Personalised recommendation systems are primarily found in e-commerce and digital retail, as well as in artificial intelligence, big data and smart data. They help to make the online shopping experience more individual and tailored for customers.
Imagine you're shopping for shoes online. The system remembers which products you click on and add to your basket. Based on this data, it suggests other shoes or complementary products that are likely to appeal to your taste. This isn't a coincidence: sophisticated algorithms are behind these recommendations, analysing the behaviour of many customers to make personalised suggestions.
Personalised recommendation systems help companies to better understand their customers, anticipate needs, and present suitable offers. In turn, customers benefit from finding products they are genuinely interested in more quickly. Well-known examples include recommendations on large online shops like Amazon or the „For You“ playlists on music services like Spotify. These systems are based on collected user data and artificial intelligence, in order to continuously improve the shopping experience and increase user satisfaction.
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