Predictive behavioral targeting

From Seo Wiki - Search Engine Optimization and Programming Languages

Jump to: navigation, search

Predictive behavioral targeting uses a linking of surveys and measurement data to open up the entire spectrum for behavioral targeting. The Predictive Behavioral Targeting system learns from user behavior combined with survey or other third party data in real time. Machine-learning algorithms are put to work in order to provide ad servers with precise profile information for the whole inventory. The technology used is the same as in research on artificial intelligence and robotics.


The methodology is based on measurement data for online usage, enriched with information gathered through a survey of sampled users. In a nutshell, the methodology encompasses three steps:

  1. Cookies are saved on the computers of all users of a portal or marketing network. These cookies indicate how often the users have visited certain websites (measurement).
  2. A random sample of users is polled on their demographics, interests and lifestyle (surveys).
  3. This information is overlaid - online and in real time - onto the entirety of the user group (projection).

This process provides a complete targeting profile containing both product interests on the basis of visited online content as well as indications of demographics, interests and lifestyle. Survey data is projected onto the entirety of users by forming "statistical twins": Users without survey data "inherit" the missing survey data from those surveyed users whose measured surfing behavior most closely resembles their own.


Predictive Behavioral Targeting is made possible through a technological system that analyzes and enhances user data online and in real time. Blind gifs are used to count the number of page hits per cookie and content page code. Additionally, random users are invited at certain intervals to take part in on-site surveys, providing information on the user's demographics, interests and lifestyle. This polling data is then overlaid onto the measurement data, allowing for a profile comparison. The profile will then be delivered to portal operators and their ad servers, who can then send out ads to the previously defined target group.

Personal tools

Served in 0.124 secs.