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Recommendation systems: The smart revolution

Have you ever thouguht what happens when you choose a restaurant online, when you make a purchase on Amazon, or when you book a car with Uber or Cabify?

Ladorian would like to take a closer look at how the different artificial intelligence recommendation systems used by technology platforms such as Netflix, Amazon, Spotify or Uber work.

For example, did you know that 91% of consumers are more likely to buy brands that use omnichannel as a sales strategy and offer them relevant recommendations?

Well, that’s nothing… Read on!

Artificial Intelligence Recommendation Systems

As we commented in our article: Artificial Intelligence: The future of physical business, we currently live in a world overloaded with information. An environment full of excesses in which users have developed by themselves a defence system known as “advertising immunity”.

There are so many options for surfing the Internet that users are no longer satisfied with a simple directory or search engine.

The human brain is not able to process and understand the sheer volume of information it has access to on a daily basis. This is the reason because of users seeking advice in the digital world in order to discover new possibilities and trends.

Also known as recommender systems, artificial intelligence (AI)-based recommender systems simplify the task of user selection,improving the user’s shopping experience (UX) and perception of your brand.

Currently, artificial recommendation systems are increasingly present, being responsible for displaying related content on entertainment platforms, similar products in online shops, advertisements adapted to our tastes on social networks and even personalised content at the point of sale through smart content.

All this is not surprising, as numerous studies in the retail sector reveal that display is the most widely used global advertising strategy in the world.

The reason? Product and/or service recommendation ads are more appealing to consumers, driving conversion at the point of sale.

The more refined the recommendation model, data control and machine learning mastery, the greater the effectiveness.

But… how does the recommender system work?

Quite simply! By means of sophisticated algorithms capable of learning about our tastes and past actions. In other words, they create a pattern of choices based on the interaction of users on a given portal in order to suggest content of interest to us.

Artificial intelligence (AI), through machine learning and data processing, makes it possible to create these algorithms that replicate the logic of people before making a decision.

In the true life, this would be like asking an acquaintance with whom you share tastes or hobbies.

The big difference in digital recommendation systems is that instead of asking several trusted people, artificial intelligence allows us to make such a large number of queries that it would be the equivalent of asking all the like-minded people in a city about a subject…

Types of recommendation systems using AI

Within the recommendation systems we can find three main models:

Content-based recommenders: This system finds the similarities between two products to advise the user of related items with very similar characteristics.

Interaction-based: With this recommendation system, the system does not need to know the specifications of the products.

It focuses on the interactions that users make on the platform, executing automatic predictions considering the interactions of similar users.

Hybrid systems: This is a combination of the two previous systems. The most prominent examples of this system would be the entertainment platform Netflix or Amazon.

Recommendation System for Retailers

At Ladorian we are absolutely committed to revolutionise sales at the retails through data analysis and artificial intelligence.

Collected the business customer data may create a customised recommendation system and design a good customer experience thanks to advanced artificial intelligence platforms.

Thanks to Intelligent Content Platforms at the point of sale we can design a personalised recommendation system with real-time information.

Ladorian has developed its own Intelligent Content Distribution Platform: LADORIAN IDS庐 . Its implementation at the point-of-sale helps to generate indexes with an increase of up to 30% of the sales of retails.

Instore Smart Media strategies improves the customer experience at the point of sale and boost impulse purchases by taking advantage of the synergy generated.

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