Video Machine Learning Skyrockets Mobile Engagement by 16.8X (Case Study)

Video machine learning technology called KRAKEN skyrockets mobile consumer engagement by 16.8X for the Interstellar Trailer (case study).

COMPANYVideo Machine Learning KRAKEN Social Moms Logo

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.

CHALLENGE

Create engaging mobile digital media campaigns for women 25-49
Video Machine Learning KRAKEN Interstellar PosterSocialMoms 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.

SOLUTION

Responsive visuals optimized for mobile

interstellarkraken1KRAKEN 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.

RESULT

Maximum lift of 16.8X on mobile for the Interstellar CampaignVideo Machine Learning KRAKEN Interstellar Graph
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.

 

Video Machine Learning KRAKEN Jim Calhoun“We’re seeing the highest engagement levels for our customers using InfiniGraph’s KRAKEN powered content.”
– Jim Calhoun COO
SocialMoms

 

 

Download InfiniGraph’s Interstellar Case Study (PDF)

Read our Birdman Case Study

Would you like to learn more about video machine learning?  Request a demo!

Video Machine Learning: A Content Marketing Armageddon?

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.

We see big players like Tubmoguel seeing massive growth, as described in Mobile Programmatic Buying Is Taking Off. Programmatic spend in mobile now surpasses desktop by 56.2%, eMarketer points out.

Video Creation & Growth
KRAKEN Video Machine Learning - Chase McMichael Video Setup

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.

In both cases, content engineering is a must-have (see 5 Hypnotic Mobile Native Video Content Marketing Methods).

Facebook Engagement Tubular Labs Ogilvy

Secrets To A Successful Video Strategy from Social@Ogilvy

Data Driven Video Storytelling

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.

The exciting part is when machine can create by themselves. We are witnessing this at Google: see Inceptionism: Going Deeper into Neural Networks.

the carnival of the animals and goodness knows what else

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.

Video Machine Learning Kraken Birdman Graph

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:

  1. 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.
  2. 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.
  3. 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?

Visual Programmatic
KRAKEN Video Machine Learning - Netflix-Wants-Personalized-Recommendations-Instead-of-Current-Interface-443094-2-1

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.

Would you like to learn more about video machine learning?  Request a demo!

How do you see machine learning impacting video in the future? Share your thoughts in the comments!

Image Credits
Featured Image: Andrey_Popov/Shutterstock.com
In-post Photo: Image by Ryan Shane. Used with permission.
All screenshots by Chase McMichael. Taken August 2015.

Video Machine Learning Boosts Consumer Engagement by 309% (Case Study)

Video machine learning technology called KRAKEN boosts consumer engagement by 309% for the Fifty Shades of Grey Trailer (case study).

COMPANYVideo Machine Learning Kraken AnchorFree Logo

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.

CHALLENGE

Increase revenue from limited inventory
Video Machine Learning Kraken Fifty Shades of Grey Movie PosterIn 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.

SOLUTION

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.

RESULT

Consumer engagement increased 309% with the Fifty Shades of Grey CampaignVideo Machine Learning Kraken Fifty Shades of Grey Graph
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.

 

Video Machine Learning Kraken Baglan“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

 

Would you like to learn more about video machine learning?  Request a demo!

Download InfiniGraph’s Fifty Shades of Grey Case Study (PDF)

Read our Birdman Case Study

Video Machine Learning Drives 40% Additional Revenue (Case Study)

Video machine learning technology called KRAKEN drives 40% additional revenue for the Birdman Trailer (case study).

COMPANYVideo Machine Learning Kraken AnchorFree Logo

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. 

CHALLENGE

Increase revenue from video longform placements
Video Machine Learning Kraken Birdman Poster
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. 

SOLUTION

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.

RESULT

40% revenue gain for the Birdman campaignVideo Machine Learning Kraken Birdman Graph
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.

 

Video Machine Learning Kraken Baglan“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
AnchorFree 

Would you like to learn more about video machine learning?  Request a demo!

