Machine Learning in eCommerce - The Future of Online Shopping

We all know that technology is advancing at breakneck speed and along with that, Commerce has also been thriving tremendously since the rise of the Internet. With the global spread of smartphones, everyone is able to access stores online and spend their money to buy necessary products even in the middle of the Covid-19 pandemic. 

Artificial Intelligence (AI) is the way forward that will definitely change the whole world in the future due to its profound impact across different industries.

Today in this article we will introduce to you some of the most notable applications of machine learning in eCommerce but first, let’s cover some basics.

What is Machine Learning in eCommerce? 

As its name says, it’s a process by which a machine can learn. Here, machine learning is about collecting data, processing, analyzing, and creating suggestions.

Nowadays, machine learning is probably the most used buzzword. It involves creating algorithms to access and learn from data by pattern recognition. 

There are 3 main types of machine learning algorithms:

• Supervised: They can predict future events based on what’s learned in the past and compare the output to the intended results. 
• Unsupervised: These algorithms will analyze unclassified and unlabeled data and then draw inferences, patterns, or ID hidden structures.
• Reinforcement: These algorithms test outputs through trial and error to identify correct behavior. 

Thanks to the invention of GPUs (Graphics Processing Units), the acceleration of machine learning has been made clear. These processors allow algorithms to analyze a huge amount of data in a far shorter time than before. Modern machine learning in eCommerce has the ability to understand complicated data and give complex and accurate predictions based on data collected. 

Artificial Intelligence vs Machine learning in eCommerce

You may feel unsure about the difference between Artificial Intelligence and Machine Learning in eCommerce and is the meaning the same? Well, the answer is either yes or no, you can call machine learning AI, but AI is not always machine learning. 

• Machine learning

Machine learning is part of artificial intelligence, which uses data to make predictions and implement actions accordingly. The more data the machine learning gets, the more accurate outputs it can produce. That’s where the part “learn” comes from and how algorithms are described as being able to learn. 

• Artificial intelligence

Artificial intelligence is a broad concept, and it’s any technology that makes computers do intelligent things that people can do, such as learning, thinking, reasoning, sensing, and making decisions. 

Deep learning is also another subset of AI and machine learning. In deep learning, massive data sets will be analyzed by complex neural networks. 

What are the benefits of machine learning in eCommerce?

There are many business benefits that machine learning brings to people, especially to online retailers because the ability of algorithms to make sense of a large volume of data is invaluable. Now machine learning is applied to almost every area of eCommerce operations, from managing inventory to improving customer experience. It's about time to discover how exactly your business can benefit from using machine learning in eCommerce.

1. Increase conversions

Every eCommerce site owner wishes that their site is good enough to turn browsers into online shoppers and bring more revenues. Therefore, it’s not surprising if you may feel a little obsessed with your site’s conversion rate. However, machine learning is very useful and it can help you increase your conversion rate in many ways. 

We will go deeper into how machine learning in eCommerce aids conversion rate in the next eCommerce use cases section. But typically, its importance lies in two areas: product recommendations and how it can empower search engines. 

Machine learning algorithms use natural language processing to deliver smarter search results. By understanding what users type in the search bar and prior searches, machine learning can show the information that attracts the users’ attention,  even without the name of a specific product or a precise description in the search bar.

Product recommendations also work in a smarter way when they are powered by machine learning. Algorithms can analyze the visitors’ behavior on an eCommerce site and then suggest product recommendations that the visitor will likely interact with most. 

That way when an individual returns, they will see similar items to those they have an interest in. The same thing happens when you visit the Amazon website, you see a bunch of things related to items you bought before or clicked on. 

2. Run marketing campaigns in a more relevant way

eCommerce marketing campaigns work best if they can reach their target audience and the good news is machine learning can bring an eCommerce business to a whole new level. 

Machine learning algorithms are vital to segmentation customers more accurately because they can split your potential customers based on their interests so that you can target them more relevantly. 

Another area where machine learning is invaluable to your online business is retargeting. Similar to targeting customers, algorithms can also understand customers’ behavior and recommend particularly relevant retargeting campaigns. 

For example, on the Bliss website, a customer might have browsed a skincare product for sky skin and even added the item to their cart but didn't purchase in the end. The thing is they did provide an email address and the machine learning of Bliss will see that visitor is a new target for retargeting and send a reminder email selling the exact dry skin product. That way can somehow make sure you won’t miss your potential customers and increase the chance of them buying your products. 

3. Improve the efficiency of in-house operations

Not all benefits of machine learning in eCommerce are related to customers’ experience. You can also make your operations much more efficient with the real-time insights that algorithms deliver to you.

