Machine learning and artificial intelligence have in one way or the other, immensely contributed to bringing e-commerce to a value of
$2.3 trillion in the market. Machine learning brought a revolution in the said field by helping merchants better analyse their businesses’ fall and rise. Its main purpose is to help learn the insider information, and the psyche and temperament of each individual, so to offer effective and more precise solutions to a specific query. The magnificence of its functionality lies in its ability to be remarkably aware of what the client wants, when and in what quantity. Without human support, it employs algorithms and collective data and successfully yields results that elaborate on the clients’ requirements. With that said, given the significance of such information in the field of E-Commerce, businesses have gained better results, increased outreach, and growth.
Significance of Machine Learning
Machine learning cuts down a huge sum of guesswork and manual labor that previously businesses had to struggle with in order to push their results. It simply penetrates the viewers’ mind to gain information about what they like/dislike, what they might like/dislike and what lies in their subconscious that they themselves are unaware of. It hoards the data from profiles and a customer’s purchasing habits, also known as data mining, and through that makes deductions in order to build a potential sale, which comes as the result of merging the likes/dislikes and general human behaviors on the internet.
What makes it different?
It overlooks generalizations and characterizations based on a group of people, rather it values each individual and treats them in the same way. This is why it is not difficult for this technology to greet new customers and learn how to handle them.
Effects of Machine Learning in E-commerce
People may often wonder how the technology evolved so incredibly in such a short time that the latest systems became mysteriously aware of whatever went through the viewers’ mind. Technological advancement is certainly one of the reasons behind the invention of such tools but what aided in the process was the quest of e-commerce to transcend time and space. Machine learning is inherently built to depict the future needs of the customer base. E-commerce has been around for far too long to surprise us with such advancements. According to
research, retail e-commerce of the year 2017 hit around $2.29 trillion and was expected to rise up to $2.774 trillion by the end of 2018 and so it did; it neared $3 trillion. It means we can say it is expected to grow by a percentage of twenty every year. Mobile Phone devices are contributing by the percentage of 70 in bringing traffic to the arena of e-commerce. There is no doubt everyone now has a smartphone and/or tablet to access all applications, retailers – anything of their need. In short, quite many technologies have contributed to pushing e-commerce industry into an upward spiral over the years.
Impacts of AI and AR/VR on Customer-base
It is estimated by the year 2020, artificial intelligence will handle most customer interactions. It is more reliable and much more efficient than relying on the human force to drive results when artificial intelligence can conduct all tasks without any errors. In the same way, augmented or virtual reality have a great scope in online shopping stores, whether they are related to cosmetics, fashion, machines or furniture manufacturing companies – it is expected to have
$120 billion revenue generated through augmented reality. What would be enforcing these technologies? Of course, machine learning. There is no better analytical tool than this to derive the unearthed desires of people from every class, creed, culture, religion or country.
So, you might ask:
What does the Future of e-commerce hold?
Whether you are a customer or a retailer, you need an idea to fulfill the purpose of your existence. On one hand, it is to serve and on the other, it is to be served. If you are a retailer, you need to think like a customer to know exactly what they need and how much they need it. This is called knowing the customer’s experience. It starts from having the need to getting something resolved to developing feedback/opinion on it. Being the retailer, you have to relax your customer in each of the phases so they can come back to indulge more in your products/services. For example, if you are an internet service provider and, let’s say, you have to sell
Spectrum bundle deals, you need to make sure you are easing your customers in each of the steps from purchasing to experiencing your services or using your products. The more personalized the offers you make to your customer, the better the response. This is the reason you have constructed a considerate campaign to give your customers a valuable experience. 73% of the customers are tired of watching or scrolling through irrelevant content on social media or other platforms. Machine learning is designed to save their time by bringing forth only the offers that they cannot refuse—that they ardently desire or desperately need.
Customized Search Results and Customer Services
Machine learning will also aid the retailers in reducing their customer service issues long before they become noticeable. Situations like the abandonment of carts, disinterested surfing or incomplete surveying of your services can be reduced once machine learning is brought to your business. Consumers will have customer service bots to understand their needs in order to offer them unbiased solutions any time one is required.
The next big step covered by machine learning is improving the search results. This time it would not be just about knowing through prior experiences. There is a leap of development in this area. Now computers can tell even what you don’t know you want. The more data you have on the internet with your presence there, the better the analysis drawn regarding your choices and needs. eBay is one of those companies that is smartly using artificial intelligence to enlist all 800 items from its store to its customers in the rightfully manipulative way. What it brings before its customers are the relevant search results; thus, making their audience satisfied in the most considerate manner.
Thus, we can say machine learning plays a great role in understanding the customers’ needs through their in-store behavior, online presence and searching history. It makes sure there is no space left for an error or a hindrance that may hold back generation of higher revenue in the field of e-commerce for years to come.