Download InfiniGraph’s Birdman Case Study (PDF)

Read our American Sniper Case Study

Video Machine Learning Sustains a 378% Lift Over 48 Days (Case Study)

Video machine learning technology called KRAKEN sustains a 378% video play rate lift for the American Sniper Trailer over 48 Days  (case study).

COMPANYVideo Machine Learning Kraken AnchorFree Logo

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.

 

CHALLENGE

Maintain engagement over long periods of time with the same media

Video Machine Learning Kraken American Sniper PosterAnchorFree 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.

 

SOLUTION

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.

RESULT

Average lift of 378% for the forty-eight day American Sniper CampaignVideo Machine Learning Kraken American Sniper Graph
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.

 

Video Machine Learning Kraken Baglan“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

 

Would you like to learn more about video machine learning?  Request a demo!

Download InfiniGraph’s American Sniper Case Study (PDF)

Read our Birdman Case Study

Video Marketing Powered By Machine Learning: Game Changer

As video consumption increases, the need for a more intelligent, learning and adaptive technology is necessary to remain competitive in video marketing today. Data driven marketing is a digital differentiation. Those that have harnessed video insights to increase video yield will lead the way. SEE Case Study on Birdman (PDF)

In our previous post 5 Ways Machine Learning Accelerates Mobile Video [VIDEO] we describe the behavioral properties of content interactions within the video stream and how to sustain consumer engagement over various video networks. The above video is a quick intro by Chase McMichael, CEO of InfiniGraph and co-inventor of KRAKEN, the world’s first video machining learning technology. In this video, he describe KRAKEN’S value proposition for both video networks and publishers.

Chase McMichael Video SetupVideo machine learning is no longer science fiction. But the technology is only part of the equation; scalability is required to process and display massive numbers of videos. For big publishers, just managing the video distribution process appears daunting; video optimization is an afterthought.  However, thanks to advanced algorithms and fast computing, the ability to learn what “Lead Visuals” are most engaging and then optimize videos can be done real-time and at scale.

Creating great video takes time, and time is money. Maximizing all your video assets requires rethinking a post-and-pray strategy.  Just as algorithms are used to target consumers,  they can now be used to optimize videos and increase engagement.

Request a demo and let us show you how KRAKEN video machine learning will increase your video yield. Access our case studies here for more depth on video machine learning.

5 Ways Machine Learning Accelerates Mobile Video

 In Mobile Video Machine Learning KRAKEN, the “Birdman” Case study demonstrates video lift engagement powered by machine learning. In “5 Ways Machine Learning Accelerates Mobile Video”, we dive into why brands are embracing video as a key marketing and storytelling tool and how machine learning can be used to drive higher engagement.

The hard reality is video is STILL LINEAR.  Even so, some are attempting to make them interactive like Jack White’s Interactive Video that allows viewers to choose their own adventure.

While the majority of brand videos are still stuck in a 15s / 30s pre-roll with a force fed content model, we’re starting to see a clear migration to long form and sponsored content that’s not just an interruption but instead it IS the story. Video machine learning is new and millions of videos can benefit from programmatic visual control. Why machine learning? Marketers don’t care what algorithms you’re using they just want to see:

Mobile Video Machine Learing Birdman post

Case study on the movie trailer “Birdman” Click to play lift achieved 3000% using machine learning technology.

  • Revenue
  • Efficiency
  • Effectiveness

Publishers are looking to achieve high KPI’s in order to increase overall spend while the media buyer is looking to lower CPA, without increasing costs. Publishers are trying to increase inventory and get the most out of their customer’s engagement. Machine learning enables both parties to achieve their goal by impacting revenue, efficiency and effectiveness simultaneously.  With this technology publishers are empowered to keep the user video engagement high over significantly longer periods of time which is proving to be an invaluable tool that will become imperative to all successful video marketing efforts.

What Marketers want to see?