For example, in managing your stock levels and accounting for your inventory, many businesses have difficulty in making FIFO and LIFO decisions, so the best way to find what is the best method for you is to analyze customer data. 

With machine learning in eCommerce, such an analysis is much more smooth and accurate when it comes to the numbers on sales, tax implications, warehousing costs, and many others. Future demand can also be predicted so that you have all the information you need to come up with the most efficient possible approach. 

4. Make more informed decisions

Follow our previous point, machine learning in eCommerce is an extremely useful tool for making informed decisions. It lets you know whether you should adopt drop shipping, whether your customers are interested in a new product line, and many questions like that.

Machine learning in eCommerce can help you with all the concerns you may have by providing all the data you need to consider before making any decision. 

5 Amazing Applications of Machine Learning in eCommerce

We’ve talked about the advantages of machine learning in eCommerce, now you may want to get to know more about how to use it in your industry. 

1. Personalization

Today customers don’t want to get treated the same as every other customer, they prefer to have a highly personalized shopping experience to enjoy. That kind of personalization can make people love your brand and become your loyal customers.

But why should you use machine learning for making personalized features? It’s because AI, and machine specifically, is the only way to create a high level of personalization online. 

Using algorithms allows customer data and behavior to be analyzed and to boost the user experiences. Thanks to them, your site can show product recommendations that are suitable for each user. Undoubtedly, such a recommendation is an excellent way to bring highly personalized experiences for different customers. In fact, this method has been utilized worldwide by remarkably successful brands such as Netflix and Amazon. 

2. Site search

Many visitors coming to your online store may already have an idea of what they need in mind and what they are unsure of is the exact name of the product or even don’t know what items can meet their needs. That’s why you need your site search to be smart enough to present the right solution for visitors regardless of what is typed in the search bar. 

For instance, when a visitor goes to Camelbak’s website, they might want to find something to help them stay hydrated easily while hiking and simply enter “Hiking” in the search bar of the site. 

And what’s great is an intelligent search powered by machine learning in eCommerce can handle that in a second. You can see from the picture above that it produced highly relevant results for that specific search text, with all products are packs designed for hiking. 

3. Managing supply and demand

Like any other area of business, eCommerce is also about supply and demand. As an online retailer, you need to make sure you get the right stock in the correct quantities to satisfy your customer’s demand. 

Those demands will change over time but being able to predict the customer needs can help you stay ahead of the fierce competition out there. 

Machine learning gives you real-time and accurate predictions to manage your supply chain. Balancing customer demand, expenses and logistics is how to get ahead in the game. 

By using an AI-powered algorithm, you can crunch all the relevant numbers with ease and as a result, the inventory and supply chain you prepare to respond will bring success to your online business. 

4. Fraud protection

In this day and age, if you think eCommerce fraud should be considered a thing of the past, you may be wrong. Despite the growing cybersecurity awareness, the value lost to fraud that retailers have to experience is going up steadily. 

Therefore, fraud detection and fraud protection are still more essential factors for all online store owners than ever. 

To solve that problem, machine learning algorithms will process the sheer volume of data and analyze them. To put it more simply, they would pinpoint the hallmarks of an actual purchase or notify you of a transaction that diverges immediately. Plus, payment comes from an unusual location or device, the purchase may also get flagged up as potentially fraudulent. 

5. Improved customer service

All businesses understand the significance of customer service but how to make a premium customer service is still unclear. A simple way to improve your customer service is to offer 24/7, omnichannel support but we all know it’s even hard for the largest brands to do so. 

Fortunately, that problem now can be easily dealt with by AI and machine learning. Many companies today seek to boost customer satisfaction that way and among them, chatbot seems to be the most outstanding example of machine learning in eCommerce. 

Magento 2 Facebook Chatbot allows shop owners to build smart and automated communication between them and their customers. This extremely useful tool not only helps engage customers through fast response but also cuts down support time and promotes marketing campaigns with timely notifications via Messenger - the most popular messaging app. 

Conclusion

Before it’s hard to imagine machines that could replace humans in everyday tasks, but now it’s very common to talk to a robot and get efficient support from it. Machine learning and many other processes driven by AI are ubiquitous and pretty much a part of everyday life. 

Their growing usage has seen no stop sign and you will surely get left behind if you cannot keep up-to-date with the trend and take proper actions. 

The benefits of machine learning in eCommerce are numerous from customer experience to inventory management. We are on a mission to offer marketing and sales tips that help businesses grow rapidly. If you want more insights like this, visit our store blogs to discover more tricks and industry-leading knowledge.