Personalization involves using technology to accommodate the differences between individuals. Once confined mainly to the Web, it is increasingly becoming a factor in education, healthcare (i.e. personalized medicine), and both "business to business" and "business to consumer" settings.

Web pages

Web pages are personalized based on the characteristics (interests, social category, context, ...) of an individual. Personalization implies that the changes are based on implicit data, such as items purchased or pages viewed. The term customization is used instead when the site only uses explicit data such as ratings or preferences.

On an intranet or B2E Enterprise Web portals, personalization is often based on user attributes such as department, functional area, or role. The term customization in this context refers to the ability of users to modify the page layout or specify what content should be displayed.

There are two categories of personalizations:

1. Rule-based
2. Content-based

Web personalization models include rules-based filtering, based on "if this, then that" rules processing, and collaborative filtering, which serves relevant material to customers by combining their own personal preferences with the preferences of like-minded others. Collaborative filtering works well for books, music, video, etc. However, it does not work well for a number of categories such as apparel, jewelry, cosmetics, etc. Recently, another method, Prediction Based on Benefit is proposed for products with complex attributes such as apparel.

There are three broad methods of personalizations:

1. Implicit
2. Explicit
3. Hybrid

Implicit & Explicit methods deal with gathering information about the user. Implicit personalization deals with gathering user information without asking the user for this and that. Explicit personalization on the other hand usually is done by asking the user to rate existing / changed things, filling up forms, clicking radio buttons, etc. Hybrid personalization combines the above two approaches for leverage best of both worlds.

Many companies offer services for web recommendation and email recommendation that are based on personalization or anonymously collected user behaviors.

Web personalization is closely linked to the notion of Adaptive hypermedia (AH). The main difference is that the former would usually work on what is considered an Open Corpus Hypermedia, whilst the latter would traditionally work on Closed Corpus Hypermedia. However, recent research directions in the AH domain take both closed and open corpus into account. Thus, the two fields are closely inter-related.

Personalisation is also being considered for use in less overtly commercial applications to improve the user experience online .

Search engines