  • Viewability
  • Video watch time
  • Audio on or off
  • When did consumer stop watching
  • Was the video paused
Video Viewablity Across the Web

Google research finds only 53 percent of PC video advertising is viewable.

Gone are the days of simply tracking web page hits. A more sophisticated marketer has emerged where data is king. However, video distribution and analytics are complicated. Machine learning facilitates the systems ability to learn behavior and automatically adjust marketing efforts based on active feedback loops. This virtual neural network driven by human interaction with video content creates a meaningful data set providing the foundation for mobile video intelligence.

Programmatic Explosion

Machine Learning Mobile Video Birdman Split Test KRAKEN

Graph shows real-time A/B testing of static image and KRAKEN image driven by machine learning. Machine learning makes it possible to stabilize and achieve lift.

Programmatic targeting reached an all time high of sophistication with it’s own machine learning and big data approach. Companies like RockFuel, Turn and eXelate have all perfected audience based targeting with advanced machine learning methods of aggregating massive sums of data to ensure that the right content is placed in front of the right people at the right time. The following are examples of machine learning techniques being used to enhance content engagement levels.

1. Algorithmic learning is used to determine what demographic segment responds well with specific content (e.g. videos).

2. Identification of habitual responses to visual objects by region allows for higher confidence of consumer engagement with content.

3. The type of content greatly affects the reaction of a targeted segment. Machine learning can track the visual preference of the video segments to give brands and content creators a new level of understanding as to what an audience will find most appealing.

4. Machine Learning can predict audience consumption. Plotting audience behavior across video types creates a consumption map, which can be used to predict things like video placement and cycle times.

5.  Reduce video fatigue and increase engagement by rotation of static video images (thumbnails). Static starting images face image fatigue due to a lack of visual changes, color and motion alterations. Continuous and dynamic changes in a static video image will increase audience interest and result in higher click to play rates as well as completion rates.

Visual Programmatic

Netflix has the capability to “predict” what you would watch next based on past viewing habits. Information like show/movie title and genre are compiled to help select Netflix’s recommendations. These algorithms are an example of something that pulls from the surface level information vs actual content within the video.

Netflix-Wants-Personalized-Recommendations-Instead-of-Current-Interface-443094-2 Visual content marketing is a very powerful method of attracting and retaining customers. Building a content story arch is key to perpetuating engagement and video is the most effective means to accomplish this. Publishers that leverage their audience to tune the video will achieve higher levels of revenue on their existing assets.

How do you see machine learning impacting video in the further and what video KPIs do you track that aren’t on the list? Let us know in the comments!

Mobile Video Play Rate Boosted by 200X to 3000X – KRAKEN Release – Case Study

Problem:

Video is the largest and fastest growing segment in online marketing. Unfortunately the first impression to a consumer of those videos is more than likely a static image and there isn’t a simple way to programmatically adjust based on audience intelligence. This problem is leaving billions on the table with un-played videos and lost engagement due to the lack of compelling starting visuals.

Baglan

Baglan Nurhan Rhymes , SVP of Revenue – AnchorFree

“In a highly competitive Ad Tech space, where videos drive the lion share of revenues, InfiniGraph’s technology, Kraken, 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. ”

Initial Results:

Our beta customers: Disney, Paramount, Microsoft and AnchorFree have experienced between 10% to 3000% lifts in click-through and play rates on their video content using InfiniGraph’s patented Kraken technology..Mobile Video Play Rate Boost AnchorFree

Example –  AnchorFree before and after on “50 Shades of Grey”:

  • 200%+ boost in play rate
  • 10X increase in private viewing sales

InfiniGraph’s machine learning technology, achieves scale by producing the highest possible response to mobile video based on audience behavior.

Learning algorithms matter:

Mobile Video Birdman AnchorFreeImproving mobile video play rates is more of a science as seen in the second example on AnchorFree running “Birdman”.  Is your video “Thumb Stopping” when a consumer scrolls through their feed?  In the case of Birdman, the results were amazing.

