AI and big data have revolutionized digital marketing. It has changed the way we target ads, content, and analytics. Despite all of these changes, the relationship between marketing and big data does not get the same amount of attention as all of the other capabilities. This is especially true with video.
Video has proven time and time again that it is a valuable asset. In fact, over 52% of marketers believe that video can offer a higher ROI than any other marketing strategy. AI has done a lot with video marketing that marketers can leverage to their advantage.
Catering Recommended Videos
Everyone has been stuck in a YouTube loop at least once. After watching the first video, you are spending maybe 10 minutes watching recommended videos. Taking advantage of the recommended videos feature increases the reach of marketing campaigns. By reaching an additional audience that is already engaged with a similar, previous video, they will be more receptive to marketing messages.
While no one knows how exactly the YouTube algorithms work for ranking recommended videos, it does rely on different variables such as the number of likes, comments, and views. It is important to optimize your videos with the right meta tags and descriptions. Include your top performing keywords in the title and description.
Production is More Efficient
Creating a high quality video is important, but can be time consuming if you do not have an in-house production team or the budget to hire one. A lot of these tools take out the programming and required design work involved in the process. This allows you to create high quality videos with little to no knowledge of design and video editing.
These tools can rely on big data in many ways. For example, big data can be used to understand the different types of content that people respond to and build custom content around them. When you put all of these together, it creates an efficient process for creating optimized video content.
Take Advantage of Targeting
YouTube and other video platforms have a variety of targeting options for marketers. For example, YouTube relies on AdWords for streaming video ads. Here are the different targeting options for YouTube Audiences:
- Age
- Gender
- Parental Status
- Household Income
- Major Life Events (ex. Having a child or finishing college)
- Interests
- Specific YouTube channels and videos
In addition to optimizing titles and descriptions, this is another way to help leverage campaigns and make sure they reach the right audience.
Video marketers need to be aware of how things are changing and adhere to them. Take advantage of detailed targeting and conduct split tests to help improve the ROI of your campaigns. It is interesting to see where AI and big data will take video targeting, but it will continue to make waves throughout the industry.