Cases of success of artificial intelligence in e-commerce

Image search to offer the perfect product 

A priori an unremarkable element but they no longer doubt in using e-commerce of very global brands like Inditex.  Image search has become popularized in the last few years thanks to API Cloud Vision de Google, that allows for similar image search to the proposal of a user and knowing where they are hosted.

This similar search system functions through key point recognition within the image, very close to how facial recognition biometrics have been popularized today. With the help of these parameters, the systems uses artificial intelligence to find similar results. 

In e-Commerce this has evolved to the possibility of recognizing these parameters to find the same product or a similar product to the photo taken by the user. If it is from the same store (like in the case of Zara), the application will show the desired product, similar garments (if the stylistic bug is very large, like in a white shirt) or including a new proposal before an image that is not recognized as its own.

Machine learning in the shopping experience and the customer journey 

Getting to know the customer journey of your users in fundamental for understanding their motivations before buying, the moment when one finds themselves and the necessities that it can have. From this point, the machine learning sheds light on carrying out predictions for the following step that the client will take. 

The Amazon machine learning algorithm complies with this objective. In what way? Being capable of proposing to users their next purchase in function of their history and buyers that share theirs likes and needs with it. This is already implemented to all the house products of Jeff Bezos, like the device Alexa, that brings with it a great search precision and proposal of content thanks to deep learning. 

In the same way, Tealeaf was a tool that IBM now has professionalized even more and that allows for getting to know what the navigation of the user within your e-commerce is and understand their interaction with the different elements of your online store. Therefore it is possible to identify the strong points of the site, as well as the leaks and parcels that are least optimized that can make you lose sales.

The shopping experience, without a doubt, is enhanced by user purchase satisfaction. A clear example that is repeated in all analyzed success cases: the Dutch website  Decathlon that obtained a conversion rate of 5.2%, after adding recommended personalized products to their users.  

Dynamic prices with artificial intelligence 

This is, without a doubt, the strong leg of software businesses like Reactev. In this case, the objective of the artificial intelligence application is to understand the price changes in the market, in function of price fluctuations of the competition, as well as the levels of supply and demand. 

Thanks to that knowledge it is possible to predict changes in user behavior, waves of purchases or a dry season due to low trend. This prediction and price optimization system is used on the behalf of all the large marketplaces like Alibaba and Amazon, as well as consumables that work with dynamic pricing strategies. 

And what profit supposes to use artificial intelligence in your pricing strategy? Not losing sales opportunities + obtaining the maximum margin at any moment. 

In general, applying dynamic prices with artificial intelligence is a success case in and of itself. And it is carries advantages from the control and stock forecast until the painstaking calculation of the values of the profit margin obtained.