Does Length Matter? Initially, this question might evoke thoughts only appropriate for your spam inbox. Obviously, we aren’t going to write a long post here on that meaning of that question — but we do find ourselves uniquely poised to answer the very same question about business video, with tons of data from business videos of every type at our disposal. The graphs below summarize literally millions of data points from the last couple years (since our last post about this topic in 2009).

The above graph (let’s call it Exhibit A, because it’s fun to feel like a detective) is the most consolidated display of the data, with one data point for each video length range, on the x-axis, with the average % viewed for videos of that length on the y-axis. Basically, it’s representative of the video engagement number within Wistia (so you could compare your number with the number for that length on this graph to see how well you’re doing compared to the average!). This graph tells us that shorter videos are better for getting people to watch the whole thing. After all, most business video is created to serve up a pre-packaged message, so the longer the video, the less people will watch. It’s also noticeable that after a certain point the engagement average flattens out — so there’s not a major difference in engagement for a 4-minute versus a 10-minute video.

On to Exhibit B, where the x-axis represents the percentage of a video viewed (think of each line as the average engagement graph for a video of that length range in Wistia, one of the bars of Exhibit A over time, with each line representing the average video for that bin, with the lengths normalized), and the y-axis represents audience engagement. In this case, you could compare the engagement graph line of your own video to the appropriate line of this graph to compare yourself to the average.

A possible takeaway from this graph would be to organize the content of your videos journalistically, placing the most important, essential information first, then following with supporting details. For longer videos, notice that the dropoff at the beginning is extremely steep; it seems that most viewers decide quickly whether or not to watch, and once that decision is made, they tend to stick around until the end of the video, when they detect that the video is wrapping up and another drop off occurs. For this reason, if you’re using a post-roll call-to-action, you might want to consider a harder stop to your video, rather than a meandering wrap-up — this will ensure that more viewers stick around to see your CTA.

Exhibit C takes things one step deeper: this is the raw data that went into creating the above graphs. Each frame in this animated graph represents one of the time ranges from the above graph. Each of the faded lines is the engagement graph for an actual video, while the average line for that video length is in orange. Again, the x-axis represents percent viewed and the y-axis represents audience engagement.

The interesting thing to notice here is the wide variation even for videos of the same length. The variation tends to be more wide at the beginning, tightening toward the end (again hinting that people decide whether or not to watch pretty quickly). There are definitely outliers, but all in all, longer videos see a tighter overall distribution, where it’s safe to say that if you’re doing 30% versus 25% engagement on average, for example, you’re doing pretty well.

The main takeaways from our first “Does Length Matter?” post still hold true: overall, shorter videos are more engaging than longer videos. You should strive to make your content as concise as possible to achieve the highest engagement. If your message is more complex, feel free to give it the time it deserves, but understand that a major chunk your audience won’t make it to the end of the video and consider front-loading your video with the most important information at the beginning.

If you’re thirsty for more, we’re hosting a webinar on video length on Thursday, May 17!

We’re huge fans of measuring everything about your web video, but analytics are pointless unless you know how to read them to better understand how well your video is working and, more importantly, how to improve upon it. While we know you’re all (almost too) smart and capable of reading your analytics, we thought it might be nice to include periodic examples on our blog, adorably entitled Stats Snacks, of how we and others have personally used analytics to improve our video (or maybe even where we’ve messed up, even though we totally don’t mess up at all, ever).

In this particular morsel, which some of you might recognize from a recent webinar, we started with a customer testimonial from our friends at Litmus, an awesome email campaign testing and tracking application. In the first iteration of the video, we asked for them to provide the context of who they are and tell their story, then talk about how they use Wistia.

The analytics for that particular video are the browner portion of the graph below. You can see a pretty big drop off at the end of the video, when we were wrapping it up, showing our logo and pitching Wistia. Overall the engagement was okay for a 1:30 video, but on the lower side. We decided we wanted to mix it up; because we’d shot testimonials with different companies, we re-edited the video so that instead of being a testimonial from Litmus, it was interviews with four to five different companies, interviewing them about why they would pay for video hosting. The graphs look pretty similar — there’s still a drop off at the end, but it turned out the second video (featured lower in this post) was significantly more engaging than the first.

