Why use an artificial intelligence recommendation system?
An artificial intelligence recommendation system uses intelligent algorithms to make recommendations. The two major differentials of these types of systems are the customization and automation.
Os recommendation systems are increasingly present in our lives. If you have already purchased at Amazon, watched Netflix or used the Facebook, for sure has already been impacted by one. And, in these three cases, the artificial intelligence is present.
In electronic commerce, these mechanisms are also quite popular inMany virtual stores use recommendation systems with artificial intelligence, as they facilitate the purchase dayimprove the user experience and, with that, raise the conversion rate. But some stores still don't use this technology in their systems.
We created this content to explain why you should use a recommendation system with artificial intelligence in your e-commerce, just like the big brands do. Check out!
Differentials of a recommendation system with artificial intelligence
The two major differences in the use of artificial intelligence (AI) in these types of systems are the customization and automation. Below, we explain in more detail how these features work and their importance for online stores.
But without the technology of a artificial intelligence, the effectiveness is not so great, as these systems respond only to fixed and linear rules.
Artificial intelligence, on the other hand, has nonlinearity as one of its main qualities. It uses nonlinear calculations to function as closely as possible to a human brain, smart algorithms.
Systems without AI, on the other hand, use simple mathematical algorithms, thus, the possibilities of recommendation become more predictable and limited, as they respond to a specific rule.
How it works in practice
Imagine that a customer is viewing a certain product, from that, the system without AI can directly search the database for all products that are in the same category as the one being viewed; with the same value range; and that are in stock.
From there, the system can order by higher discount, for example. This is the rule, this is fixed. For all the items that the customer searches for, there will be the same rule and you quickly find out which rule is returning those products.
To artificial intelligence there more possibilities, more paths beyond those already expected, because it uses the learning mechanism, through the machine learning ou machine learning. She uses the data to learn and then generate the recommendation, so the results can be surprising and unpredictable, but much more effective.
In a wine store, she can come to the conclusion alone, for example, that whoever buys a wine for 30 reais does not buy 1500, without having to create a rule for that. But she can also come to the conclusion that whoever buys a cabernet sauvignon also buys shiraz, even though they are quite different from each other.
This happens because, in that environment where AI learned, she realized that people do buy both wines. At least in that environment, since people are different and have different cultures and habits.
In a system without AI, where the rules have been pre-programmed by one person, the result will always be the same. While with a recommendation system with artificial intelligence, the results can be different and, therefore, very more assertive e more personalized than one that a person has placed according to their unique and exclusive expertise or that of a small group of people.
Personalization, shopping experience and artificial intelligence
In the video below, our CEO, Rodrigo Schiavini, explains the relationship between personalization, shopping experience and artificial intelligence. Watch and understand!
SmartHint's recommendation system uses artificial intelligence to personalize each consumer's shopping experience within virtual stores. Meet SmartHint!
Automation is also an important feature in a recommendation system with artificial intelligencebecause it does real-time analysis and not A / B testing, as with other systems. This greatly facilitates processes and optimizes staff time.
In the case of electronic commerce, this is reflected in the freestanding showcases, which work automatically. This happens, because the AI performs analyzes in real time and, with this, it is able to identify which storefronts are converting more, which are the best positions and which are the most relevant for each user.
In this way, the showcases are positioned on their own, reducing the need for configurations through human and manual work.
To learn more about standalone showcases, check out this post: Standalone virtual showcase: how to customize automatically.
As you saw, artificial intelligence makes all the difference in a recommendation system, personalizing and further elevating your customers' shopping experience, reducing costs and optimizing team work.
It is no wonder that the biggest success cases involving recommendation systems, such as Amazon and Netflix, use artificial intelligence.
Want to elevate your online store's shopping experience with a recommendation system based on artificial intelligence? Talk to us!