Datazoom, Inc. Sponsored Content
Solving the Data Standardization Problem in Streaming Video
The Solution: Adaptive Video Logistics
If you aren’t Apple, Amazon, Netflix, Hulu, or one of the other
very large video distributors, fixing fragmentation can be a pipe-dream. Larger companies not only have the developer resources
to cobble together solutions (like linking data records, by user,
across provider data sources), but they have the clout to make
demands on component providers.
Ultimately, fixing fragmentation enables these larger providers to offer a much better video experience, resolve issues,
and retain revenue. But many of the smaller video distributors, whether they are pureplay OTT providers or service operators, must simply live with the problems caused by fragmentation, and continue to struggle with increasing abandonment and
One strategy adopted by video distributors within the industry to resolve the impact of fragmentation has been to outsource
their entire video workflow and stack to third- party providers like
Bamtech Media, Neulion, Verizon Digital Media Services, and
others. Although this can be a tenable solution in some cases, it
completely removes control of the video experience from the
distributor, and places it in the hands of a third-party, governed
under SLA. Oddly, those SLAs are informed by data collected by
that same third-party.
Adaptive Video Logistics is a new approach to fix the fragmentation problem. AVL consolidates data collection from within
the video player to mitigate redundancy, assure veracity, improve
control, and reduce the size of the player and the resources
required. The Datazoom AVL platform not only fixes the video
player fragmentation problem, but it also enables companies to
truly become data-driven. No longer do video distributors have
to wait and analyze data to solve quality-related issues. They can
get the data they need, in the time they need it, over to the tools
which handle it, and make the critical decisions which affect the
success of their video business.
Datazoom: The First AVL Platform
AVL works by collecting data from the video player on behalf of
other technology components and sending individual data elements, with configurable frequencies, to any third-party destination. With AVL, video distributors can have a “master set” of data
that can be plugged into a variety of different visualization tools.
Datazoom has pioneered the industry’s first AVL platform. It is
comprised of four main elements:
• Data capture SDK—the video distributor installs a single
component (SDK) into the video player (replacing other
components used to capture data) that can be remotely
configured in real-time.
• Cloud-based administration—a cloud-based administration portal enables the video distributor to modify which
data elements to capture, at what frequency (including
sub-second real-time), and where to send it, enabling true
• Third-party integrations—multiple third-party integrations,
enabled at the click of a mouse button through the cloud-based administration, provide distributors an easy way to
send data where it needs to go.
• Data Delivery Network — a proprietary network optimized
for lightning fast data capture, deliver, and storage underpins the entire offering.
How to Get Started with AVL
What do you want to do with your data? There are a few things
to consider when choosing an Adaptive Video Logistics platform
and finding a company who can support your requirements:
• What data points are you looking to collect, at what frequency, and at what aggregation level?
• Which video frameworks do you need the AVL vendor
• What requirements do you have from 3rd party analytics vendors to ensure their tools have the data necessary to be useful?
DID YOU KNOW?
In interviews with key video distributors, we uncovered
that the average video player has 14 or more integrated
third-party technology components. These can include
audience measurement (like Nielsen), ad insertion (like
Comcast Freewheel and Google DFP), QoE measurement
(like Conviva and Nice People at Work), and DRM/security.