Overall video play rates grew by:

  • 3000%+ boost in play rate
  • 2.6% peek click through rate

 

Mobile Video Performance Birdman KRAKEN Machine LearningSolution:

The Kraken machine learning system is continuously analyzing the video and user interactions at every content distribution endpoint, over many sequences. This decision making is done almost in real-time.

Value:

Mobile Video Machine LearningInfiniGraph’s mission is to help video content owners, publishers, and agencies deliver the most relevant video experience. This helps boost video starts, video completion rates, and increases page visit depth by eliminating creative burn and waste. This translates into higher revenues for the existing content through higher video starts, higher VCRs, and higher brand engagement.

Our clients, who have implemented proprietary “video click-through / play rate enhancement technology called “Kraken”,  have experienced upwards of 3000% lift in content plays.
As an Advertising,  Content Mobile Video Machine Learning Whats KRAKENProducer,  or  Brand Management Professional you know that video creates the greatest impact to your online marketing.  The challenge and measurement of success continues to be execution of “play-rates” and “video completion rates” .

Want to see more or run your own test? Contact Us

 

Mobile Native Video Interstellar 14X Hyper Play Rate Jump

Jim Calhoun, COO SocialMoms

Jim Calhoun, COO SocialMoms

We’re seeing the highest engagement levels for our customers using InfiniGraph’s native content

Paramount’s Interstellar uses mobile native video and distributed native advertising units to hyper jump their play rates by 14X. Mobile video is exploding and brands are leveraging advanced methods of distribution outside of the old school static native ads we are seeing today. We are now in the age of intelligence, machine learning, and responsive design.  Why can’t this intelligence be applied to mobile native video? Learn how to hyper drive your own mobile native video – signup, request a demo, and see how intelligence is applied.
Sign UP for Mobile Native Video

Above is an example of such intelligence integrated within the mobile native advertising unit for on and off domain content amplification. The mobile video leverages “deep linking” to launch video on a smartphone creating a seamless consumer experience. The content inside the native unit is dynamically updated based on consumer actions which increases overall engagement rates and exposure.

The Takeaway:

  • 50% play rate boost
  • Maximize content marketing spend
  • Mobile first content rendering
  • Intelligent content distribution
Rich Media CTR example

Doubleclick data showing industry averages of 0.06 to 0.18 vs .84 for mobile native more on benchmark on rich media

Most brands are sitting on tons of great content. This content is usually stuck in silos and doesn’t have a simple way of tracking with the consumer across other media sources, such as a websites/blogs (owned), and other paid mediums. Ad re-targeting is extremely effective; however a major issue is visual ad fatigue. The consumer sees the same media over and over, eventually reducing effectiveness. The Industry benchmarks on rich media content averages around .06% to .10% CTR compared to native ads which perform much higher. With new intelligent data techniques harnessing machine learning, these technologies are pushing engagement rates up to 50% improvement. 

Interstellar200

Interstellar Mobile Native Video

Content Marketing has truly taken on a new life and the quality of content within videos has leaped to extraordinary levels.  As more publishers and brands are seeking to control the content on their site, white label native ad platforms will continue to take hold.

Native unit for Interstellar launching the mobile native video

Native unit for Interstellar launching the mobile native video

The example on the left demonstrates what an embedded native unit looks like when deployed over a publisher network or brand website. The code behind these units is designed with a mobile first strategy, assuring optimal rendering on mobile. InfiniGraph sources content from the existing Interstellar movie published content, scores the content and transforms it into intelligent mobile native units. What’s unique about this approach is the consumer actions on content are tracked and the brands content inventory is managed per individual unit to maximize content marketing spend. eye-120803Keeping content fresh is a major factor in reducing image fatigue, repetitiveness, and inactive engagement. The human brain can process images in 13 milliseconds, how fast your visuals resonate with your consumer is key to amplifying brand content on domain as well as enhancing off domain engagement. The same mobile native unit can be deployed over other 3rd party native networks, ad networks, programmatic exchanges, and on the brands domain simultaneously.

