PROPENSITY-TO-CLICK TARGETING AND MODELING

In an embodiment of the present invention, two or more metrics may be measured from the group consisting of: the user's age, the user's gender, the user's race, the user's geographic location, the user's annual income, the user's profession, types of areas of the search engine that the user frequents, types of searches that the user typically conducts, and the user's prior history (short and/or long-term) of clicking on advertisements. A propensity-to-click score may then be calculated for the user based on the two or more measured metrics. Then this score may be used to dynamically determine how to present advertising in response to a search by the user.