So, you’ve developed an OTT app and you’ve marketed it to your viewers. Now your focus is on keeping your viewers watching. How can machine learning drive more engagement? Let’s face it—they may have a favorite show or two, but to keep them engaged for the long term, they need to be able to discover new shows. Because OTT is watched on TVs, you have a lot of real estate to engage with your viewers. A video’s thumbnail has more of an impact on OTT than any other platform, so choose your thumbnails carefully!
Discovery is different on different platforms
On desktop, most videos start with either a search (e.g. Google) or via a social share (e.g. Facebook). Headlines and articles provide additional info to get a viewer to cognitively commit to watching a video. Autoplay runs rampant removing the decision to press “play” from the user.
TVs have a lot more real estate than smartphones
On a smartphone, small screen size is an issue. InfiniGraph’s machine learning data shows that more than three objects in a thumbnail will cause a reduction in play rates. Again, social plays a huge role in the discovery of new content, with some publishers reporting that almost half of their mobile traffic originates from Facebook.
OTT Discovery is Unique
The discovery process on OTT is unique because the OTT experience is unique. Most viewers already have something in mind when they turn on their OTT device. In fact, Hulu claims that they can predict with a 70% accuracy the top three shows each of their users is tuning in to see. But what about the other 30%? What about the discovery of new shows?
Netflix AB Test Example
Netflix has said that if a user can’t find something to watch in 30 seconds, they’ll leave the platform. They decided to start A/B testing their thumbnails to see what impact it would have, and discovered that different audiences engage with different images. They were able to increase view rates by 20-30% for some videos by using better images! In the on-demand world of OTT, the right image is the difference between a satisfied viewer and a user who abandons your platform. If you’re interested in increasing engagement on your OTT app, reach out to us at InfiniGraph to learn more about our machine learning technology named KRAKEN that chooses the best images for the right audience, every single time. Also, check out our post about increasing your video ad inventory!
Want to learn what type of video content KRAKEN’s Video Machine Learning technology works with? Read on!
So, you already have video on your site and you’re asking yourself, “can KRAKEN help me get more video plays??? I mean, my content is pretty special and unique!”
Let’s get right down to answering that with these 3 easy steps:
Step 1: Come to our blog. Wait… you’re already here. Good job! You’ve done Step 1 successfully, so check it off your list.
Optimized thumbnails with 198% lift
Step 2: Ask yourself—what kind of content do I have and how is it monetized? I mean, you could just have video and not make money on it. You could run pre-roll beforehand, or you could get paid with every video play by the producer/creator (this last one is called “premium video”).
Step 3: Scratch Step 2, because KRAKEN can help increase play rates with all three types! Check out the following examples!
Quick recap of what’s happening with each video below:
Video is broken down into a bunch of “best possible” thumbnails (using crazy smart algorithms)
Your audience selects their favorite thumbnails via A/B testing & machine learning (favorite=thumbnail they WANT to click on)
We intelligently rotate through the best (aka favorite) thumbnails to ensure a high click-to-play rate
Click play… notice that the video begins playing? This is premium video where the content is the advertising medium. Notice the video is about a product, so there’s no need to run a pre-roll ahead of time.
What do I do next?
As you can see, KRAKEN increases play rates on just about any type of video content. You just need to release the KRAKEN!
Want to see some awesome examples where optimized thumbnails performed up to 425% better than the original? Check out this article.
I’ve never met anyone who intentionally picked a bad video thumbnail—but they’re everywhere.
To be clear, bad ≠ ugly. Bad thumbnails are sometimes beautiful. Bad means that people don’t WANT to click on them. After all, the point of a thumbnail is to get people to click “play” or “stop scrolling” long enough for the video to start to playing.
Editors and content creators with years of experience spend a lot of time picking “best” thumbnails. And publishers posting hundreds of videos daily rely on content management systems (CMS) that suggest or auto-pick thumbnails.
Guess what? They’re usually wrong.
Almost always, there is a better thumbnail for any given video or set of thumbnails.
Because “best” is defined by your audience, not you. You bring your experience and baggage with you every time you pick a thumbnail—and you are different from your audience. Why not take the guess work out of the equation and use data, not opinion, to choose the right thumbnails every time?
Let’s say you’re an editor in LA and pick a thumbnail for a video about the latest breaking news topic. You might choose this image to the right:
Now what if your viewer is from Texas? What if that image doesn’t speak to them at all? That doesn’t mean they’re not interested in the topic or wouldn’t want to see the video content, it means that the thumbnail doesn’t make them WANT to click “play.”
If you had asked your viewers, they would have told you that they preferred seeing the images on the left—all taken from the very same video.
Our recent post “The Force Awakens” shows another great example and the science behind data-chosen thumbnails.
Your audience isn’t one-size-fits-all. Your thumbnails shouldn’t be either.
