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Page 29 of 73
 
Look-Alike Modeling

Look-alike modeling allows marketers to target individuals who "look like" their preferred audience. It finds consumers who exhibit similar online patterns to those consumers who have already demonstrated a desired behavior, or who have already generated a conversion on their site. A conversion is a marketing goal, such as a purchase, a completed form, or downloaded content.

Websites and networks first build the data used in behavioral targeting, then use an algorithm to compute how similar an individual's online behavior is to the behaviors of other consumers who have already converted to target that individual appropriately. For example, when a marketer purchases look-alike modeling media on an ad network, the ad network will track individuals who have converted and follow them around the web. With its tracking and algorithm, it may see that sixty percent of conversions are from people who visit sports sites and live in New England. The ad network will then begin targeting other users who visit sports sites and live in New England because it has deduced that this is the look-alike audience.

Audience Targeting

Audience targeting is a combination of targeting tactics rolled up into one line item within a media buy: behavioral, retargeting, contextual targeting, and demographic and geographic targeting. It is purchased from ad networks or DSPs and used to help marketers meet a specific goal. Instead of manually reallocating funds from one line item to another when optimizing a campaign, audience targeting allows ad networks and DSPs to automatically shift, in real-time, to whichever targeting tactic is driving the most conversions (i.e. clicks, sales, form completions, or downloads).

Page 29 of 73
 

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