Fascinating Ways AI is Intersecting with Video Marketing

Artificial intelligence and big data have played a major role in video marketing over the past few years. They will continue to disrupt the profession in the years to come.

May 28, 2018
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Smart Data Collective has published a number of articles on the impact that big data has had on the marketing profession. Most of these articles focus on the role big data plays in marketing analytics. The relationship between big data and video marketing has received considerably less attention.

Over 52% of marketers believe that video offers a higher ROI than any other marketing strategy. A lot of this is due to the highly advanced targeting options that big data has provided to video marketers.

Advances in artificial intelligence and data technology have turned video marketing on its head. Here are some ways that marketers can leverage it to their advantage.

Streamlining production

Producing high quality videos is obviously an important part of video marketing. It is easier said than done. Many marketers can’t develop cutting edge video content on their own, so they turn to tools such as mysimpleshow to streamline production. These tools rely extensively on big data in a variety of ways.

The developers of the mysimpleshow platform have used big data to best understand the types of content that people will respond to and help marketers build custom videos around them. At the same time, they’ve also taken out all of the programming, required design and video work involved in the process — thus allowing anyone to take advantage of what the video creation tool has to offer, without the headaches of learning how to be a video or graphic designer.

Refining their knowledge of customers to promote related videos

YouTube and other video hosting platforms encourage visitors to look at videos that are related to the content they just watched. Google executive, Tris Southey, the product manager for Google’s DoubleClick Search division, provided a succinct overview of the benefits back in 2016 in their post on Think With Google.

“If you’ve ever finished a YouTube video and then enjoyed watching another (and another) thanks to the related videos that appear at the end of the video or on the sidebar, you’ve already benefited from an enhanced prediction engine. In the same way that YouTube interprets multiple systems and patterns to recommend a video, Smart Bidding can now set the appropriate original bid values and future adjustments for keywords that go far beyond the more obvious head terms into the longer tail.”

The recommended videos feature is beneficial to marketers for a couple of reasons:

  • It increases the reach of video marketing campaigns. Most viewers would presumably leave the video hosting site or look at a totally unrelated video after watching it. By showing their videos to more people, they considerably expand the pool of potential, relevant viewers.
  • People that look at videos that were recommended for being similar to the one they just watched are already engaged. They should be more receptive to marketing messages than people that found the videos through called traffic.

Big data is making it easier for video hosting platforms to recommend similar videos. However, brands must understand the ways that they can better target related videos. They must incorporate the right tags and descriptions to signal the relevance their content has to other videos on the network. However, demonstrating that your video is related to other frequently watched videos is not enough on its own. Over five billion videos are watched on YouTube every day. Many of them are in your own vertical, which makes it difficult to stand out.

If you want to make sure that your video content appears in the recommended videos results, you must have a deeper understanding of the algorithms behind it and optimize your content accordingly. Youtube uses logistical regression to assess the quality of all videos on their platform.

The exact formula for ranking videos on YouTube has not been publicly shared. However, it relies on a variety of weeded variables, such as the number of likes a video has received and comments in the stream.

Video marketers must try to boost their social metrics on YouTube to get more visibility through the recommended videos results. This can involve sharing videos through certain networking channels where they will receive the best responses and rewarding people that provide positive reviews.

Taking advantage of better targeting of users

YouTube and other video marketing platforms have provided a number of targeting options for marketers to reach their target audience. YouTube relies on the AdWords advertising platform, which is one of the most sophisticated in the world.

YouTube marketers can use AdWords to reach customers by:

  • Age
  • Gender
  • Parental status
  • Household income
  • Major life events, such as finishing college getting married
  • Interests
  • Specific YouTube channels and videos

The AdWords AI and big data solutions have made these target and capabilities possible. Big data is also useful for marketers trying to optimize their campaigns. They can leverage some of the most sophisticated tracking tools available, which help them identify the targeting options that proved to be the most effective.

AI and Big Data Are Changing Marketing in Spectacular Ways

Artificial intelligence and big data have played a major role in video marketing over the past few years. They will continue to disrupt the profession in the years to come. Video marketers must be aware of the targeting capabilities they provide and conduct a variety of split tests to improve the ROI of their campaigns. They should see even impressive results once they understand the potential big data and AI have created.