Artificial intelligence (or AI) enables devices or systems to solve multiple tasks without the need for an interference from a user (human). Results from its work get better over time thanks to its ability to learn from real experience.
ui42 has always been a place with a vision, pioneering new ideas, and it is no different in the case of using artificial intelligence. Only recently, we have introduced our chatbot to the world but our most efficient brains are already looking into the possibility of using artificial intelligence to optimise online shops in Slovakia - and most importantly, to increase their conversion rate.
Would you like to know more?
Where can you find artificial intelligence or machine learning?
The idea of artificial intelligence being a perfect robot acting and looking like a human is - unfortunately - miles from the truth. Even though many of the craziest science fiction ideas have found their inspiration within the realm of artificial intelligence, the reality is a bit simpler. And this probably won’t change much for the foreseeable future.
Artificial intelligence, or a science discipline called machine learning, simplifies our lives and makes our lives more comfortable already today. Thanks to the method called deep learning, machine learning has seen big developments. Deep learning is based on neural networks and is supported by two important technological factors: more powerful computers and fast graphic cards (graphical processor unit − GPU), whose prices have made them accessible to the broad public.
What’s the result?
Try to google something using a picture. The search engine results will list not only the websites containing your picture but also websites containing pictures similar to yours. Google is, however, not the only one capable of turning this aspect of artificial intelligence into a higher conversion rate.
Amazon, YouTube and also much beloved Netflix display personalised content thanks to machine learning.
Big players understood the ways artificial intelligence can enlarge the importance of personalised content very quickly. Thanks to its outputs, they can display different landing pages to different users - and these, of course, would reflect users’ search criteria. For instance, Alibaba saw a 20% increase in conversion rate thanks to personalised websites. Amazon can thank personalisation for more than a third of its sales and Netflix for more than 75% of all its views. All backed by machine learning. How does it work?
Recommending system based on real data
These days, you come across recommended products, services or content on many websites. However, websites struggle with their quality, accessibility or price. It was only the big e-commerce players who were really interested in creating their own recommender system which would display only outputs their users would actually be interested in.
The tipping point comes with the dawn of machine learning development. Neural networks can process large amounts of data generated on websites and this results in recommended content (goods, services, video, picture,...) even if the users are not logged on or they haven’t entered any information into the system. Because...
Not all data were created equal. Quantity is good for machine learning
To recommend a book you would probably enjoy reading, the recommender system, consisting of neural threads, does not need to know who you are. It also does not need to know what type of literature you like, what was the last book you bought or who your favourite author is - and it is still able to recommend a relevant product that captures your attention.
Data plays an important part in implementing artificial intelligence. They are anonymous and the most important factor is their amount. Thanks to sheer amount of data, the system can correctly predict user’s behaviour regardless of their registration or information shared. To be clear - we are speaking of millions of user interactions.
Slovak online shops and artificial intelligence. Can we turn its potential into higher sales?
Up until recently, many e-commerce projects relied on limits that recommendation tools have, and these were programmed following certain rules. They used to encounter difficulties because you can use different names for the same thing.
Try to imagine all the hues of blue you can think of. To go through all these and then link them to a t-shirt that could be light-blue, dark-blue, navy, indigo, cerulean or simply blue would be a sisyphean task. The probability that your recommender system displays relevant results decreases with the increasing amount of options you have.
The solution to this problem is a recommendation tool which is able to create offers the users are likely to be interested in thanks to gathered data on users behaviour and other relevant information (price, discount, category and such).
Well, if you were wondering what was the hottest and most discussed topic behind ui42’s office walls, we offered a little insight. Our (humble:) ) goal is to implement artificial intelligence tools into online shops in our realms. In case you can’t wait to know how all this turned out and whether machine learning can increase conversion rates (sales, forms filling, interaction with content) even in your online shops, we will definitely let you know soon. Stay tuned!