Personalization has become a common feature in modern digital products. Recommendation feeds, saved preferences, customized home pages, and suggested content are increasingly powered by artificial intelligence.
When designed well, personalization can reduce search effort and make large content libraries easier to navigate.
When designed poorly, it can become repetitive, intrusive, or difficult for users to control.
AI personalization uses data and machine learning to adapt the digital experience to user preferences or behavior.
Examples include:
The goal should be to make the product more useful, not to manipulate user behavior.
Personalization can use two types of signals.
These are preferences users intentionally provide.
Examples include: