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Data Snacks | Feb 11
Gabriel Marguglio on June 19, 2018 (last modified on March 22, 2019) • 3 minute read
Content attribution is hard work.
People consume the content you produce in so many different ways, and across so many different channels, that it’s often hard to say whether or not one specific piece of content is the reason someone purchases or not.
Attribution is not a straight line.
Now consider the different ways in which people can view and consume videos.
How much of the video do they watch?
Which parts of the video, if any, did they rewatch?
Did they click any calls-to-action in the video?
Marketing videos introduce a whole new set of challenges when it comes to attributing leads and sales.
That’s why we’ve put together this Data Snack as a resource for getting started. In it, you’ll see how to set up your dashboard, the specific metrics you should track, and what they all mean for your overall content strategy.
*Editor’s note: In addition to being a Databox Premier Partner, Nextiny Marketing is also a Wistia Platinum Partner. Check out their video marketing services here.
P.S. Want help building the dashboard featured in this episode? Contact Gabriel for help.
Hello everybody, this is Gabriel from Nextiny Marketing.
In today’s Data Snack we’re going to talk about how to measure success with video. In this case, we have a dashboard that we created in Databox with data from Wistia and HubSpot to understand the correlation between video and how it affects leads and helps them move through the funnel.
We have a video plays and how they’re growing over time. We also analyze videos by the number of plays to understand which videos are performing better than others. We also add a Datablock tracking actions by videos. At the same time, we want to understand and see an overall view of which metrics we can track to see if and how video is creating an impact in an account.
We also have average play rate, a metric that comes from Wistia and average engagement which helps us to understand how many viewers are clicking on the videos and also how much of a specific video is being watched.
We’re also tracking the click-through rate of our videos, that’s a calculation using Databox, and average time played which in this case is showing as 6%, meaning 6% of people click on a call to action in the video. The average time people watch is 48 seconds, so we probably shouldn’t create super long videos for this account, as an example.
Now, for the lead analysis with video. We created lists inside HubSpot that show leads that have/have not watched a video, and customers that have/have not watched a video.
So this was good enough in the beginning because it was like, “okay, 11% of leads have watched video and then 20% of customers have watched videos.” So that’s a bigger percentage that shows that video has a big influence on customers.
But how can we show this in a different way so that is more impactful in that it actually shows that there is an impact on video in terms of lead generated? Well, we created these calculations from leads that have turned into customers that have watched video and leads that have turned into customers that didn’t watch video. So you can see that in this case leads that haven’t watched videos close into customers at a 7%, while leads that have watched video close at an 18%.
So this is showing us that leads that have watched video close at twice the rate as leads that haven’t watched video.
Of course, leads can watch video after becoming customers, but this definitely shows the correlation between people watching videos and turning into a customer at a higher rate.
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