implementing ML. It does not just make it easy for business owners to manage and organize their online store but also generates many opportunities to increase their online sales.

If you own an e-commerce business, there are many ways you can implement machine learning. It is a fantastic tool with many opportunities. Let’s see how it can help e-commerce companies in providing better customer experience and boost sales.

Improved Search Results

Machine learning allows you to provide tailored search results based on the preference of the online customer. Ecommerce leading companies like eBay, Alibaba, and Amazon have already implemented ML-based search results to offer content that is not just related but also targeted to the particular searcher. Even many small companies are implementing machine learning for their e-commerce business with the help of customized applications. It considers your location, your purchase history, and your earlier search preference to give the most accurate results.

Product Recommendations

With the help of machine learning, the product suggestions could be shown significantly well, and therefore, it can serve as a useful tool to direct users through the trending options available to them. By implementing a machine learning solution, the online store system can track the shopping behavior of all the customers and set up a special mode for each consumer.


Sometimes you visit an e-commerce website and leave it without buying anything. After that, you might find the ads of the same site in your Facebook feedback. That’s what we call retargeting. Many e-commerce business owners use machine learning as a part of their sales optimization tactics to retarget their potential customers, specifically who’ve left the store without making a purchase. This assists in not only bringing back the potentially lost customers but also assists the business owner to consider the activities of in-store customers. Thus, they can quickly know which product most of the visitors are visiting and stock that up.

Fraud Elimination

Ecommerce business owners can use ML to find the patterns in the data and know what is okay and what is not and get notified when something is not okay. Companies often have to deal with offensive customers that make bigger orders by using the stolen credit cards or customers that take back their payments after the product has already been delivered.

With sales optimization and machine learning, you can explore patterns for any anomalies. Because frauds take place when there are anomalies or differences in pattern, you can check and abolish the complete process easily. If you are a seller, you can learn what is okay and stop any transactions, which are not.

Predicting Sales

One of the major benefits of machine learning is that it helps in predicting the sales patterns for e-commerce companies. ML can quickly, regularly, and effectively analyze the big data collected and come up with the patterns that help in improving sales. For example, machine learning can effectively perform market basket analysis to define that if a customer buys something, he or she is likely to buy another thing as well.
Machine learning can efficiently predict:

  1. Whether a given user will make a purchase in a particular product category in real-time; so that the retailer can react accordingly.
  2. Whether the customer will be returning and what purchases he will make at certain times.
  3. How much money a particular user will spend in your shop
  4. Prediction of demand for specific product categories

Retailers can use these predictions and plan their marketing and sales strategy accordingly.

Customer Service

As an e-commerce business owner, you know the value and importance of excellent customer service because it defines your sales and your company. However, paying for a special team for round-the-clock customer service could be quite costly for small business owners. This is where ML and AI can come in handy. Companies can utilize predefined templates for answering the specific questions of their customers. This not only helps companies reduce costs but also provides the best service experience to their customers.

How Companies are Implementing and How It Increases Their Revenue?

Implementing machine learning techniques is like hiring a sales representative. Only that this sales representative is quiet, totally invisible going tactfully unnoticed. What is more, this sales representative is not only always polite but saves your customers time. They will be grateful to discover the required products faster through customized search results and recommendation blocks across the website. As a result, customers are sure to make further purchases.

Many e-commerce giants have already implemented this technology. Amazon’s Alexa is the most popular and most famous example of an AI product in e-commerce that helps drive the algorithms that are necessary to Amazon’s targeted marketing strategy and lets Amazon predict what products will be the most demanded. As for Alibaba, most likely, first what comes to our mind is their AI assistants – Tmall Genie and Ali Assistant that’s customer service chatbot processes 95% of customer inquiries and helps to drive internal and customer service operations. Moreover, Alibaba utilizes artificial intelligence to map the most efficient delivery routes resulting in a 30% reduction in travel distances and a 10% reduction in-vehicle use.

With the evolution and the integration of machine learning with business applications, even many small companies are efficiently taking benefits of this technology and booming with the higher ROIs.


The high tech tools like robots entering into the industry, and they are here not to steal jobs, but to change the world we know thoroughly. ML is intended to become a more significant asset to e-commerce companies looking to computerize most of their costly manual processes to gain insights of their customers and, most significantly, to increase purchases, positive ratings and repeat visits. The e-commerce companies who are not realizing the power of machine learning are heading towards their ends.

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