Insights in Motion: Data Requirements for Video Platforms

Having explored data requirements for the central systems of a learning ecosystem, the LMS and LXP, let’s turn to the products you might bring into your ecosystem to enhance those core platforms with additional functionality.

Video platforms turbo-charge your training capabilities and can generate a lot of useful data about what learners are watching—right down to the level of where they’re pausing, skipping, or rewatching. In this post, we explore the data you can expect from your video platform and what to ask your vendor in relation to data requirements.

What’s a video platform and how does it fit in a learning ecosystem?

A video platform is a learner-facing platform specifically designed for delivery of video content. While your LMS or LXP may be able to link to or even embed videos, dedicated video platforms tend to provide additional functionality to the organization. This is in terms of hosting and streaming video content, and to the end user in terms of player control.

Video platforms also may offer advanced video functionality, such as embedded quizzes or branching videos. Some video platforms collect granular data about video interactions, and some platforms may include reporting on that data as well as a data export for more granular reporting and analysis in a learning analytics platform.

In organizations where the majority of learning is delivered via video, a video platform can be the primary learning platform and replace the LMS and/or LXP. In most cases, however, video will just be one medium of several.

In these cases, the video platform can be integrated into the LXP and/or LMS in order to deliver video content to the learner in the context of their primary learning platform.

Note: In some cases, vendors have extended their video platforms to support other kinds of content. As a result, they effectively cease to be a pure video platform and become an LMS or LXP with good video support. Learning platforms sometimes have fairly complex product evolutions and can be difficult to classify!

Video data requirements and what to ask your vendor

What data should I look to pull from my video platform for reporting in the LAP?

Some video platforms include impressive reporting capability—especially concerning analysis of the videos themselves—but they tend to feature only high-level reporting when it comes to looking at users.

Bringing data from the video platform into an LAP not only means that all the learning reporting can happen in one place, but also that the video data can be combined with other data. This includes your organizational hierarchy, allowing for much more segmented and granular learner reporting in relation to video interactions.

Ideally, data about learner interactions can be streamed in real time to the LAP from the video platform via xAPI—assuming the video platform has a good xAPI implementation. Where this is not possible, it may be possible to extract the data via CSV instead.

At its core, a video platform plays videos and so any related data should include details about playing videos. To support content analytics, it’s important that this data includes not just high-level events, such as the learner watching a video, but more granular events—such as pauses, skips, and resumes.

It is also helpful if the data includes information about the learner’s progress through the video, so you can get a sense of how much of the video has been watched.

We created these example reports to explore how attendees at our Insights conference interacted with a pre-conference teaser video we sent them. We can see which segments of the video were watched and where viewers skipped from and to in the video.

The platform may include additional features, such as the ability to:

  • like, rate, or comment on content; and/or
  • search or organize videos into collections.

If these features exist, track them to see to what extent they are being used. (NOTE: As these features are similar to an LXP, you may want to read our previous blog post about LXPs for more information.)

What does the data tell you, or what kind of things can you learn from it?

Video platform data can be used for video analytics and learner analytics.

From a video analytics perspective, data can be used to analyze an individual video (e.g., seeing where people are most likely to pause a video or at what point people stop watching). This can be useful to inform the design of future videos. If there is a particular feature that causes people to switch off, avoid including that feature in future content!

Data also can be used at a higher level to compare videos across the platform. For instance, you might want to:

  • Report on all the training videos with low usage so you can remove or improve them.
  • Identify popular videos, so you can apply similar techniques when creating new content.
  • Look for other “outlier” videos, such as the most paused videos or the most rewatched videos, to find out what makes them stand out and why.

From a learner analytics perspective, the data also can be used at micro and macro levels.

At a micro level, you might want to produce a learner or team transcript of videos watched so managers can see how their team is using the platform.

At a macro level, it might be useful to compare usage across different parts of the organization or look for trends in what different groups are watching.

What questions should I ask my vendor about getting the data out?

Most of the leading video platforms tend to have good xAPI tracking already implemented and in regular use by some of their major clients (which means it’s also well maintained). So, there’s really no good reason to settle for less when choosing a video platform.

We recommend that you require good quality and well-maintained xAPI tracking when choosing a video platform. (Take a look at Kaltura’s xAPI documentation as an example of the events and data that can be tracked, or check out our documentation on reporting that is possible using Instilled’s xAPI data.)

What if my video platform doesn’t support xAPI?

If you already have a video platform that doesn’t have a good xAPI implementation, or decide to go against our advice and get with one that doesn’t (don’t worry, we won’t take it personally), then you’ll need to go with plan B for data extraction: CSV imports.