Apply some intelligence in your mobile native video – signup, request a demo and see how intelligence is applied.
Sign UP for Mobile Native Video

5 Hypnotic Mobile Native Video Advertising Methods

Mobile native video advertising has transformed content marketing via native advertising world in a big way. Brand are clamoring to get their video storytelling in high gear as others have jumped on the bandwagon long ago. Today we’re undergoing a forced feeding of video on Facebook with their Foie Gras auto play strategy and every post in our feed has videos popping up. (Original post on SEJ)

No wonder controversy has peaked with talks of YouTube being second fiddle and the emphasis of video on the other big social platforms. This video hypnosis strategy is being perpetuated by brands as static visual display gives way to 30 frames a second story telling. The mobile consumer has put in motion an explosion of new tools, data insights, and techniques that brands must embrace to be competitive. There’s no question video is not only killing it for the brands but every person is a video content author now. This is changing the way content is being created, shared, and consumed.

In a previous post, 5 ways to weaponize your mobile content marketing via native advertising, I addressed the channels and solutions brands must consider to scale their content marketing. Recently, major bets have been placed, such as Yahoo acquiring BrightRoll for $640MM and Fox acquiring TrueX for $200MM, making the importance of mobile video to the ad machines clear. Mobile, video, and native advertising are top priorities, according to top ad executives. Consumers have an insatiable appetite to consume mobile video, as described in 5 Electrifying content marketing methods via native advertising. Now, the stage is set for mobile video and native advertising to erupt in the digital ad landscape.

Here are a Few Points Bolstering Mobile Native Video

Disney Planes Mobile Native Video

iPhone simulator screen shot of mobile native video of Disney Plans Fire & Rescue. Photo/ Screen shot 12/05/2014 www.mamiverse.com

  • Native advertising hyper growth: From 2013 we have had a 29% growth with eMarketer projecting $3.1 billion in spend. Publishers are holding the fort, like Forbes and LinkedIN Pulse with their mobile app.
  • The mobile platform is ripe: Smartphones are fueling this mobile video growth, powered by higher bandwidth on wireless networks, broader wi-fi access, incredible processing power, monster memory, high-definition screens, HD cameras, and killer optics. There are also a plethora of video editing apps making it easy to create and deploy high quality video on the spot and distribute it with just a click.
  • Longer-form video is desirable: Consumers are shifting to rich experiences with greater tolerance to video advertisements. Greater than 20 minute video content grew 86% year over year and shorts from less than five minutes all the way to 20 min clicks experiences a 22% growth reported by FreeWheel.

We have now entered the trifecta of mobile, video, and native advertising, creating a great opportunity for new mobile native video delivery mechanisms that would work well in the confines of editorial content and optimized over many form factors. As this popularity builds for mobile native video, the brands and content creators who streamline delivery will ultimately win.

Advertisers obviously value a richer and immersive storytelling experience. As more publishers and brands move to native, they are shifting from short pre-rolls to longer form content. Facebook has fully capitalized on this movement with 53% of its revenue from its mobile advertising and recently released a Premium Video Ads product. There is lots of news and quotes from experts around the move of content consumption on mobile. Here we highlight a sample set from a recent campaign running mobile native video ads:

The consumer is hungry for great content. The right placement of mobile native video makes a formidable strategy. In the Disney Planes case study, mobile native video produced 70% higher CTR over the desktop native unit of 26%. With 66% mobile users being more likely to interact with a video than those on a desktop demonstrate why there is some much talk on mobile first strategy . Consumers are highly trained now (like a Pavlovian dog) thanks to the many video apps and video enabled feeds.

Mobile vs desktop comparison running mobile native video. Mobile had a 66 present increase in engagement. Photo created for post Chase McMichael

Mobile vs desktop comparison running mobile native video. Mobile had a 66 present increase in engagement. Photo created for post Chase McMichael

When a video ad appears prompting interaction, consumers are more likely to participate due to the reward of great content. This drives the higher share volumes we see on experience based content. These results are very encouraging for brands developing cross-screen campaigns.