Here are 52 videos from last month that prove intelligent selection of images can greatly improve video play rates. Each has an optimized set of thumbnails that performed 101%–425% BETTER than the original thumbnail.
Quickly though—what is an optimized thumbnail?
Optimized thumbnails are dynamic and rely on machine learning and audience feedback. Our product called KRAKEN does this all in real-time
So, what the heck does that mean in english???
It means that our computers examine a video and pick a bunch of ‘best possible’ thumbnails, then A/B tests them to determine what ones people actually click on. It will serve different images to different people depending on a variety of factors, including device and placement. Hey, it’s a patented process!
Said another way, we crowdsource what thumbnails people actually engage with, then show them to future visitors.
Results – Before & After
Think sports fans will click on any video related to their team? Think again. Optimized thumbnails performed 198% better than the original: Original Thumbnail KRAKEN Optimized Visuals
Optimized thumbnails work for ‘hard’ news videos, too. This video about Enrique Marquez’s ties to the San Bernardino gunmen had a 205% lift: Original Thumbnail KRAKEN Optimized Visuals
Kardashians—love them or hate them, right? It turns out that optimized thumbnails can produce a 128% lift in video play rates: Original Thumbnail KRAKEN Optimized Visuals
From earlier in the article: the Rikers Island Guard video saw a 157% lift, while the video of a Teacher under fire for her lesson on Islam saw a 127% lift.
Our top performing video of December saw a 425% lift. Here’s an overview of all 52:
What could you do with double the video plays (or 3X or 4X)?
Would it double your video revenue? Satisfy your audience because more of them are seeing your awesome video content (after all, that’s why they’re on your site in the first place)?
The good news is your “best” thumbnails already exist and are buried in your existing videos. You just need to release the KRAKEN and get them to the surface.
Leave a comment below and tell us your thoughts. If you are interested in links to all 52 top performing videos, send me an email at email@example.com—I like talking with new people.
Video machine learning technology called KRAKEN skyrockets mobile consumer engagement by 16.8X for the Interstellar Trailer (case study).
Social networking for influential moms
SocialMoms began in 2008 as a popular community site for moms looking to build their reach and influence through social networking, traditional media opportunities, and brand sponsorships. It now boasts over 45,000 bloggers, reaches more than 55 million people each month, and has a network of influencers with more than 300 million followers on Twitter.
Create engaging mobile digital media campaigns for women 25-49 SocialMoms brings top brands to millions of women each month. They are responsible for ensuring that each campaign not only reaches the intended audience, but also that it be engaging and meaningful. However, it was challenging to get meaningful audience engagement with video campaigns on their smartphones.
Responsive visuals optimized for mobile
KRAKEN replaces a video’s old, static default thumbnail with a responsive set of “Lead Visuals” taken from the video. It treats each endpoint differently, so it can optimize a movie with one set of visuals for a desktop site and another set of visuals for a mobile site—because people respond differently depending on which device they use for viewing.
Maximum lift of 16.8X on mobile for the Interstellar Campaign After KRAKEN’s “Lead Visuals” optimization, engagement via mobile skyrocketed. SocialMoms saw over 16.8X increased engagement compared to the original default thumbnail that was chosen for the desktop site. They also reported higher completion rates when running KRAKEN.
“We’re seeing the highest engagement levels for our customers using InfiniGraph’s KRAKEN powered content.” – Jim Calhoun COO SocialMoms
Video marketing is being revolutionized by machine learning, fast data and artificial intelligence. The dawn of data-driven video is upon us. Video takes the lion’s share of marketing spend and fast-growing mobile video is surpassing all other marketing methods. Understanding behavior and content consumption is key in optimizing mobile video. Brands have an insatiable appetite for consumer engagement, as evident in brands’ adoption of video, reported by YouTube, Facebook and InMobi.
Video industry leaders who embrace these advanced technologies will establish a formidable competitive advantage.
The market is moving away from the video interruption ad model and premium video is taking center stage. Battle for middle earth is being waged between video networks, publishers, and content creators. Those who have intelligent data will win the video marketing thunder-dome.
With few exceptions, old school person-to-person media buying is fading fast. Machine learning is being used to ensure the optimal deal is always reached in programmatic video placement. We are seeing a torrent of data coming in from ad platforms, beacons, wearables, IoT, and so forth. This data tsunami is compounding daily, creating what the industry calls “fast data”. Video and human action on video is a big challenge due to consumption volume. The competitive weapons are now speed and agility when building an intelligent video arsenal.
In July, I attended the launch of Miip by InMobi, an intelligent video and ad unit experience. These units are like Facebook’s left and right slider units, but Miip has also implemented discovery. Check out the video to see more of what I’m talking about:
All programmatic networks use fast data composed of human personas, actions, and connected devices. This data explosion is forming big data, and it’s happening at a massive scale. It’s not surprising that programmatic targeting leveraged machine learning and big data management. There is a lot of hype around Real-Time Bidding (RTB) and programmatic targeting.
