Each week, DataWorks defines a data-related term marketers need to know. Last week we looked at Algorithms.

Look-Alike Models are used to build larger audiences from smaller audience segments to create reach for advertisers. In theory, they reflect similar characteristics to a benchmark set of characteristics the original audience segment represents, such as in-market kitchen-appliance shoppers. Generally, the higher the marketer's tolerance for loosening the model, the larger the segment can become.

Theresa LaMontagne, managing partner, senior practice lead, MEC Analytics & Insight, on Look-Alike Models and Audience Targeting:

"Beginning in the mid-'90s behavioral or audience targeting began to really take off. In the last 10 years the industry has continued to grow rapidly with more and more companies getting into the business of selling, acquiring or merging data for the targeting of advertising. While historically this has been an online-only phenomenon, the continued rapid growth of tablets and addressable TV is resulting in the digitization of other mediums which will spread audience targeting across screens.

Unfortunately, buyers are limited in their ability to reliably gauge the quality of the underlying data such as quality and accuracy of the underlying targeting source data [and the] definition of the data sources used including the size and age of the underlying data set. [Marketers also need] audited assurances and standards to ensure consumer privacy is not being violated, and full disclosure of methods including the validity of the underlying predictive models."