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predictive personalization

Contributor(s): Matthew Haughn

Predictive personalization is the effort and ability to predict the actions of users, based on their previous behaviors online. In general, personalization is the process of tailoring website content to suit the characteristics or preferences of individual users. The practice is commonly used for online marketing but may also be used to present information and news items that the user is likely to be interested in.

Eliciting desired behaviors from users has always been the intention of such efforts, both online and off. Predictive personalization takes the concept one step further, however, applying information about the user’s past interactions to guide the presentation of content that has a better probability of eliciting desired behaviors from them. One of the main differences is the huge increase in the amount of user data that is being generated and gathered, often without the user's knowledge or explicit consent.

For predictive personalization, the data collected from behavior exhibited in online sessions is analyzed. Such data includes the amount of time spent on different sites and pages, items added to shopping carts, purchases, forms that are filled out, searches run and social media interactions. The data can all be used to predict the actions of users and thereby place ads and content more apt to elicit desired behaviors such as making purchases or sharing content.

Although some survey respondents say they don't mind being tracked as long as they gain something from the monitoring, people typically don’t like noticing that they are being tracked. The presence of  highly targeted ads can make a user feel eerily watched and inspire distrust in any associated site, product or brand. Similarly, there’s a fine line between persuasive and manipulative design. User experience (UX) experts warn that any benefits gained from tricking or misleading users are likely to be short-lived.

 See also: predictive modeling, implied consent

This was last updated in September 2016

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