Artificial intelligence has found a home in many industries as a time-saver. AI's adoption in the video marketing industry underscores that widespread push into other sectors. Marketing, as a whole, has adopted AI in a big way. Gartner mentions that as much as 59% of firms have already deployed AI. We already know that video has a better chance of conversion than other marketing media. By combining it with AI, we try to harness both technologies have to increase sales and outreach. Both AI and Big Data are emergent technologies showing up in media around the world in a positive light. Their technological benefits have set the stage for marketers to take advantage of the information they provide us. In this article, we'll explore the ways that AI has already started disrupting the video marketing industry, and how marketers can seek to take advantage of technological development in this arena.
Professional video is usually of high production quality. Users tend to engage with a video production that is crisp and fun to look at. However, even when you produce high-quality video, you still need to get it in front of the right eyes. AI can help with both of these elements. By taking a look at what other video producers have done, AI can successfully advise companies what sort of videos work well in a given demographic.
Additionally, with enough collected data, AI can successfully predict what demographic of users best suits a company's videos. Other topics close to their original product may also drive new buyers to them, but it requires AI to determine the best route to take to get eyes on their advertising.
We already know that algorithms have an uncanny way of predicting the things that we're likely to enjoy. Along those same lines, marketers can leverage AI to help us understand customers more. This application can help video marketers in two distinct ways. Firstly, knowing what interests an audience helps the company decide what videos their audience is most likely to interact with.
Secondly, learning how the audience enjoys specific topics can provide inspiration for further advertising that takes advantage of those elements. As a bonus, predictive technology can push a video that conforms to what users are already interested in. Inc mentions that over 500 million people watch YouTube daily. Enhanced prediction algorithms allow related videos to get more views, and it's something video marketers can capitalize on.
Targeted marketing is a cost-effective method to ensure the "right" consumers see your video marketing. On social media, targeting is already something that companies can invest in. Facebook, Twitter, and Instagram have options for limiting the audience of an ad (and by extension, the ad spend) to a smaller demographic of users that make up the company's core audience. Lower spend with higher conversion rates are a win for any marketer.
For video sites such as YouTube, there are innovative ways to target an audience. Initially, YouTube invested in using AdWords to direct users to videos. Newer technology has seen the company move away from Google's solution with a focus on their own Find My Audience option for video marketers. Additionally, to further drive home the usefulness of ads and appeal to the small-business demographic, YouTube only charges the company when the user sees their ad. This subscription model is a win-win for both the advertiser (which serves their ads to the best possible audience for a minimal cost) and YouTube (which benefits from ad income).
Big Data is how social media companies get data to know which individuals to market to. Thus, for users of YouTube, big data encompasses a series of characteristics, that may be as general as age and location, or as specific as whether the user likes ice-cream or not. This level of granularity can be crucial to an advertiser to know whether a user may be interested in what they're selling. AI helps advertisers narrow down the net they cast with their ads to focus on the most convertible consumers.
For video marketers to have a chance of increasing the return on investment of their ad spends, they need to leverage AI alongside big data. Knowing what brings in the most views, combined with what creates the most buyers is a crucial metric. When marketing dollars are limited, being efficient with the use of these funds has never been more critical. Technology has given us the ability to spend smarter on ads, not it's up to us to take advantage of the improvement.