Customized Placement of Digital Marketing Content in a Digital Video
Techniques and system are described to control output of digital marketing content with respect to a digital video that address the added complexities of digital video over other types of digital content, such as webpages. In one example, the techniques and systems are configured to control a time, at which, digital marketing content is to be output with respect to the digital video, e.g., by selecting a commercial break or output as a banner ad in conjunction with the video.
1 . In a digital medium environment to customize a time at which digital marketing content is output in relation to a digital video, a method implemented by at least one computing device, the method comprising:
examining, by the at least one computing device, content included in a digital video:
generating, by the at least one computing device, a suggestion based on the examining, the suggestion specifying a time at which an item of digital marketing content is to be output in relation to output of the digital video; and
outputting, by the at least one computing device, the generated suggestion to control output of the item of digital marketing content in relation to the subsequent digital video.
2 . The method as described in claim 1 , wherein the generated suggestion describes the time in the output of the subsequent digital video through use of a timestamp or the time as associated with a particular frame of a plurality of frames of the digital video.
3 . The method as described in claim 1 , wherein the generated suggestion describes the time as a break that is to occur in the output of the subsequent digital video to output the item of digital marketing content.
4 . The method as described in claim 1 , wherein the generating is performed based at least in part on tag matching or a rules engine.
5 . The method as described in claim 1 , wherein the examining is performed using a model trained using machine learning based on training data that describes:
user interaction with training digital marketing content output in conjunction with at least one training digital video; and
a time at which the training digital marketing content is output in relation to the at least one training digital video.
6 . The method as described in claim 5 , wherein:
the training data describes segments of a user population that correspond to the user interaction;
the training of the model is based at least in part on the segments described in the training data; and
the generating of the suggestion by the model is also based at least in part on identification of at least one of the segments of the user population that is to interaction with the item of the digital marketing content.
7 . The method as described in claim 5 , wherein:
the training data includes tags that describe characteristics of the digital video output in conjunction with the digital marketing content;
the training of the model is based at least in part on the tags described in the training data; and
the generating of the suggestion by the model is also based at least in part on identification of at least one of the tags of the subsequent digital video.
8 . The method as described in claim 5 , wherein the training data describes a series of said digital videos output in succession and the generating is based at least in part on identification of the subsequent digital video as part of a series of digital videos.
9 . The method as described in claim 5 , wherein the training digital marketing content is a banner advertisement or a video advertisement that is selectable to cause conversion of a good or service and the training data describes whether or not conversion is caused by the training digital marketing content.
10 . The method as described in claim 1 , wherein the generated suggestion is configured for output in a user interface of a content creation system that creates the subsequent digital video.
11 . The method as described in claim 1 , wherein the generated suggestion is configured to control the time at which the item of digital marketing content is output in relation to the subsequent digital video in a stream from a content distribution system to a client device via a network.
12 . In a digital medium environment to control output of digital marketing content with respect to a digital video, a method implemented by at least one computing device, the method comprising:
training, by the at least one computing device, a model using machine learning based on training data, the training data describing:
user interaction with training digital marketing content output in conjunction with respective portions of at least one training digital video; and
a tag that describes a characteristic of the respective portions of the at least one training digital video;
generating, by the at least one computing device, a suggestion by processing a subsequent digital video based on the model using machine learning, the suggestion specifying whether to apply the tag to a respective portion of the subsequent digital video; and
outputting, by the at least one computing device, the generated suggestion.
13 . The method as described in claim 12 , wherein the tag describes an emotional state associated with the respective portions of the at least one training video.
14 . The method as described in claim 12 , wherein the tag is associated with a particular frame of the at least one training video.
15 . The method as described in claim 14 , wherein the generated suggestion identifies a particular frame of the subsequent digital video, with which, the tag is to be associated with.
16 . In a digital medium environment to customize output of digital marketing content in conjunction with a digital video, a computing device comprising:
a processing system; and
a computer-readable storage medium having instructions stored thereon that, responsive to execution by the processing system, causes the processing system to perform operations comprising:
detecting a tag included in the digital video that describes content included within a respective portion of the digital video;
selecting an item of digital marketing content that is to be output in relation to output of the digital video based on the detected tag; and
controlling output of the selected item of digital marketing content in relation to the digital video.
17 . The computing device as described in claim 16 , wherein the tag describes an emotional state exhibited by the respective portion of the digital video.
18 . The computing device as described in claim 16 , wherein the selecting is performed using machine learning.
19 . The computing device as described in claim 16 , wherein the selecting is based on the tag associated with the digital video and a tag associated with the item of digital marketing content.
20 . The computing device as described in claim 16 , wherein the operations further comprise assign the tag to the digital video in real time as the digital video is streamed.