Abstract: An online system evaluates the quality of a content publisher displaying sponsored content items. To determine a likelihood of conversion actions associated with the sponsored content items, the online system uses information about users and their interactions with sponsored content items featured within the content publisher against interactions with sponsored content items featured within a benchmark system (e.g., online system). By determining a ratio of these interactions, the online system can determine a likelihood of conversion actions for the content publisher. The online system uses this likelihood of conversions to determine a publisher quality score that it uses to normalize third party value contributions toward placing sponsored content items on the content publisher. Thus, third party systems no longer need to be concerned about the intrinsic value of a given content publisher as third party value contributions are normalized based on the content publisher's conversion rates.

Abstract: An online system evaluates the quality of a content publisher displaying sponsored content items. To determine a likelihood of conversion actions associated with the sponsored content items, the online system uses information about users and their interactions with sponsored content items featured within the content publisher against interactions with sponsored content items featured within a benchmark system (e.g., online system). By determining a ratio of these interactions, the online system can determine a likelihood of conversion actions for the content publisher. The online system uses this likelihood of conversions to determine a publisher quality score that it uses to normalize third party value contributions toward placing sponsored content items on the content publisher. Thus, third party systems no longer need to be concerned about the intrinsic value of a given content publisher as third party value contributions are normalized based on the content publisher's conversion rates.

Abstract: An online system evaluates the efficacy of one or more content placement slots within a content publisher in a publisher's page layout. To evaluate the efficacy of the content slot, the conversion rate at the slot and in a benchmark for selected content items published at the slot is identified to determine the ratio of conversions at the publisher slot and in the benchmark. For different content items, these conversion ratios may vary, and may further be weighed by a value contribution for each content item. Thus, to determine the value of the conversion ratios for a given publisher, the online system uses information about online system users and their interactions with third party content featured within different locations, or placements, within the publisher's page layout. The arrangement of slots in relation to one another can be manipulated by the publisher to yield optimal conversion rates for featured slots.

Abstract: An online system presents advertisements itself and provides advertisements to third party systems. To mitigate different amounts interactions performed by users presented with advertisements via the online system or presented via a third party system, the online system modifies bid amounts associated with advertisements based on a difference in a number of interactions performed by users presented with advertisements via the online system and a number of interactions performed by users presented with advertisements via a third party system. Based on the difference in interactions performed by users presented with advertisements via the online system and via the third party system, the online system modifies bid amounts associated with advertisements. When the third party system requests an advertisement from the online system, the online system selects an advertisement for the third party system using the modified bid amounts.