Abstract: Techniques are described for machine learning-based generation of target segments is leveraged in a digital medium environment. A segment targeting system generates training data to train a machine learning model to predict strength of correlation between a set of users and a defined demographic. Further, a machine learning model is trained with visit statistics for the users to predict the likelihood that the users will visit a particular digital content platform. Those users with the highest predicted correlation with the defined demographic and the highest likelihood to visit the digital content platform can be selected and placed within a target segment, and digital content targeted to the defined demographic can be delivered to users in the target segment.

Abstract: Techniques are described for machine learning-based generation of target segments is leveraged in a digital medium environment. A segment targeting system generates training data to train a machine learning model to predict strength of correlation between a set of users and a defined demographic. Further, a machine learning model is trained with visit statistics for the users to predict the likelihood that the users will visit a particular digital content platform. Those users with the highest predicted correlation with the defined demographic and the highest likelihood to visit the digital content platform can be selected and placed within a target segment, and digital content targeted to the defined demographic can be delivered to users in the target segment.

Abstract: Techniques and systems are described to enable an analytics system to generate a forecast value for audience impressions of subsequent digital video content. In one example, an analytics system generated a linear regression model using data. The data describes audience segment values for past audience impressions of digital video content and a time series of when the digital video content is made available for consumption. The analytics system generates forecast values for audience impressions of digital video content using the linear regression model. In one example, the analytics system generates a forecast value for audience impressions of a subsequent item of digital video content based on scheduled availability for the subsequent item.

Abstract: Creating audience segments for campaigns is described. In one or more embodiments, an audience manager is configured to create, for one or more videos, a video audience segment associated with the video by storing, in a data management platform, user identifiers of users that viewed the video. The user identifiers can be received from a client player each time that a video is played at the client player. The audience manager is further configured to extract demographic information from a demographic report associated with the video that is received from a demographics provider, and to associate the demographic information with the video audience segment. The audience manager is further configured to generate a target audience segment for a campaign by merging and combining user identifiers that are included in two or more video audience segments.

Abstract: Techniques and systems are described to enable an analytics system to generate a forecast value for audience impressions of subsequent digital video content. In one example, an analytics system generated a linear regression model using data. The data describes audience segment values for past audience impressions of digital video content and a time series of when the digital video content is made available for consumption. The analytics system generates forecast values for audience impressions of digital video content using the linear regression model. In one example, the analytics system generates a forecast value for audience impressions of a subsequent item of digital video content based on scheduled availability for the subsequent item.

Abstract: Creating audience segments for campaigns is described. In one or more embodiments, an audience manager is configured to create, for one or more videos, a video audience segment associated with the video by storing, in a data management platform, user identifiers of users that viewed the video. The user identifiers can be received from a client player each time that a video is played at the client player. The audience manager is further configured to extract demographic information from a demographic report associated with the video that is received from a demographics provider, and to associate the demographic information with the video audience segment. The audience manager is further configured to generate a target audience segment for a campaign by merging and combining user identifiers that are included in two or more video audience segments.

Abstract: Embodiments are disclosed that provide dynamic creative optimization for video advertisements. In certain embodiments, a content creation system receives a request for a video advertisement from a remote computing system. The request represents attributes of a specific recipient. To generate the video advertisement, the content creation system accesses a collection of assets, such as templates and video elements, from which video content can be generated. The content creation system selects a subset of assets from the collection and combines some or all of the selected subset of assets into a composite content file. The content creation system generates (or causes another system to generate) the requested electronic video advertisement or other video content from the composite content file. The content creation system provides the generated video advertisement or other video content in response to the request that was received from the remote computing system.

Abstract: Creating audience segments for campaigns is described. In one or more embodiments, an audience manager is configured to create, for one or more videos, a video audience segment associated with the video by storing, in a data management platform, user identifiers of users that viewed the video. The user identifiers can be received from a client player each time that a video is played at the client player. The audience manager is further configured to extract demographic information from a demographic report associated with the video that is received from a demographics provider, and to associate the demographic information with the video audience segment. The audience manager is further configured to generate a target audience segment for a campaign by merging and combining user identifiers that are included in two or more video audience segments.

Abstract: Creating audience segments for campaigns is described. In one or more embodiments, an audience manager is configured to create, for one or more videos, a video audience segment associated with the video by storing, in a data management platform, user identifiers of users that viewed the video. The user identifiers can be received from a client player each time that a video is played at the client player. The audience manager is further configured to extract demographic information from a demographic report associated with the video that is received from a demographics provider, and to associate the demographic information with the video audience segment. The audience manager is further configured to generate a target audience segment for a campaign by merging and combining user identifiers that are included in two or more video audience segments.