Trends in Video Ads on Top Brands

Analyzing thousands of brands and their video posting behavior along with consumer interaction creates unparalleled insights as to what brands need to do, and the level they must play at to be in the game of mobile native video.

Top 25 brands share ratio to post

Top 25 brands and media companies with high video posts to share ratio. Photo: Created by Chase McMichael

Here, we compare top brands and the volume of video they are creating along with the engagement on those videos. Don’t assume video plays is the best measurement of video effectiveness. Brands are looking for full consumption and engagement resulting from the content. The ratio of shares per post has been found to be a great measurement of comparing a brand’s consistency and quality factors.

The share per post ratio over the past year shows Fox News, PetFlow, and BBC News lead the way along with traditional video based TV news properties dominating the social video landscape. Where Women Get It Free is head to head with NBA! Those media outlets engineered to naturally produce video content will continue to see an increase in their dominance.

Top 25 brands like ratio to post

Top 25 brands and media companies video posts to like ratio. The top share ratio brands don’t match with the top likes ratio brands. Content that achieves high shares is most valuable. Photo: Created by Chase McMichael

There are challenges at the moment with video chicanery such as autoplay and paying for plays that skew the real numbers, however, people commenting, liking, and sharing video provides hard attribution to go from. Be careful on plays, there are so many services out there that will get you PLAYS for cash, like the old days of buying friends and followers, but it’s hard to fake shares and authentic comments. Unfortunately, we’re seeing ad fraud in the billions and that’s coming to mobile native video. Facebook autoplay still playing an ad when hidden under the fold will not build confidence.

What’s it going to take to be in the top mobile video advertising game? If your brand is among one of the industries we have analyzed, the bar has been set very high.

The chart above provides a view into the amount of content required (video posts) and the reach / share levels of engagement required. The main takeaway question is does your CMO or CEO know the commitment level to be a top player in video?

Translating Big TV Spend to Mobile

Recent deal such as Target and Best Buy with True[x] clearly shows marketers are moving media spend from banners to the native ads. The data don’t lie with the response on native over social networks and other publishers preferring in context rich media, video, and visuals as part of the ad experience.

Interstellar Native Unit

Example of native mobile video optimized to support responsive design. Screenshot 11/23/2014 www.socialmoms.com

Likes on video is not the same action as sharing to your friends. Consumers willing to stamp their name on something with greater emotion tend to share or comment. That is why these tend to be the best hard attributions besides click to purchase. The WWE, UFC, MLB, and NBA skew towards male users where Women Get It Free, PetFlow, Prez Hilton, and The Voice skew female. It’s well know that females share more, and the data on video proves that to be true.

There has been a great deal of hullabaloo and hype about how Facebook has passed up YouTube, and how Yahoo is overtaking Twitter in mobile ads. Some have claimed it’s all lies. The reality is, consumers are sharing video in a big way. In fact, as the data has shown, there are more shares than likes on videos.

Video Usage Analysis on Mobile Native Video Advertising

Here are five ways brands can leverage these 2015 trends that will define high performance content marketing efforts and help brands get a jump on their mobile native video advertising strategy.

Agile Marketing and Real-Time Tool Explosion

The smart brands have created newsrooms and command centers, driving content creation to the next level with full on video production. Data will be a driving factor to the competitive advantage. Knowing what consumers engage with and what they click on is a gold mine. Many technologies enable you to understand your competitive content landscape.

Mobile First

Over the last four years, we have seen a steady increase in mobile activity due to native apps and responsive web content. 2014 was truly a breakout year with many experiencing as high as 60% and 70% shift to mobile. In 2015, brands must focus on useful mobile experiences for content and commerce. With 66% increase in CTR over desktop, it’s easy to see why the ROI justification on mobile is simple. Think of what works best for mobile and where your consumers are consuming your content. Content designers must realizing that not all consumer are in front of a TV. What are you looking to achieve on mobile and is the video designed for the mobile experience?

