Artificial intelligence is an innovative tool that is applied in many areas to achieve great benefits. In the form of machine learning, it can help increase the growth and the satisfaction of the customers of an ecommerce.
How has machine learning affected the evolution of ecommerce? In what aspect of ecommerce does machine learning benefit? How does this affect the customers of those stores?
Artificial Intelligence is a concept that is currently in vogue and that little by little will continue to grow and discover new applications to benefit us in any aspect of our lives. The objective with artificial intelligence is to replace human beings by imitating their cognitive functions.
As a result of artificial intelligence, other concepts arise that, for not being subordinated, implies an inferiority relationship. This is the case of machine learning (machine or automatic learning), which refers to the capacity of artificial intelligence to learn as it receives and processes data through algorithms.
Machine learning opens up endless possibilities in a great variety of disciplines and many of them probably we don’t even know them yet. Even so, focusing on the present, there are already many applications of this technology, which has made possible a positive evolution of ecommerce.
What are the advantages of machine learning for the evolution of ecommerce?
The purchase made by a person allows knowing many things about him/her. This information is very valuable for any trade because you can analyze them and offer an improved service for your client.
This data analysis is translated, first, into an improvement in the ecommerce search. When the customer types something in the search field, a series of suggestions appear automatically that can help to find the desired product more quickly.
Thanks to machine learning, more relevant search results are achieved, which makes it much easier for the desired purchase to be made and for it to be satisfactory to the customer. What he/ wanted to buy he found as easily as possible.
As we said, the purchases allow you to create profiles and know much better the customers who buy in your store. With these defined profiles, the marketing department has a higher quality base material to work on. The actions to reach the different targets will be more personalized, with the consequent satisfaction of the client, who will receive offers and other types of actions based on their needs.
By getting together the data and the profiles of several users and with the help of machine learning, you also get another option that benefits the customer and makes your life as a buyer easier, which are the suggestions. Artificial intelligence analyzes the purchases made by the user and others with similar tastes and suggests other products that are complementary.
According to Amazon statistics, its recommendation engine is responsible for 35% of its sales, which demonstrates the importance of machine learning and the benefits its use brings to electronic business.
The price of the products is also another key factor to convince customers when making the purchase. Different variables are included in the price that affect its final result, which makes it difficult (almost impossible) for a human being to dedicate himself to this task. The processing capacity of computers makes this a perfect task for them.
Thanks to machine learning, a series of factors can be introduced for the program to take it into consideration and act based on them, such as the prices of the competition, the demand, the time of day or the type of consumer. A good optimization will achieve a greater volume of purchases.
Stock management is also important, because if there are no products to sell, the store demands don’t matter. Machine learning allows analyzing the sales made of all products and predicting when it will be necessary to buy more stocks. Analyzes of artificial intelligence are much more complete and the more information it has over a longer period of time, it will be able to predict trends better.
The difference between electronic commerce and a physical one, among many others, is that nobody is next to the client who can advise him/her or solve any doubts he/she may have. Through machine learning, this can be changed without having to spend too much on a staff team that can serve all the users that enter the page.
Machine learning allows having bots as customer service workers in the electronic commerce. So, any doubt that a customer has can open a conversation with the bot, ask him/her and he/she will solve it without needing to have someone pending of this service. A quick and satisfactory service helps to have a happier customer and possibly complete a purchase.
Machine learning also in physical business
Moreover, machine learning can make the leap to physical stores combined with other techniques such as location intelligence in closed environments, which is known as indoor mapping.
Indoor mapping adds a new perspective to the data that is obtained: the location. Knowing where and when certain events take place, you can act consistently to debug certain problems. The machine learning allows analyzing all this information and processing it.
Geographica Success Case: Drivethrurpg
Geographica has developed an intelligent system for OneBookShelf, a digital content company in the United States with different online stores specialized in the entertainment industry and more than 500,000 users. In their continuous desire for growth and innovation, they opted to collaborate with Geographica.
The work consisted of the development of a recommendations system for the users that were able to learn from the past purchases and thus make suggestions more according to their tastes, thus increasing the possibilities of sale.
Definitely, machine learning has helped, is helping and will continue to help in many aspects to ecommerce (and even the physical, in combination with location intelligence), which affects positively the benefit of the owner and customer satisfaction.
The customer will have a more efficient service and will be able to find what they are looking for more quickly and discover suggestions that help them discover new products that interest them, while the shop owner has a quantity of important information analyzed and processed to act accordingly.