With all this technology, the one thing that remains true is content still must resonate with the consumer – and machine learning is creating a huge opportunity to match the right content with the right consumer.
Video creation tools like Magisto, PowToon, and iMovie are simplifying the process. The decreasing hardware costs have also lowered the barrier of entry. The iPhone 6, Hero4, and video drone technology are great leaps forward in video capture.
Low-cost broadcast-quality video is here with iMovie HD and Camtasia Studio 8. Full commercials are edited on iPhones only. There is an explosion of professional content now. What was once cost-prohibitive is now the industry norm. With all this video technology unleashed, hundreds of YouTube stars were born. The cable cord-cutting acceleration is upon the cable networks now. As more high-quality digital video hits the scene this will fuel grater choice on the consumer’s terms.
Peter Fasano, from Ogilvy, and Allison Stern of Tubular, did a great job presenting The Rise of Multi-Platform Video. Here they reveal the differing advantages of Facebook and YouTube.
This year, Cannes Lions was all about VIDEO storytelling with a big focus on data. Visual and mobile content experiences are personal. I am seeing a massive shift to data-driven journalism. Companies like Google News Lab, Facebook’s Publishing Garage, and Truffle Pig (a content creation agency) are all working with Snapchat, Daily Mail, and WPP – all powering scaled content creation.
“The power of digital allows content, platform, and companies to test and learn in real time before scaling.” -Max Kalehoff
Hear more on this movement from David Leonhard from New York Times’ The Upshot, Mona Chalabi from Facebook Garage, and Ezra Klein and Melissa Bell from Vox:
Video is Not Spandex
Consumers are not one-size-fits-all when it comes to how they consume content. The creation of content is a natural progress for using artificial intelligence (AI) technology. Machine learning has the ability to connect many data elements and test many hypotheses in real-time. Using humans to adjust the algorithms is “supervised learning”. “Unsupervised learning,” a self learning and constantly improving system, is the holy grail in AI.
Getting the right message to the right person is critical in obtaining a positive response. The delivery process and decision will impact the responsiveness. Each platform requires a different strategy. Companies like Tubemogul, Tremor Video, and Hulu all have programmatic video management.
Now broadcasters are starting to embrace data, which enables advertisers to target a more specific audience. Soon we’ll have AI video distribution based on the actual content inside the video.
This graph shows real-time A/B testing from video launch and KRAKEN machine learning optimization in action. Machine learning makes it possible to stabilize and achieve lift.
The following are three examples of machine learning techniques being used to enhance video engagement levels:
Fast data requires advanced algorithmic learning to process: Identify what demographic responds well to which content type (e.g. video). Segment your audience by the type of content consumed. Look at what was shared when most comments were generated. Combine these data points and see what drove most action. These steps will help you learn what logical groupings achieve highest targeting response.
Identify what visual objects induce habitual responses: What visual objects allow for higher consumer engagement? Visual content can then be grouped and that knowledge can be used over and over in later videos.
Machine learning predicts video consumption habits: What people watch tells you a great deal about their preferences. Measuring audience behavior across video types creates a consumption map. Consumption maps predict things like video placement and cycle times.
The type of visual content affects the reaction of a targeted segment. Machine learning can track the visual preference of the video segments. Each brand and content creator structure can achieve a new level of understanding. What does the audience find most appealing? Is there a large-scale pattern you can identify?
The next frontier of mobile video is intelligence – the ability to predict, as well as adapt, content based on all the data available. We are seeing companies like IRIS.TV indexing video libraries to recommend content. Netflix and Amazon have the capability to “predict” using supervised learning human curators. All this metadata in video is providing a treasure trove of information: now we’re connecting with the social graph changing the game.
Finding content that viewers will enjoy is the ultimate goal and extended deep video engagement is a big opportunity. Achieving this level of nirvana has its challenges: see Why Websites Still Can’t Predict Exactly What You Want. We are just scratching the learning algorithms surface of artificial intelligence.
As technology advances, more intelligent visual content marketing will emerge. Machine learning will soon dominate the data-driven marketing landscape. We are moving toward story creation with technologies like Dramatis. People like Brian O’Neill at Western New England University are leading the way (see With Expanding Roles, Computers Need To Add ‘Storyteller’ To Resume). Video networks, content creators, and publishers have a grand opportunity, but all are going to need to collaborate and incorporate a more sophisticated offering if they plan on competing over Facebook and YouTube. The big question is, will they maintain control of their content destiny?
In the age of intelligent data, audience insight is always a winning strategy. Those who tune their video content with intelligence will achieve higher levels of revenue.