Instead of going back and re-editing the first testimonial, as we could have done, we wanted to take the opportunity to have the testimonial be more focused and work with other content we’d shot. We didn’t shoot any new content, just combined footage we already had.

The point of all of this? Whatever analytics you’re using, the numbers aren’t necessarily going to give you that final insight. You need to look in context of what you’re actually doing to see what caused the boost. In this case, we think the newer version was more engaging because more was packed into a smaller period of time to hold attention, hitting key points over and over (versus the first video that was a slower narrative video about Litmus). Additionally, the new video was placed right on the front page of the Wistia website. In that context, the question “Why Pay For Video Hosting” was probably a question on visitors’ minds — so the video aligned context to content, making the video more engaging.

By closing the circle with analytics and improving our own videos, we can apply our learnings to whatever we do in the future. If you have any stats stories that you think would be a good snack, send Alyce an email!

On April 12, we held our second webinar, Using Analytics to Make Great Web Video! Compared to our first Intro to Video Marketing webinar, we went a bit less technical, this time using two cameras (one on a tripod and a GoPro in the background) and just one microphone. This was Brendan’s first webinar! We covered three examples of our own videos, using analytics and engagement graphs to show what we’ve learned from our videos. We hope those who tuned in found the webinar helpful!

You can catch up or re-watch with both the video and slides below.

Here are the links of interest from this webinar:

If you have good examples of your own, we’d love for you to share or to help you analyze your videos in a future webinar! Contact Ezra (ezra@wistia.com) if you’re interested.

This new engagement graph separates watches from rewatches (the former graphs were basically the top line of this graph). The first view by an individual of any part of the video is counted in the blue portion of the graph, while any subsequent views are counted in the orange (so take note: 16 views worth of orange could be one person watching 16 times, four people watching four times, or 16 individual rewatches — you can come to further conclusions in the individual heatmaps).

With the new engagement graphs, you can tell more than ever which parts of your videos are the most engaging, whether it’s because they’re the most interesting and most confusing, and continue to improve the videos you make in the future based on this information. Happy analyzing!

To access IP Filtering now, go to Account Dashboard > Embed Settings and enter the IPs you’d like to exclude!

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When we launched the new stats, we decided to try another thing that was new for us: instead of only explaining the new feature on a feature page or in a blog post, we also added a popover video inside everyone’s accounts so that no one would find themselves nose-deep in stats with no idea what was going on. We wanted to make sure it was as easy as possible for everyone to find the right resources and know what was different — without any startling surprises — and hopefully reduce support requests on our side.

The window had a quick (and very engaging, apparently — 88% of people finished watching!) video introducing the new stats, then offered two options for viewers: to close the popover and explore or to visit the feature page:

Because of our new identity tagging feature, we could see that 34% of people who watched the popover video within their accounts then made it to the feature page to watch additional videos and learn more there before engaging with the new feature within their account. In an email, a 34% click-through rate would have been absurdly high. We were able to use identity tagging to see how people viewed all of the videos, and how those views related to one another, on an individual basis. We didn’t see any noticeable increase in support requests with the Stats 2.0 launch – something that we did notice when we launched SuperEmbeds, which we didn’t use a popover for.

Being able to see what our viewers watched, by individual, in sequence, allowed us to make connections that would previously have been a mystery. Have you made any interesting new connections yet using Stats 2.0?

Today, we’re really excited to announce the birth of a new family of features that have been in the works for quite some time. If you haven’t viewed the feature page yet, you can learn more about the basics of Stats 2.0 there. Here, we want to explain the philosophy behind these new features, why things are set up as they are, and why it took time to make these new analytics part of Wistia.

When we started with video analytics, our first big feature was heatmaps. The earliest incarnation of heatmaps just showed whether a viewer had watched a certain part of a video or not — an area was either green or white. Next came colorized heatmaps that displayed more layers of viewing information, with areas that were rewatched showing up as shades of yellow, orange, and red. People really liked this, and with the addition of engagement graphs to summarize this information on a video-by-video basis, we basically reached “Stats 1.0,” the stats Wistia has been offering for some time now. Since then, we’ve made small tweaks based on user feedback, but many higher-level changes ended up in the big ol’ bucket known as “Stats 2.0,” and as that bucket became deeper, it became an increasingly daunting project to actually tackle. We’ve been gathering all of this information since the very beginning — you can view your stats starting from the inception of your Wistia account — but it was important to make sure those numbers made sense.

