Video publishers have been caught off guard with the recent announcement of Apple blocking video autoplay. Even Google is pushing back on bad web ads. The backlash against video autoplay has been festering for some time. If losing video ad revenue and turning consumers off with declining traffic isn’t a wake-up call then what will be? Headlines like this from CNN “Apple’s plan to kill autoplay feature could leave publishers in the dust” should get video publisher’s attention. This clamp down isn’t a joke and Google and Apple are taking a hardline to clean up the web experience when it comes to video. Here we dive deep into how to get ahead of these changes by Apple/Google and increase your video lifetime value.
Facebook started the conversation
Since Facebook started force-feeding video autoplay on us, other publishers followed suit knowing their video volume would go up. However, some major agencies flat out said they would only pay half of the CPMs due to the viewability issues with autoplay. A major advertiser (Heineken) is publicly having challenges getting a 6 sec clip to stick. Publishers say the video relationship with Facebook is “complicated”. This is a topic of constant discussions and other players are outright opting out of video autoplay altogether in favor of a better consumer experience. The major catch 22 here is that publishers driving their O&O strategy can’t think of autoplay is a video strategy—it’s a tactic that, in most cases, turns consumers off. If you want to see some of the consumer backlash, just search on Google “how to turn off autoplay” and you will see that this is most definitely a real consumer pain point. With Apple’s latest release of iOS 11 specifically blocking video autoplay, a more thoughtful and intelligent approach is required.
A video strategy involves deciding to dominate a content category vertically and be the go-to source for the highest value content in that space. Yes, video is content marketing. People watch video for information, enlightenment, entertainment, etc. Video is a very effective communication tool. Video is mobile and on demand. And being a tool, the publisher has a responsibility to harness and wield that tool surgically vs. a blunt object that pushes video views without consumer consent or value add to paid advertisers. Some publishers understand this, such as LittleThings Inc. They are disabling video autoplay completely and focusing on consumer experience. This has resulted In higher play rates (CTR), and higher CPMs that can be verified and justified to their customers. The other major benefit was consumers engaged more.
“We wanted video views to be on the consumer’s terms. By running autoplay, you might [reach your desired] fill rate, but the user is not engaged with the brand the way they would if they raised their hands to watch the video” said Justin Festa, chief digital officer for Little Things, at JW Player’s JW Insights event in New York
The digital publisher today is going to have to use higher intelligence with consumers. A surgical approach to utilizing data and then presenting it is now a must have. So what is the benefit of artificial intelligence in video? It is better to start with the question: What is digital video? If we break it down, digital video is just a series of images and sequences spliced together. Humans are visual and have emotional responses to images and context. The story is a major draw in creating greater emotional response over simply the affinity one may have to the people. Now a computer that translates all the above and puts it into context would have to be truly intelligent. This is not something new; Netflix proved you get higher take rates by having the right images, which results in higher consumer engagement.
In the Making
Three years ago, a technology was introduced called KRAKEN. It utilizes video machine learning to select images to replace the static non-intelligent thumbnail with interactive dynamic thumbnails which are the best set of images to drive the highest play rates possible. The rotation of images provides more visual information when compared to a single image. Video clipping (GIF) was next, however, it is most effective in action shots. A new way of looking at video thumbnails was required. The solution was creating a real time responsive, dynamic intelligence and scoring images based on relevance. Finding the best images is one thing, however, powering video recommendation was a natural fit for finding great images. Learning what collective visuals work together to extend longer time on site is a major deal for all publishers. We’re living in exciting times with advances in machine learning and computer chip design having achieved amazing levels of image processing capability. We have experienced a big leap forward in the code foundation (like Deep Learning) now powering platforms to segment out objects, images, places and facial recognition. We’re in an artificial intelligence renaissance.
Show me the money
It’s no secret ads still drive the bulk of digital video revenue. For that very reason, each video play, and increased time on site, translates into cold hard cash. Making the site sticky and getting more repeat visits requires video intelligence. Google and Apple are very serious about protecting the mobile web. It is clear that Google AMP (accelerated mobile pages) has won out with the publishers while Facebook instant articles has fallen short and most have abandoned it due to lack of making money vs AMP. The perfect trifecta of real-time video analytics, intelligence image selection, and video recommendation are now a reality. We have the data and processing power to predict what images make you excited and what video is most relevant to watch. Video discovery is key for increasing video life time value.
Are you ready for the do not track and the non-autoplay world? Like it or not, Google and Apple are disabling video autoplay and intrusive ads. The digital broadcasting publisher has a grand opportunity to leverage machine learning in video. Tapping into visually relevant actions and drawing out behavior is a competitive advantage. Machine learning linked with digital video that maximizes your video assets is a strategic advantage and increases video lifetime value. The above video recommendation example was not possible before machine learning based video processing made it a reality. What possibilities can you imagine? .