Artificial Intelligence In The E-shop
Artificial intelligence (artificial intelligence – AI) enables devices or systems to solve various tasks without needing constant user (human) intervention. He improves his output thanks to the ability to learn from real experiences.
What is machine learning, and where do we encounter it everywhere?
If, until now, you thought that the acronym AI hides a perfect robot that takes on human characteristics, the truth is a mile away. Although science fiction has taken many movie and book subjects from this industry, the truth is still much more prosaic. And it will probably stay for a long time.
Artificial intelligence, or rather the field of this scientific discipline, called machine learning, simplifies and makes our life more pleasant in many areas already today. Machine learning has seen development in recent years, thanks to deep learning.
It is based on neural networks, to which two other significant technological factors have been added. More powerful computers and fast graphics cards (graphical processor unit – GPU) are increasingly affordable even for the general public.
What do Amazon, YouTube, Netflix, and AI have in common?
The big players quickly understood how artificial intelligence could amplify the importance of personalized content. Thanks to its outputs, they can show a certain landing page to user A and a completely different one to user B. Of course, one that best matches his search queries.
A recommendation system that works based on real data
We encounter recommended products, services, or content on many sites today. However, websites often struggle with their quality, availability, or price. Until now, only big e-commerce players have been able to create their recommendation system that would show the likely user outputs that interest them.
But the breakthrough comes precisely with the development of machine learning. Neural networks can process the amount of data generated on the page. The result is recommended content (product, service, video, image…) without the user logging in or entering any information about himself into the system. Because…
It is not data as data. In the case of machine learning, quantity plays the biggest role
A neural network recommendation system doesn’t need to know who you are to recommend a book you’d probably like to read. Not even what literature you prefer, what books you bought last time, and who is your favourite author. Nevertheless, it recommends a relevant product that interests you.
Thus, data also plays an important role in deploying artificial intelligence. However, they are anonymous, and the most important thing is their quantity. Thanks to it, the system can predict the website visitor’s behaviour regardless of his registration or the type of data he provided in a form. To give you an idea – we are talking about millions of user interactions.
Until now, many e-commerce projects relied on the limits of recommendation tools that were programmed according to certain rules. However, they often encountered moments when one thing could be labeled with several names.
Just imagine how many different shades of blue you know. Finding out and then assigning a t-shirt flag, which could be dark blue, inky, ultramarine, cobalt, aquamarine, or simply blue, would probably take a long time. The more options there are, the less likely the recommender will show the user relevant products.