BACKGROUND

In the world of online advertising, an advertisers' goal is to find a new audience for their products. Indeed, while an advertiser will typically have a body of users to which they advertise, advertisers can grow their business and revenue by expanding that body of users to which they advertise.

Advertisers have many available controls to specify a target audience for an advertisement and/or advertisement campaign. Indeed, often an advertiser will filter its body of user data to identify certain users with specific interests, demographics, search keywords, and the like. This doesn't expand the audience for the advertiser, but allows the advertiser to access a specific, desired group of users.

A method an advertiser might use to target users for advertisements is a technique called “audience look-alike” targeting, which allows the advertiser to provide a set of its own high value customers to an advertising platform. The advertising platform, which has and maintains its own set of users, will then find similar users among its set of users, i.e., users that are similar to or “look like” the high value customers of the advertiser. Typically, the advertisement platform then directs the advertisements of the advertiser to that expanded group of “look-alike” users. This technique has the added benefit of reaching customers/users that are unknown to the advertiser.

In “look-alike” targeting, the advertiser is able to apply reasoning, metrics and logic that it knows about its own customer or client base when identifying the seed group of users for the advertising platform. However, for security purposes, this information and/or rationale is not conveyed to the advertising platform. As a result, the advertising platform is blind to any motivation the advertiser employed in selecting the seed group of users.

