Today's marketing teams are investing more than ever in producing great content designed to attract, engage and convert their online audiences, but one of the biggest challenges we still face is understanding which content is really resonating with our audience.
Which pieces are holding their attention and actually educating them through the buyer's journey? Ebooks and whitepapers are great, but we have no idea if the person actually chose to consume that content after they downloaded it.
And this is one of the reasons why I'm so passionate about video and think about it as a content marketer's best friend.
It is the most trackable content medium and can give you real-time insight into exactly how your audience is engaging with it. Which parts they're choosing to consume and which parts are losing their attention.
My name is Tyler Lessard and in this Chalk Talk, we'll discuss how you can use video engagement analytics to better understand your content performance and to help you continuously optimize your overall results.
Because video is a centrally hosted, stream-based, medium it affords us some unique opportunities to develop deep insights into how are audiences are actually choosing to consume that content.
But it also affords us the ability to centrally track that information to optimize our content accordingly to update it everywhere it's published and to test how that impacts overall performance.
So, it's not just about informing future content decisions it's also about helping us optimize the performance of our existing assets in field. So, the types of metrics you can track with a platform like Vidyard that are going to help you do this optimization are listed up here on the board.
Now, I think about this through the engagement journey of your video. It starts with the splash screen. What's the click-through rate on that as your front door to your video?
How many views is that video getting? How many seconds are being watched in total? What's the average second-by-second drop-off rate for people who choose to stay tuned to that content? And finally, what's the average engagement time by the end and what can you learn from that to optimize your content performance?
So, let's talk about how you can apply these metrics into a few different models to make sure that you’re optimizing your video performance using these analytics.
So, the first thing I always recommend doing is making sure that periodically you're looking at the macro-level trends around your overall video views and video engagement time across your entire library of videos.
Needless to say, you're always going to want to - up and to the right – kind of trend over time but what you really want to look for here are outliers where you see spikes up or down in the number of views or the amount of seconds being watched of your overall video content.
For example, if at a certain time you see a big spike up dig into that and you might find a video that all of a sudden had a huge number of views or a huge amount of engagement and that video you're going to want to double down on and learn from it
Or the opposite, if you see a big drop in the number of user engagement time perhaps there was a video that was performing really well that got removed or changed or something happened to have a big impact.
So that's going to give you some good macro-level trends to see how your overall video library can perform to its best potential.
Now, more important is actually driving into your individual videos to figure out what's working and what's not.
The first thing, as mentioned earlier, is the splash screen. With a platform like Vidyard, you can split test up to eight different splash screen images for each video in your library.
By doing that you can make sure you're putting the best front door on your video that optimizes the number of people clicking on it to engage in that content.
So now that you've got the most possible number of people watching the video you're going to want to identify hot and cold spots within that content.
This is an example of an engagement chart which is showing you over the duration of the video how many people are staying tuned in and how many are dropping off.
It always starts at 100 percent and by the end of a video, on average, you're expecting it to be around 40 to 50 percent of viewers still watching. A high-performing video retains about 60 percent of viewers. A low-performing video less than 40 percent.
Now one of the important things, in addition to the overall engagement, is looking for hot cold spots. For example, a cold spot here I can see at this point in the video I'm losing a lot of people. So, I want to look at that content and figure out why is that?
Did it turn to a more 'salesy' message? Did we somehow—you know—maybe the content with dragging out too long. What is it that's causing people to drop off there and can I change the content to fix that to keep more people?
The other big thing is helping to identify content that might be too long. Again, if you're less than 40 or 50 percent of viewers making it to the end that content piece is likely too long. So, think about how you could shorten it or perhaps even cut it up into multiple content assets.
Quick tip–people are more likely to watch two 2-minute videos then they are to watch one 4-minute video.
So, look at the data and see what you can learn to make sure you're getting at least 50 percent of your viewers to the end of your video when you're going to have that final call-to-action.
Now the next thing you're going to want to do is start to look at more advanced things like not only is this video getting great reviews, are we seeing high engagement time, and are we keeping people to the end, But is it driving in the desired downstream conversion?
So for example, if a certain video is designed to help you generate new leads you'll want to be tracking how is it influencing lead flow within my marketing automation system. Or if it's designed for a bottom of funnel content, can I find a way to associate it to the amount of revenue we're closing and understand if it's helping me close more deals. Things like that are a bit more advanced because you need to integrate the data into your marketing and CRM systems.
Another thing you can do is test different calls-to-action at the end of your video. So, if I'm now optimized how many people are watching to the end, what do I want them to do at that time? So, I could test different calls-to-action. Maybe I want to have one that's a request a demo button. Maybe another one that's watch another video maybe another that's download this ebook or one to say watch a customer story. And I could test different calls-to-action and see which ones of those get the best results.
And now I know I'm getting the most people to watch my video and at the end, I'm converting at the highest potential rate. That one is something that I get really excited about and encourage you to think about in your own business.
And then finally, related to the first point is looking at how videos are helping to influence lead generation, pipeline development, or revenue which are often the goal for creating video content within your business. Again, to do that you need to make sure that all of this data is being tracked back into your Marketing Automation in CRM and overtime again you'll see trends on which videos are overperforming not just with views and engagement time but in terms of how they're influencing actual pipeline and revenue in the business.
So hopefully this gives you a good sense for how you can use video data to not only understand how many views you're getting and how long people are engaging in your content but to identify areas of improvement to optimize your performance to update your content in the field and continuously improve how you're doing video content.
My name is Tyler Lessard and this has been a Vidyard Chalk Talk.