Optimizing GA Dashboards to Visualize Video Insights
When paired with a real-time source of standardized, video data like Datazoom, Google Analytics transforms from a robust, customer data analytics tool into a cost-free alternative to other solutions for video QoE analytics.
Some media networks are making the change. You can too by following the high-level plan for getting set up with Google Analytics and Datazoom which you can read here.
This time, we’re going to introduce Google Data Studio as a tool for expanding upon the metrics computed by Google Analytics. Google Data Studio provides a platform for customizing the way matrics are calculated in more detail than Google Analytics’ more “out of the box” interface. Pairing a Datazoom + Google Analytics configuration with Google Data Studio yields a query function similar to systems like Splunk, New Relic Insights, and Datadog, which richer, more user-centric metrics can be designed.
Here, we’ll review some steps you can follow to get set up with a couple of basic metrics. You can use the same general ideas to write other useful metrics for your team.
Before we begin, please review and complete our Google Analytics Connector setup steps. This will ensure that you can take advantage of the full functionality of Datazoom’s free trial while utilizing Google Data Studio to understand your data. As well, click here to review some of the important differences and limitations between Google Analytics and Google Data Studio’s free and paid versions.
1. Link Google Analytics with Google Data Studio
Prerequisite: You will require a Google Analytics account and have deployed the requisite Global Site Tag (gtag.js) as per Google’s instructions before you begin.
Follow the steps outlined in this Connect to Google Analytics document. Once you’ve successfully completed the steps, you will see the following screen:
Click the “Refresh Fields” icon on the bottom left of your Data Source page in case there are any new custom dimensions or metrics that need to be included.
2. Creating the Metrics
Prerequisite: You will require a Collector for your video player and have its configuration deployed before you begin.
Prerequisite: You will require a Data Pipe with at least “timeSinceLastFluxData” and “Play Request” selected and enabled before you begin.
Create a metric for the number of minutes watched
Click the + next to “ADD A FIELD”
Enter Minutes Viewed in the upper left under “Field Name”
Enter timeSinceLastFluxData/60000
Click “Save” in the lower right
Create a metric for the number of play requests
Click the + next to “ADD A FIELD”
Enter Play Requests in the upper left under “Field Name”
Enter COUNT_Distinct(CASE WHEN Event Action = “Play_Request” THEN sessionViewId ELSE “” END)
Click “Save” in the lower right
3. Building the Report
Now that we’ve created two metrics, put them to use in a Google Data Studio Report. Click the “CREATE REPORT” button. You will see the following:
Click “ADD TO REPORT”. This will bring up a new report screen. From here you can begin to build visualizations using the metrics just created. Be sure to give your report a name so you can find it easily later. Click “Untitled Report” in the upper left to rename the report:
Click on the “Add a Chart” item in the toolbar and select the left icon under “Table:”
Enter “title” in the search field in the far right under “Available Fields”. Click and drag the resulting “title” onto the green dimension “Medium” to replace it:
Enter “Minutes Viewed” in the search field in the far right under “Available Fields”. Click and drag the resulting “Minutes Viewed” onto the blue metric “Pageviews” to replace it:
Click on the “Add a Chart” item in the toolbar and select the left icon under “Scorecard:”
Enter “Play Requests” in the search field in the far right under “Available Fields”. Click and drag the resulting “Play Requests” onto the blue metric “Pageviews” to replace it:
Continue using the tools in Data Studio to add a Date Filter and begin adjusting the size and layout of the report to your liking.
Click the “VIEW” button in the upper right to be taken to the report.
You can now view the number of minutes viewed by Title and the number of Play Requests in that time period:
Going Beyond
Below are additional examples of the types of reports you can build using the free trial Datazoom account and the free version of Google Analytics with Google Data Studio.
For a bit more detailed overview of these steps, and other resources for using Datazoom in tandem with other analytics systems like Splunk, New Relic, and Datadog, check out our documentation at the Datazoom Help Center.
With these resources, a world of insight is now at your fingertips:
Happy analyzing!
Configuring Google Analytics for video with Datazoom
For those at the beginning of the journey to becoming data-driven, Google Analytics (GA) provides a solid foundation for familiarizing a team with an analytics platform. Traditionally used by e-commerce outlets looking to understand behavior on a website, GA provides real-time feeds, behavioral data, campaign performance tracking and conversion pipelines. Up to certain usage limits*, Google Analytics can be a powerful, cost-free and relatively easy to use tool for video analytics as well. When paired with Datazoom’s video data infrastructure platform, real-time, standardized video data can be routed from the player and into your dashboards. Here, we’ll lay out the five steps for getting started.
These metrics and pre-configured reports provide quicker access to new insights, resulting in, hopefully, fully optimized marketing campaigns driving more revenue.
Google Analytics offers two models (You can check them side by side here)
Standard – *no charge up to 500,000 sessions and 20 custom dimensions. More information here.
Premium “360” – additional charge
Before we proceed, it’s important that you have a Google Analytics account with tracking script configured on one or more webpages. For help, check out the Google Analytics Academy or this documentation here.
1) Set-Up a Google Analytics connector in Datazoom
First, go to app.datazoom.io and either sign-in or create a free Datazoom trial account. Then build your Connector according to this Tutorial or by following the basic steps we lay out here (at our Help Center).