In this scenario, you should make sure the data you need is available for CSV extraction, as well as follow all the advice in the second post of this series relating to extracting data via CSV. For video data in particular, be careful to check that the data includes a record of every time the learner interacted with the video so you can report on which videos, and video segments, are watched multiple times.

Video platforms and your learning ecosystem

What are the benefits of combining video data with other tools and systems within my ecosystem?

Some major video platforms have impressive built-in video reporting functionality, so why would you want to pull the data out into a learning analytics platform for analysis? There are three key reasons:

  1. Learner analytics segmented by organizational hierarchy information. Most internal video platform analytics focus on video analytics or high-level learner analytics and do not make use of organizational hierarchy information. This means that it is only possible to report on the organization as a whole—not by discrete segments.
  2. Combining data from multiple sources. The video platform’s reports can only report on data about its own videos. Aggregating the data from multiple platforms in an LAP enables you to report on all your learning data together.

    For example, perhaps you want to compare usage of the platform’s videos with YouTube content accessed via your LXP. Or, you want to measure progress toward a digital credential that includes training from the video platform and others systems. These kinds of reports require data from multiple systems—including the video platform.
  3. All your reports in one place. Aggregating all your learning data into an LAP means you can have a single system to see all your learning reporting side by side, rather than having to log into multiple systems.

    The video platform’s reporting will still be useful, especially for administrators of that system, but for those involved with multiple systems, having all the reports in one place is incredibly helpful.

As with other platforms, the key to mapping data together is to make sure that a single learner can be tracked across multiple platforms by having:

  • a common learner identifier across all platforms, or
  • a collection of identifiers per learner that can be mapped together.

Where the video platform serves embedded videos to another platform, such as an LMS or LXP, it is also useful to be able to match data from the video platform with data from the platform embedding the video. This can provide a useful data check to ensure everything matches up and enables you to see the granular video data in the context of the larger learner journey.

How can you use this data to improve and grow your training programs?

Video analytics data is really important in improving the quality and effectiveness of your content. If people aren’t watching your videos, they’re not having an impact. That’s why it’s vital to be able to see and measure what is and isn’t being watched so you can remove or improve content.

Beyond that, you also need to understand why people are watching certain videos and not others, and where and why people are dropping out of or skipping through the content.

Are the videos just too long? Are there certain elements that turn people off? Is there a problem with the content itself? Or, are there technical issues preventing people from watching?

The Brinkerhoff Success Case method can be particularly helpful here. Use your data and analytics platform to identify the videos that are particularly successful and explore what makes these videos work so well. Then, identify the videos that are less watched or have high dropout rates; what is it that makes these less engaging?

Alongside Brinkerhoff’s model, broader trend analysis can also be useful. For example, looking at the average time your learners watch before they skip or pause will give you insight into the optimal video length.

Real-World Example: See how Caterpillar analyzed video data from Kaltura to identify exceptionally popular videos each month. This information could then be used to further promote videos that people were finding useful that month, and to explore what it was about these videos that made them successful in order to learn lessons for future content.

How might data from a video platform be useful for compliance reporting?

Required compliance content can be delivered as videos on the platform. This applies to both specific training content, and to content that contributes to a required number of hours of learning.

In both cases, data indicating that learners watched the video, and that they watched all of it, can form part of the learner’s compliance record.

How might data from a video platform be useful for skills reporting?

Three elements that can contribute to evidencing that a person has a skill:

  1. Evidence the person has put effort into developing that skill, such as a record of completed learning or practice hours logged
  2. Evidence the person has mastered the skill, such as successful completion of an assessment
  3. Evidence the person has applied the skill in a real-world context, such as within a work project

The video platform may be able to provide skills evidence in relation to the first point. If you can identify and tag or select videos that are relevant to development of a particular skill, you can then use the data to identify which learners have watched those videos and may be likely to have developed those skills.

This can then be cross-referenced with data about skill mastery and skill application. And you can use this information to evaluate the video’ effectiveness in helping to:

  • develop those skills, and
  • build confidence that learners who watch videos designed around a particular skill actually acquire and apply that skill.

Up Next: Data requirements for survey tools

Video platforms can generate a huge amount of valuable data that can be transformally informative to your video content strategy. So make sure you’re getting that data into your LAP and not missing out! Another tool that can be used to generate really useful data is a survey tool.

Be sure to subscribe to our blog for next week’s post—which looks at the kinds of data that survey tools can capture, and the requirements for exporting that survey data to an LAP.

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What are reporting requirements for your video platforms?

Use this guide to see how you can get the L&D data you need from your video platforms while asking the right questions of yourself and your vendors to get the best results.

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