Video machine learning technology called KRAKEN boosts consumer engagement by 309% for the Fifty Shades of Grey Trailer (case study).
AnchorFree: The most trusted VPN service in the world!
With a monthly active user base of over 25 million and 350 million installs to date, AnchorFree’s Hotspot Shield VPN is the largest free VPN service in the world. It has an unparalleled ability to protect users’ IP from spammers, snoopers, and hackers, provide Wi-Fi security, and detect and protect against malware.
Increase revenue from limited inventory In order to keep Hotspot Shield free, AnchorFree relies on advertising. With finite inventory and users, increasing consumer engagement is very important, as this results in a higher yield for each video. They are constantly looking to generate more interest and engagement with each longform video placement to increase advertising revenue.
Responsive visuals at programmatic scale
KRAKEN uses machine learning technology to replace static thumbnails with a programmatically optimized set of “Lead Visuals.” This directly results in higher user engagement. AnchorFree is therefore able to increase yield from a finite user base and inventory.
Consumer engagement increased 309% with the Fifty Shades of Grey Campaign
Over the course of the campaign, KRAKEN was able to increase consumer engagement by 309% when compared to the trailer using a standard default thumbnail. AnchorFree was able to generate additional revenue leveraging existing customers and without having to add inventory.
“Without KRAKEN running, we would be leaving money on the table. I can’t imagine why anyone would run video without first optimizing it with KRAKEN.” – Baglan Nurhan Rhymes Chief Digital Officer, SVP Global Revenue AnchorFree
Video machine learning technology called KRAKEN drives 40% additional revenue for the Birdman Trailer (case study).
Most trusted VPN
service in the world! With a monthly active user base of over 25 million and350 million installs to date, AnchorFree’s Hotspot Shield VPN is the largest free VPN service in the world. It has anunparalleled ability to protect users’ IP from spammers, snoopers, and hackers, provide Wi-Fi security, and detectand protect against malware.
Increase revenue from video longform placements In order to keep Hotspot Shield free, AnchorFree is constantly looking for ways to increase their customers’ engagement levels and average revenue per user (ARPU). Regardless of premium placement on the AnchorFree launch page, the video ads were producing less than desired click-to-start and completion rates. Before KRAKEN, AnchorFree tested with various forms of static default thumbnails attached to the video promos.
Responsive visuals at programmatic scale KRAKEN uses machine learning technology to optimize “Lead Visuals” in a programmatic structure, enabling the highest video engagement possible. KRAKEN became the preferred platform to maximize video revenue yield from their current advertiser base.
40% revenue gain for the Birdman campaign KRAKEN boosted click to play rates for the Birman trailer video campaign by a staggering 3,000%. This increase in click to play rates directly resulted in a 40% gain in revenue. After realizing such profound revenue gains, AnchorFree does not run high value video campaigns without KRAKEN.
“InfiniGraph’s Kraken technology is the first real breakthrough we have seen in many years. I can see Kraken being implemented by digital broadcast networks, publishers, ad networks and video player platforms in the very near future. Early adopters will turbo charge their video ad revenues on desktop and mobile.”
– Baglan Nurhan Rhymes Chief Digital Officer, SVP Global Revenue
Video machine learning technology called KRAKEN sustains a 378% video play rate lift for the American Sniper Trailer over 48 Days (case study).
AnchorFree: The most trusted VPN service in the world! With a monthly active user base of over 25 million and 350 million installs to date, AnchorFree’s Hotspot Shield VPN is the largest free VPN service in the world. It has an unparalleled ability to protect users’ IP from spammers, snoopers, and hackers, provide Wi-Fi security, and detect and protect against malware.
Maintain engagement over long periods of time with the same media
AnchorFree shows movie trailers as part of their advertising campaigns. A single campaign with various video content might last two months. Before KRAKEN, AnchorFree would see engagement peak when videos were launched, but steadily decrease over time. Engagement levels decreased as users saw the same thumbnail over and over, slowly becoming blind to it. This phenomenon is called video fatigue.
Responsive visuals at programmatic scale
KRAKEN replaces a video’s old, static default thumbnail with a responsive set of “Lead Visuals” taken from the video. Since it is powered by machine learning, KRAKEN continually optimizes the set of “Lead Visuals” to ensure a consistently high engagement rate, even over long periods of time.
Average lift of 378% for the forty-eight day American Sniper Campaign Over forty-eight days, KRAKEN was able to increase engagement by an average of 378% for a single American Sniper video trailer. With a consistently high yield, Anchor- Free was able to run the campaign longer to maximize revenue versus using a standard, static thumbnail.
“We run trailers for weeks, even months at a time. Only after optimizing with KRAKEN have we been able to see consistent and high levels of engagement from the beginning of a campaign to the end.” – Baglan Nurhan Rhymes Chief Digital Officer, SVP Global Revenue AnchorFree