For Google Analytics specifically, you’ll require the Tracking ID associated with your account as well as the Custom Dimension-Metric Index Mapping configuration as detailed here.
2) Build Data Pipe
With Connector in hand, we can now link the Collectors associated with your video distribution components with Google Analytics with the help of a Data Pipe. For help setting one up, check out our tutorial videos.
3) Play Video
Soon after you start playing video, you’ll see real-time, raw video data being captured by Datazoom making its way into Google Analytics under the Realtime/Events section.
4) Basic Metrics.
Once you see data in the Real-time screen, you can begin to build visualizations and reports with the included tools under the “Customization” section of the main Google Analytics screen.
Some examples of the widgets illustrated above that you can build are illustrated below. These “bread-and-butter” widgets are useful starting points:
A. Sessions by Asset Title
B. Sessions by ASN Organization
C. Percent of New Sessions by streamingType
5) Improve metrics in Google Data Studio (next article).
While Google Analytics provides a springboard for getting started with analytics systems in general, it is, after all, designed for e-commerce and not video. In our next article, we’ll dive into how Google Data Studio can make the insights made possible by Google Analytics configured with Datazoom even more successful for managing your video content.
At this point, you’re ready to get started configuring useful widgets to power your video analytics strategy with Google Analytics. Pat yourself on the back once you come to your senses (maximizing the usability of a free tool for a task it wasn’t even intended for can be a little thrilling). Check out a real-world use case here!
But we’re not done yet.
In Part 2, we’ll enhance the usability of the metrics computed by Google Analytics by using Google Data Studio (another free tool) to build crisp, easy to use dashboards to make these metrics even more accessible.
There’s no time like the present to bring clarity to your video data strategies! Maximize the potential of Google Analytics for video when you get started by signing up for your free trial of Datazoom here.
Why real-time data matters
What “real-time” means to Datazoom
The purpose of this article provides a standard for defining “real-time” and the reasons why detailed “real-time” user Quality of Experience data is important for streaming media content providers. Datazoom provides a mechanism to capture detailed QoE data in sub-second real-time. We build our technology to get your team detailed data ‘zooming fast.
For example, some leading analytics claim to provide a “real-time” dashboard view, but your ability to drill down to specifics is limited by their data processing capabilities. Sometimes as much as 30-minutes of delay exists between data collection and your ability to review metric details.
We just lost 50% of our viewers! Why?!”
Startup time just spiked from an average of 2 sec to 12 sec… sustained for the last 2 minutes. All platforms? All apps? Which CDN? Which ISP?”
Authentication latency for MVPD X went up and stayed up. Our users can’t log in!”
Getting detailed, real-time KPI data into the hands of an analyst is important only if it’s actionable. Let’s review some actions a hypothetical Datazoom customer, RadarVid, could take with real-time granular data.
Use case 1: Operations is receiving alerts that indicates an SLA impacting event
Say RadarVid, has an SLA with a CDN vendor which guarantees X percentage of availability. Actionable data, in this case, causes RadarVid to contact the CDN vendor.
RadarVid uses Datazoom collected real-time data fed into their analytics tool(s) to:
Determine if any load-balancing/auto/manual failover service has mitigated the impact on users.
Inform their customer care team of the problem. Providing customer care with details related to platform/app version/region/ISP/Affiliate etc. is a bonus.
Inform their ad sales team of potential revenue impact.
Calculate costs against vendor SLA for that calendar month.
Use case 2: Customer care is getting problem reports with their Direct-to-Consumer product.
“I paid to watch this show/event and I can’t. I want a refund!” Hell hath no fury like a disappointed subscription audience.
There can be any number of reasons for this. In this case, RadarVid’s customer care team would have access to that user’s session data which may include things like available bandwidth, device connection type, application version, ISP and so on. All of this information can help guide the customer care representative on taking a specific course of action.
RadarVid uses Datazoom collected real-time data fed into their analytics tool to:
View relevant data about the problem the subscriber reported
Track similar problem reports to develop trends related to app version/platform/region/CDN/ISP
Use data to inform a course of action
Use case 3: Ad Operations is alerted about a decrease in fill rates during a predicted high traffic event.
With Datazoom, RadarVid’s ad operations team can see real-time data that includes ad creative metrics. RadarVid uses Datazoom collected real-time data fed into their analytics tool to:
Determine if an ad decisioning partner system is suspect
Determine if the ad insertion system is suspect.
Determine if the ad creative is suspect. Confirm that internal teams have properly configured campaigns.
Use case 4: Synchronous data
Leveraging the real-time capability of Datazoom Data Pipes, RadarVid can ensure that disparate data is time-aligned with client viewing experience data. A time data point captured by Datazoom can allow to specifically display other time indexed data that aligns with the time as represented in a live video stream.
RadarVid uses Datazoom collected real-time data fed into their analytics tool to establish the time of the currently viewed video frame versus the reference and react accordingly.
Use case 5: Add new data points
Using the Datazoom Data Pipes configuration tool, a customer can react to platform-specific changes to the types of data points that become available.
RadarVid uses Datazoom collected real-time data fed into their analytics tool(s) to:
Add a newly available platform data point without an often lengthy application update development cycle.
Once the data point is added to the configuration, customers can immediately begin to collect data on that metric.