Personalized Advertising Task

From GM-RKB
Jump to navigation Jump to search

A Personalized Advertising Task is an advertising task that attempts to tailor advertisments to prospect characteristics.



References

2013

  • (Wikipedia, 2013) ⇒ http://en.wikipedia.org/wiki/Targeted_advertising Retrieved:2013-12-1.
    • Targeted advertising is a type of advertising whereby advertisements are placed so as to reach consumers based on various traits such as demographics, psychographics, behavioral variables (such as product purchase history), and firmographic variables … or other second-order activities which serve as a proxy for these traits.

      Most targeted new media advertising currently uses second-order proxies for targeting, such as tracking online or mobile web activities of consumers, associating historical webpage consumer demographics with new consumer web page access, using a search word as the basis for implied interest, or contextual advertising.

      Addressable advertising systems serve ads directly based on demographic, psychographic, or behavioral attributes associated with the consumer(s) exposed to the ad. These systems are always digital and must be addressable in that the end point which serves the ad (set-top box, website, or digital sign) must be capable of rendering an ad independently of any other end points based on consumer attributes specific to that end point at the time the ad is served. Addressable advertising systems therefore must use consumer traits associated with the end points as the basis for selecting and serving ads.


  • (Wikipedia, 2013) ⇒ http://en.wikipedia.org/wiki/Targeted_advertising#The_process Retrieved:2013-12-1.
    • Advertisers want to reach as many consumers as efficiently as possible. This requires an understanding of how customers' minds work. [1][dead link] Behavioral targeting is the most common targeting method used online. Behavioral targeting works by anonymously monitoring and tracking the content read and sites visited by a user or IP when that user surfs on the Internet. This is done by serving tracking codes. Sites visited, content viewed, and length of visit are databased to predict an online behavioral pattern. [2] A further refinement to behavioral targeting is Predictive Behavioral Targeting, where machine learning algorithms overlay behavioral patterns with sampled data, to create data-rich predicted profiles for every user. Alternatives to behavioral advertising include audience targeting, contextual targeting, and psychographic [3] targeting.