How to sell more with artificial intelligence recommendation tools?

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How to sell more with artificial intelligence recommendation tools?

Selling more with artificial intelligence recommendation tools photo qaleon

In an increasingly digital and competitive market, it is necessary to evolve and adapt to the needs of customers and their buying patterns. The recommendation tools are becoming increasingly sophisticated and are able to suggest better products to potential customers, but many remain just basic cross-selling. In this article we will tell you all about these recommendation tools and what's new with artificial and predictive intelligence.

What is a recommender system?

A recommendation system or software for a business is a tool that connects different elements and patterns based on data and offers predictive recommendations with a sales objective. These tools are widely used by many e-commerce companies to encourage cross-selling and to make both cross-selling or up-selling.

The benefit of a referral system or tool is that it helps you scale sales. They create impacts to potential customers about products or services within the business space.

recommendation software is able to offer products that may be of interest to our shop visitors, for example, which increases sales. In addition, it is a less aggressive sales mechanism because it tries to offer the user products or services that are of interest to him.

Example of business with AI tools

The 21st century has seen the emergence of numerous technologies that are able to offer, through recommendation tools and depending on different variables, practical solutions.

One of these solutions could be Spotifywhich is able to cross-reference all the data of the songs you consume with the music market and offers you specific playlists for you with artificial intelligence. Also, once a playlist ends, it offers you related songs, in the same style as the one you were listening to, without the need to tell the system anything.

Another similar option is Netflix. Based on the series, documentaries or films that you watch or leave, Netflix knows what level of match an audiovisual product may have using its artificial intelligence.

Another exemple, is Linkedin which, through your profile, is able to recommend specific job offers for you based on your career, your chosen preferences, your location... The aim of these recommendation tools is to create better user experiences that help users.

What types of recommender systems are there?

There are different types of recommendation tools, four types based on different aspects:

  • Popularity: The system offers the most popular products bought by other users.
  • Relation: Here, in turn, there are three basic types of recommendation based on products or services and in relation to the user/visitor:
    • Relation user-product: based on the individual preferences of the users.
    • Relation user-user: based on similar people, i.e. people of similar age, background, etc., who are similar to each other, who are likely to have similar product preferences.
    • Relations product-product: based on similar or complementary products, e.g. printers and ink cartridges, which can be classified into relevant groups.
  • Content: The first one is the same as the previous one, but it is deeper when it comes to segmentation, because it is based on the characteristics of the products or services in relation to the user/visitor and not so much on the relationship between the products or services.
  • Hybrid: as its name suggests, it is a system that can be a mix of the previous ones to offer different options to users. This model would be the most complete because of its integration of all the information and data to be able to offer a much more refined benefit.

Product or service recommendation tool


It is a solution developed by Qaleon that offers through artificial intelligence an advanced recommendation of products beyond the basic recommendation of some e-commerce. With QeKiero you will be able to create personalised customer-centric experiences.