In the end, we’re happy we waited until now to launch Stats 2.0. Instead of working blindly on adding features that just sounded good, we were able to base our decisions on tons of unique feedback and information that only we have to create not only the next generation of stats for Wistia, but also a whole new way of approaching video analytics in general.

Our biggest worry was losing the simplicity of the old Wistia stats. Stats 1.0 didn’t offer an overwhelming amount of information, but what it did offer was carefully selected to be as powerful as possible while making it almost impossible for users to get lost. One of the biggest problems with all-encompassing stats tools like Google Analytics is their complicated nature — in order to get exactly what you want, you have to put in a lot of effort, and while you’ll eventually be able to view your data in the precise way you need it, there’s a much higher learning curve. We wanted to put a lot more power into our stats without complicating the simple flow we were proud of. We wanted to focus on what’s valuable so we wouldn’t dilute what’s really important with clutter.

One big way we’ve made stats easier to browse is that the stats area now mirrors the main area of the Wistia app, with project-level organization and project-level stats. We’ve also made several small changes to existing features to make them feel less cluttered. Hovering over certain areas, such as heatmaps, displays more information, but only when you want it, with everything contained in the rectangle. On graphs, axes are not labeled until mouseover.

Stats 2.0 is playful — you can interact with almost any element of your stats and access deeper layers of the information you care about, but we worked hard to keep the interface intuitive. Another fun fact: we built our own graphing library for the Trends stacked area graph — we’ve played with a lot of other libraries but we wanted this one to be suited perfectly to our unique task.

As always, it’s important to us that an audience isn’t just an amorphous blob. For some companies, the aggregate numbers are most important, and for others, every individual viewer counts. You’ve always been able to view heatmaps, but now, you can also track individual viewers across all of your videos. See who’s the most active and identify who’s been engaging the most with your video content.

We hope you enjoy playing around with Stats 2.0! Or, you know, not playing and being really, really stoic and serious. Keep the feedback coming, we’d love to hear what you think!

Get Smart Content is a content-targeting platform that enables marketers to provide website content and messaging that is tailored to their visitors’ interests. You can follow them on Twitter at @GetSmartContent.

Get Smart Content is a big proponent of data-driven marketing. The Wistia team is all about analytics and that’s why we get along so well! It’s also why Get Smart Content and Wistia are teaming up on an integration scheduled for completion later this month.  Soon you will be able to combine Wistia’s powerful video tools and Get Smart Content’s content personalization technology to show the right videos to the right visitors at the right time on your website!

To kick off this integration, Get Smart Content wanted to share our thoughts about audience segmentation and how content can be personalized to meet the varying interests of your different visitor types.

For most businesses, your website visitors are a diverse group of people who are driven by varied interests and have different levels of experience with your site and brand. How you interact with your website visitors is key to cultivating and retaining customers. But without a phone conversation or live chat, how do you personalize lead interactions to better engage and connect with your audience?

By looking at a visitor’s online behavior and interests, you can tailor your website content specific to your visitors’ needs. Being extremely relevant creates a natural connection with your leads and thus increases the likelihood of conversion. Here at Get Smart Content, we can help you segment your audience into meaningful groups and give you the tools to personalize your website content to each audience segment.

See below for an example of Get Smart Content’s audience segmentation and content personalization in action!

Not sure how to analyze your website’s audience? Check out this video we made, with a little help from Wistia’s great video hosting solution, that gives an overview of our free audience segmentation tool we call the Opportunity Report.

