SAURABH GUPTA: Hello, and welcome
to Understanding Audience Experiences on Google Cloud
Platform.
My name is Saurabh Gupta, and I'm
a customer engineer at Google Cloud
for Media and Entertainment.
Media streaming has a global audience
with wide variances in device types, user locations,
connection bandwidth, and user behaviors.
Today, I'll be talking about large-scale media
analytics for digital streaming and how Google Cloud's products
can make it easy to ingest, analyze, and get insights
at scale from millions of users watching your content.
This demo shows the power of Google Cloud's
fully-managed Enterprise Data Warehouse, BigQuery,
along with Google Cloud's fully-managed Enterprise Data
Visualization tool called Looker to explore the media audience
experience and answer the question how many people are
finishing their videos.
Over the past few days, members of my team
have been watching various short movies.
Events are emitted from the Shaka player running
in the browser being used for these movie watching sessions.
These events are transmitted to an ingest end
point running on the Cloud Run Serverless platform.
The events are enqueued onto PubSub,
which is a fully-managed global event streaming system.
Dataflow is a unified stream and batch data processing
service based on Apache Beam.
Dataflow uses the events stream from PubSub as a data source
and inserts the data into BigQuery.
Looker is then used to visualize the data
and get meaningful insights from it.
So over to the demo.
Here, you can see a simulation of a streaming services video
library, just as what a streaming
customer might be expected to see in their streaming service.
As a user, I can select any movie to watch.
Before we begin, let us activate the browser's debug window,
so we can see the events that are
being emitted for analytics.
Let me now select one of my favorite movies, "Caminandes."
The video starts playing in the video page
and a sample Preroll ad starts before the video.
You can see the different ad quartile events being emitted.
Let me click on the ad, which takes me to the ad's details
page, where a customer would likely
see the details of the ad they've just clicked on.
Let's return to the video and continue playing.
As expected, other events continue to fire.
Let me mute, and you can see that event being emitted.
And let me pause the video.
And again, all these events are streaming directly
into BigQuery.
So let's take a look at BigQuery.
Here is where the events would land in a specific data set.
I can run a sample query to see these events land
in BigQuery in near real time.
This query shows me all the events
that have accumulated in the past 1 minute,
including the events related to pausing the ad
and pausing the video as I issued them on the player.
All of these events can be analyzed in Looker
using visual dashboards.
Let's take a look at that.
Here is the Media Event Analytics dashboard
that we've created in Looker based on the data in BigQuery.
Up here, you can see the total number of events
that we have logged, the number of sessions
we've encountered this month, and, most
importantly, the viewership funnel,
which shows us the progression of viewership
from one quartile of the video to the next.
So we can see the number of starts, mid-points,
and completion of videos.
We can also see where customers are watching
the videos in a map view.
Additionally, we can also see the device breakdown
and get session level details.
Further down, we can also break down the ad funnel
in terms of how many ads were started,
how many were completed, and how many were clicked through.
We can also get details on a particular asset
and drill into that.
So here, let's select "Sintel" and see
the details of what this specific asset is collecting
from an analytic standpoint.
Again, the data that we got at the coarse-grained gross level,
we can now drill down at a finer level and get
details about this specific video
in terms of how many events were issued against it,
how many sessions, the viewership funnel,
the completion rates, devices, ads, sessions, and also
geographic distribution.
Let us now return to the presentation.
As you just saw, BigQuery and Looker
provide a unified view of data across ads,
players, and other sources of data regarding your streaming
platform.
BigQuery and Looker offer self-service access
to key insights for the various stakeholders,
thus allowing better and more timely decision making.
And since these are fully-managed serverless
components, you're freed from the overhead of managing
infrastructure and can focus on running your business.
BigQuery and Looker make a powerful combination
for streaming media analytics, allowing you to unify analytics
across ads, content, viewers, and other sources,
derive meaningful insights in minimal time
leading to deep understanding of the audience experience
for actionable outcomes.
Thanks for watching Understanding the User
Experience on Google Cloud demo.
Please visit cloud.google.com/solutions/media
entertainment for more details and other solutions for media
on Google Cloud.
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