Mobile Video and Social will Demand TV Budgets

Mobile, social and video are the hottest trends and will commandeer big spends as the quality and complexity of story telling continues to rise. The consumer is mobile and the experience has to shift to the medium where they are at making the challenge of the creative fit the form factor.

Engagement and Viewablity Videos Views

Marketers are increasingly being pushed for verifiable results over the simple view or play. Viewability is now a must-have for brands to be assured their content is being seen and engaged with. Next year, it will be all about video engagement. We’re quickly moving beyond YouTube and seeking out customers in their native environments.

Optimizing Video Ads for Device and Thumbnails

Marketers would be wise to customize ads for each device, because those type of ads drive the best results. This is back up by data we see and also by a study from video advertising firm Innovid, which analyzed video ads over Crackle’s network consumer base. The study combined pre-roll and interactive video ads across auto, retail, CPG, entertainment, and travel for one-year period on desktop, mobile, and iPad. Optimized ads can deliver a six times increase in engagement, seven times boost in click-throughs, and a 25% rise in completion rates, the study reported. The thumbnail image is one of the most critical images because it is the first image consumers see. Studies show optimizing the thumbnail image can increase CTR’s from 5 to 30%.

A new startup called Neon coming out of Carnegie Mellon University is using advanced video analysis techniques to determine what thumbnail or text in combination would yield higher CTR. Working with IGN results have even gone as high as 59% increase on highly customized thumbnails based on cognitive sciences. Overall, brands will see the best results when an ad is optimized for the screen and the thumbnails are well crafted. Brands must prepare for the multi modal customer and engineer for omnichannel to stay in this high stakes poker game.

Facebook Disruption

Facebook now how Premium video along with the auto play and pushing video over all other post their drive for dominance is self evident if you’re on Facebook. For Facebook this was always in the plan to debase YouTube video dominance. Morgan Stanley projects Facebook video ads could to be worth $1 billion this year and rocketing to $5.5 billion by 2019.  And now Facebook is creating a YouTube like experience going head to head with the more static non social YouTube. We could be witnessing a move over old school video channels.

Viewability and attention as the key measurements now over just clicks are views.  Brands what to know is their ads being engaged with. Google recently announced 56.1 percent of ads on the internet are not view-able.  See infographic too.  A revolution like the editorial content mixing with ads “native” is now happening with with video where rich media meets polished ad copy all engineered as entertainment. As mobile native video takes hold there will be a best in class native ad structure. The melding of native ad content and video will give rise to a more interactive experience customer want to watch, willing to share and engage on.

Your Next Big Move

Over the last three years growth in brand mobile videos has skyrocket with 73% from 2013 and sees to top over $4.4 billion in 2018, and mobile video ads will grow almost 5X faster than desktop. We will see a migration of desktop ads to mobile, which is a no brainier. And mobile video is just add water for advertisers’ video ad assets created for larger screens.

The number of videos does not extrapolate to overall levels of engagement however. It’s easy to see the growth of top brands and their acceleration will continue as long as consumers keep consuming. Democratization the video creation and dissemination process has lowered the barrier for any size brand to enter and establish a video footing.

Facebook Mobile Ads Are Brands’ Best Bet for Holiday Shopping Season -With the holiday shopping season fast approaching, new research from advertising technology company Spongecell indicated  mobile ads are the way to go. Loading video is now as easy as taking a picture. If a picture is worth a 1000 words with 30 frames a second and audio to boot makes 1,000,000 words or so, Right? Video Selfies funding demonstrates even VC’s are ready to capitalize on the fastest-growing sector of mobile advertising and is attracting big brands looking to leverage their heavy television media buys.

We’re quickly moving past the 15 and 30 second to full-length creative content streams. Mobile ad spend is growing rapidly, but brands who invest in mobile-ready solutions now will win. By getting ahead of the trend, brands will be able to understand, experiment with, and become market leaders in mobile advertising.

Tell us in the comments how your integrating video into your content marketing and what’s working.