Abstract: Various embodiments pertain to techniques for forecasting and providing guaranteed delivery of ad impression opportunities using real-time bidded platform inventories. In various embodiments, bid landscape data, such as information regarding a number of impression requests by a particular supply unit, a time of the impression requests, and an amount of a winning bid for the impression requests, is recorded for use in forecasting an available impression volume as a function of cost. The forecasted available impression volume represents a number of ad impression requests likely to be obtained through real-time bidding channels. In various embodiments, an advertiser can place an order for a number of ad impressions at a particular price, and the ad impressions ordered can be specifically allocated for that advertiser. The number of ad impressions ordered by an advertiser that are guaranteed vary depending on the price and the available volume forecasted at that price.

Abstract: Systems and methods are provided for evaluating candidate orders relative to available inventory, such as evaluating candidate orders of advertising impressions relative to an estimated available inventor of advertising impressions. The evaluation can include matching orders with available inventors based on linear programs that include objective functions and constraints. At least one objective function can include multiple slack variables.

Abstract: Systems and method can be provided for selecting advertising payloads for display in an available advertising impression location. The advertising payloads can be selected based on an auction between various types of hosted and third party campaigns, including hosted reserved advertising campaigns and hosted non-reserved advertising campaigns. The rules of the auction can be set and/or updated over time to allow hosted campaigns to meet desired goals, such as delivering a minimum number of impressions or spending an expect budget amount.

Abstract: Computer-readable media for determining whether to accept a candidate order from a content provider, or advertiser, to display a particular number of advertisements within a specified time segment are provided. Initially, the content provider may include placement criteria that, among other things, identify a leaf node at which impressions of the advertisement are expected to be rendered. Generally, the leaf node refers to a location within a topic graph that describes inventory that is permissible to allocate to satisfy the candidate order. To perform the determination, the inventory of impressions available for accommodating the candidate order and a log of booked orders scheduled to be placed within the time segment are identified. Linear programs are then utilized to determine whether the estimated inventory that satisfies the placement criteria is available by predictively placing the booked orders at the estimated inventory. If estimated inventory remains available, the candidate order is accepted.

Abstract: Computer-readable media for determining whether to accept a candidate order from an advertiser, to display a particular number of advertisements within a specified time segment are provided. Initially, the content provider may include placement criteria that, among other things, identify a leaf supply node at which impressions of the advertisement are expected to be rendered. Generally, the leaf supply node refers to a location within a topic graph that describes inventory that is permissible to allocate to satisfy the candidate order. To perform the determination, the inventory of impressions available for accommodating the candidate order and a log of booked orders scheduled to be placed within the time segment are identified. Linear programs are then utilized to determine whether the estimated inventory that satisfies the placement criteria is available by predictively placing the booked orders at the estimated inventory. If estimated inventory remains available, the candidate order is accepted.

Abstract: Computer-readable media for determining whether to accept a candidate order from a content provider, or advertiser, to display a particular number of advertisements within a specified time segment are provided. Initially, the content provider may include placement criteria that, among other things, identify a leaf node at which impressions of the advertisement are expected to be rendered. Generally, the leaf node refers to a location within a topic graph that describes inventory that is permissible to allocate to satisfy the candidate order. To perform the determination, the inventory of impressions available for accommodating the candidate order and a log of booked orders scheduled to be placed within the time segment are identified. Linear programs are then utilized to determine whether the estimated inventory that satisfies the placement criteria is available by predictively placing the booked orders at the estimated inventory. If estimated inventory remains available, the candidate order is accepted.