Here are seven simple categories which we typically recommend for audience segmentation. Some categories will be more or less relevant depending on your type of business, but we have yet to find a business that can’t benefit from at least a couple segmentations:

1. Geo-targeting: the geo-location of your visitors.
2. Keyword: the keyword search made by your visitor tells you what they are looking for.
3. Previous Engagement: how the visitor has previously engaged on your site – what actions they have taken.
4. Mobile: defines what mobile device a visitor is using and allows marketers to change their messaging depending upon the device.
5. Social Referral: how has the visitor engaged with your brand through social media.
6. Time/Day/Date: provide content based upon the time of day, day of the week, or date.
7. Total Visits: the number of times a visitor has been to your site.

You can generate your own Get Smart Content Opportunity Report to see how your different audience segments are performing and where you might be missing opportunities to connect.

Be on the lookout for more details about the upcoming Wistia & Get Smart Content integration!

Want to be part of the beta launch? Sign up here!

URL shortening services like bit.ly are more than just a method for making messy-looking links more pretty. You can also see how many clicks a link is getting from a particular location, and you can compare the number of people finishing the video (from Wistia’s analytics) to the number that are clicking your post-roll links. Services like bit.ly are a really easy way to track which paths people are taking to a particular page.

Another thing that you can try is using UTM codes (a.k.a. Urchen Tracking Module codes), which can be tracked easily in Google Analytics (and you can even combine their power with bit.ly tracking by putting UTM code URLs into bit.ly!). You can use Google’s URL Builder tool to filter analytics by UTM categories like source, medium, and content. For example, if you have a video in a few different places, you can give each post-roll URL a different “source” code. Multiple versions of the same video could be differentiated by different “content” codes.

Another added benefit of using UTM codes with Google Analytics is that you can track beyond just the initial call-to-action click and keep track of whether people are actually converting — signing up for trials, filling out contact forms, etc.

Regardless of what tools you use to track your users, it’s hard to argue against connecting the dots of how video-watching is helping you to create prospects and increase conversions.

I’m proud to say that I’ve recently shifted how I use Facebook. I transitioned out of stalker mode and into business mode, using the platform to showcase my latest video work as CRLVIDEO. When I make a new video that I’m particularly proud of, I first email my close friends directly, then tweet it, then embed a Wistia video on my Facebook wall. Sharing my work on Facebook may be self-gratifying, but I tell myself that it’s building recognition for CRLVIDEO and what I do.

Every year (since 2005), I edit a short “year in review” video for my wife Courtney for Christmas. Nothing special, just some quirky music with pictures and video clips from whatever we did that year. I consider it to be the most important project I work on all year. No matter how many other projects I find myself trying to wrap up by the year’s end, I always love finding time to do at least this one very important project.

I followed the same video sharing progression I use for CRLVIDEO after I completed (and gifted) this year’s 2011 Christmas video. I sent out a few emails, tweeted it, and posted it on my (and Courtney’s) Facebook walls. Like the analytics junkie that I am, I checked my Wistia stats on the video a few days after.

I was shocked by the numbers. An extremely personal video. Made up of personal memories. Featuring pictures and video of only my wife and me. Garnered a metric of 91% engagement across everyone who watched the video. Umm…what? We’re not talking about a 10 second video here. This was a 3 minute and 10 second video… one of the longest I’ve created in over 2 years. 67 people watched an average of 91% of the video. 91% of every vomit-inducing, sappy, love-drenched frame.

With this video, I reached a new milestone. The 2011 Christmas video became the most engaging video of all of the videos I host on Wistia. Why? I don’t think it’s because it’s my best video. I think it’s because the video offers a privileged look inside our lives. We’re not living any differently than a lot of other of our friends. It’s the sheer curiosity and downright creepiness of everyone in our Facebook network that led each person to click play and watch all the way through.

Not creepy enough for you yet? Check out the spike in the aggregate graph at around 2:15. People re-watching this section like woah. Why? Because it had a joke picture of a joke gift from two of our closest friends that fake alluded to Courtney being pregnant. Guess that explains the e-mails from people we haven’t talked to since high school asking when the baby is due and if we know what she’s having!

There are a few lessons I learned here:

• Facebook is a creepy yet intriguing means to share your work.
• Facebook can easily fake people out and make em’ think your wife has a bun in the oven! (p.s.: She doesn’t.)
• Analytics don’t lie (and can sometimes creep you out).
• It’s okay to make video personal — relatable techniques can keep viewers engaged!