ABSTRACT
Advertising is an integral part of premium broadcasters’ and video content providers’ monetization strategies. To optimize revenue opportunities, this advertising needs to be personalized accurately for the user and delivered so that it does not impair the quality of a viewer’s experience.
The industry is moving towards server-side advertising insertion (SSAI). With SSAI, a single uninterrupted stream containing both program and commercial content is delivered at a consistent quality, and commercials are personalized for each individual stream at the moment of delivery.
This paper examines the architectures required to achieve SSAI at scale so that thousands or even millions of concurrent, individually-tailored advertising manifests can be delivered in a timely fashion, even for live streamed events.
To achieve this scale, cloud and cloud-assisted software solutions are required.
This paper assesses the effectiveness of this approach and the long-term practicalities of delivering targeted and secure dynamic advertising with high quality of experience.
INTRODUCTION
THE CHALLENGE
There is no question that consumers have come to expect content anywhere, any time and on any device, whether fixed or mobile, on demand.
That expectation does not waiver when it comes to live content – particularly sports. If the consumer cannot watch live events on a large television at home, then the same content should be available wherever the consumer happens to be, preferably with the same functionality including pause and rewind.
To put this in perspective, an estimated 1.6 billion people worldwide watch online video on connected devices (1). 61% of these global consumers watch television and video on smartphones (2).
That number rose to 71% between 2012 and 2015, and is still rising. Video traffic to mobile devices is set to grow at 55% a year through 2020 (3).
Today’s content delivery industry includes relative OTT newcomers such as Amazon, Hulu, and Netflix and traditional broadcasters such as BBC, NHK and CBS, and specialist content companies such as UEFA, which provides comprehensive Europe-wide football coverage.
These organizations all share two key issues that drive operational and technical planning.
First, these companies want to ensure a consistently high quality of experience for their subscribers. Although video delivery may be IP over broadband, the expectation is that this will be akin to broadcast television which more or less “just works,” provides a consistent level of image quality and has very few disturbances today.
This is in contrast to the early days of the internet which relied heavily on text and a handful of still images. Today’s expectations are video-centric with increasingly intense demands for bandwidth to support this.
Second, content providers need to earn revenue from the internet, an idea which runs counter to consumer expectations that the internet is “free.” In the earliest days of the internet, content was provided by hobbyists and people looking to build brands. Now, content has to generate a commercial return.
This is further complicated by the growing complexity and respective bandwidth requirements of the video era.
Today, the costs of delivery are significant: US$0.01 a gigabyte just for the content delivery network (4), not including processing and storage costs. Pay TV operators and content owners are accustomed to traditional linear TV monetization models.
But the internet is an unmanaged network with unclear monetization models. It is also not possible to apply multicasting approaches; over the internet and with the current IP architectures, it is necessary to use “unicast” (one-to-one) delivery and not multicast (one-to-many).
With each piece of internet-delivered video a unique point-to-point connection, delivering video at scale means significant costs. Commercial operations must be able to cover these costs and make a margin.
The most common source of revenues for OTT services is spot advertising.
In traditional linear TV models, advertisers leverage broad demographics and geographies to target commercials for the right country or region. With the ability to more precisely identify the Internet subscriber to a video service through a mix of information gathering and cross-site tracking techniques, there are many ways to achieve a much more personalized advertisement strategy.
With traditional linear TV advertising strategies falling short, the optimal approach to increasing OTT delivery monetization is to get ads tailored at the individual level, based on previous viewing histories and other “big data.”
It is important to note that traditional methods of personalizing advertising fail the quality test because they depend on content coming from one source and advertising from another. In addition, combining the two when viewed on a consumer’s device empowers that user to install clever ad-blocker software that can identify advertising content and skip it entirely.
Finally, video streaming and OTT business model depends upon “impressions” – specific consumer views reported from the client to the player. If there is no way to acknowledge that an advertisement has been played on a specific device, then no money is due from the advertiser to the service provider.
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