Abstract: The present teaching generally relates to identifying data bucket overlap with online experiments. In a non-limiting embodiment, first data representing a first set of identifiers associated with a first data bucket of a first online experiment may be obtained. Second data representing a second set of identifiers associated with a second data bucket of the first online experiment may be obtained. Based on the first data and the second data, a first number of identifiers that are associated with the first data bucket and the second data bucket may be determined. In response to determining that the first number exceeds a threshold, a data flag indicating that results associated with the first online experiment are inconsistent may be generated.

Abstract: One or more methods and/or techniques for content resource allocation are provided herein. A user, of a client device, may access content. Real time user traffic associated with accessing the content may be determined. A trend may be identified from the real time user traffic for the content. The real time user traffic may be indicative of an amount of the content distribution resources used to provide a threshold level of service to users. Responsive to the trend indicating a projected increase in real time user traffic for the content, the content distribution resources may be allocated to the content based upon the projected increase, such that the allocated content distribution resources provide the threshold level of service to the user.

Abstract: As provided herein, a primary content provider (e.g., a book retailer) may present a campaign for a product (e.g., a novel), comprising non-published content and a keyword (e.g., the novel title), to a permitted content provider (e.g., the publisher of the novel). The permitted content provider may be presented with an option to bid on the keyword. Responsive to the bid being accepted by the primary content provider, a cumulative bid is determined based upon an accumulation of an existing bid from the primary content provider and the bid. The non-published content, but not second non-published content of a second primary content provider, may be selected to be provided to a user based upon the cumulative bid exceeding a second bid for the keyword by the second primary content provider. In this way, content that may be relevant to the user may be identified and provided to the user.

Abstract: The present teaching generally relates to identifying data bucket overlap with online experiments. In a non-limiting embodiment, first data representing a first set of identifiers associated with a first data bucket of a first online experiment may be obtained. Second data representing a second set of identifiers associated with a second data bucket of the first online experiment may be obtained. Based on the first data and the second data, a first number of identifiers that are associated with the first data bucket and the second data bucket may be determined. In response to determining that the first number exceeds a threshold, a data flag indicating that results associated with the first online experiment are inconsistent may be generated.

Abstract: The present teaching relates to managing online experiments. In one example, a plurality of experiment layers is created with respect to a plurality of online users. Each experiment layer includes at least one experiment each of which includes one or more buckets associated with respective features to be experimented on. Each of the plurality of online users is assigned to a corresponding bucket in each experiment layer, such that the user is simultaneously associated with multiple experiments in different layers. User event data related to the plurality of experiment layers are collected from the plurality of online users. One or more contaminated buckets are automatically detected based on the user event data.

Abstract: As provided herein, a primary content provider (e.g., a book retailer) may present a campaign for a product (e.g., a novel), comprising non-published content and a keyword (e.g., the novel title), to a permitted content provider (e.g., the publisher of the novel). The permitted content provider may be presented with an option to bid on the keyword. Responsive to the bid being accepted by the primary content provider, a cumulative bid is determined based upon an accumulation of an existing bid from the primary content provider and the bid. The non-published content, but not second non-published content of a second primary content provider, may be selected to be provided to a user based upon the cumulative bid exceeding a second bid for the keyword by the second primary content provider. In this way, content that may be relevant to the user may be identified and provided to the user.

Abstract: One or more methods and/or techniques for content resource allocation are provided herein. A user, of a client device, may access content. Real time user traffic associated with accessing the content may be determined. A trend may be identified from the real time user traffic for the content. The real time user traffic may be indicative of an amount of the content distribution resources used to provide a threshold level of service to users. Responsive to the trend indicating a projected increase in real time user traffic for the content, the content distribution resources may be allocated to the content based upon the projected increase, such that the allocated content distribution resources provide the threshold level of service to the user.

Abstract: One or more systems and/or techniques for generating a combined advertisement are described herein. A primary advertisement associated with a primary advertiser may be accessed. A primary attribute for the primary advertisement may be defined (e.g., a car advertisement may target teenage boys). A first spot advertisement associated with a first advertiser may be selected based upon the primary attribute of the primary advertisement (e.g., a car tuning advertisement that also targets teenage boys). A combined advertisement may be generated based upon the first spot advertisement and the primary advertisement. In an example, the combined advertisement may be displayed to a consumer based upon a determination that the consumer corresponds to the primary attribute (e.g., a teenage boy visiting a website). In this way, multiple advertisements (e.g., having similar attributes/goals) may be provided through a single combined advertisement.