Is Online Video Growth Really Slowing Down?

The headline on data that Nielsen released last week: growth in online video time spent is outpacing the growth in the number of users.   Growth in total minutes for the most recent period, August 2010-August 2011 (9%) is more than double the growth for users (4%) and higher than the growth for streams (7%).  Thus the average stream is longer than it was a year ago.  The chart is shown below.

This trend in rising length of stream is apparent from data in Nielsen’s January press release…I pointed it out here and noted that the finding makes sense; the audience for online video is becoming saturated while the upside for time spent is tremendous.

According to Nielsen’s June data, time spent for the average online video viewer is 4 hours/30 minutes per month.   Compare that to average time spent per TV viewer at upwards of 30 hours per week and it’s clear that online video time spent has nowhere to go but up particularly as consumers increasingly watch long form content over-the-top on their TV screens.

That said, what seems odd about the chart, not explicitly called-out in the accompanying text, is that growth for all the online video metrics has slowed severely over the past 12 months.   I’d expect growth in users to plateau (as per the chart) and I’d expect growth in number of streams per user to slow as people watch longer streams.  But it’s surprising that total time spent with online video is growing at less than 10%, year over year.

It’s particularly surprising since the base for time spent per user is so low.   To get a sense of how low it is, take a look at Nielsen’s June press release and do a little back-of-the-envelope on time spent per stream.  It’s only 2 minutes/40 seconds, on an average of 101.5 streams per viewer per month.  So, according to this information, the average viewer of online video watches somewhere around 3½ streams per day at less than 3 minutes apiece.   You would think, given Netflix, Hulu, Amazon and other long-form streaming options, that total time spent would be growing at more than 10% off this base.

Another interesting back-of-the envelope:  calculate the average streams per user and time per stream for the three competitors for which the press release provides monthly user, streams and time spent data.    For YouTube (with 108M users): 81.7 streams at 1:55 (mins/secs) apiece.   For Hulu (13.5M users):  46.7 streams at 4:45 apiece.    And for Netflix (8.0M users) 24.1 streams at 21:18 apiece.    The total is tilted toward the YouTube number with its enormous user base, but the Hulu number is surprisingly short and even the Netflix number, at less than half an hour per stream, makes me wonder about what might not be included in the data.

The shape of the Nielsen growth curve is contrary to the one below, for example, from Cisco data cited in ReelSEO earlier this year.   This predicts that bandwidth demands for streaming video will not decelerate but in fact accelerate over the coming years.

I suspect the Nielsen time spent growth curve is affected by a particular aspect of their methodology; they monitor online video activity on their respondents’ computers.    The way I read it:

Online video that people access through games consoles, Internet-connected TV’s, Roku boxes, Apple TV and any other device that circumvents the computer  and ports online video directly to the TV screen are not included.   This is probably not a substantial piece of the puzzle on a user basis or on a streams basis.   But the absence of this piece may understate the growth of time spent per stream with the increasing consumption of longer streams concentrated in non-PC devices.

This isn’t a knock on Nielsen’s methodology – it measures no more and no less than it says it does.  But if we’re really going to understand the total picture of online video behavior we’ll need to get a handle on the whole ball of wax no matter what devices the video streams flow through.

Is Over-The-Top Driving Long-Form Growth?

I’ve made the assertion that people will always prefer to watch long form video on the 10-foot screen as a human truism that will drive how the market evolves.   But I’ve felt a little pang about being so dogmatic since I don’t have data to support it.   And what about the iPad; might it not become a major outlet for watching movies and TV shows?

So it was interesting for me to find this CNET item from November 2010 citing a comment from Netflix CEO Reed Hastings:  the tablet craze affects us very little:

“People prefer large screens,” Hastings said. “So the impact of Xbox, PS3, the Wii phenomenon–huge impact. The impact of the iPad–it’s a great system, but the Mac laptops outstrip the iPad for Netflix viewing by a huge factor.” Long-form video viewing does not translate that well to mobile platforms, he asserted.

So this downplays the impact of the iPad, from a company whose strategy is driving the trends; they would be in a position to know. Though it suggests that the 4-foot screen, in the form of Mac laptops, is a major outlet for Netflix product.

I’d love to see data on number of streams and time spent with online video broken down by screen type – current state and recent growth. My hypothesis: the 4-foot screen dominates current online video consumption by far, but dominates less as length of stream increases, with the 10-foot screen being relatively stronger for longer form and the driver of long-form growth.

Though another paragraph in the CNET article suggests that this hypothesis may be U.S. centric, perhaps true only for a culture in which the TV is the center of life:

Former News Corp. executive Peter Chernin, who joined Hastings on the panel, said he agrees, with regard to the U.S. market, but that the story will be very different in developing markets, where big-screen TVs are less commonplace and cheap tablet devices will soon be readily available.

I’ve also argued that over-the-top will penetrate the home through the path of least resistance, assuming that Internet-connected TV, the simplest connection from a consumer perspective, will be the key driver. But both the CNET article and a June 8, 2011 MediaPost piece citing new data from CBS research chief Dave Poltrack suggest that video game systems are currently behind the growth in over-the-top consumption:

Poltrack contrasted Netflix’s remarkable growth with rather tepid adoption rates of other so-called “over-the-top” TV streaming platforms, such as GoogleTV, Boxee and AppleTV, but said that video game platforms such as Microsoft’s Xbox, Nintendo’s Wii, and Sony’s PS3 have become a major means of streaming TV programming, and that many of those platform users are actually doing so via Netflix.

So…it’s a box that already exists in the household, that’s already connected to the TV for some other purpose that is serving to-date as the main over-the-top conduit. And that makes some basic human sense.

Yahoo Data: “Online Primetime”

Yahoo/Interpret recently published results of an online video study updating a study conducted in 2009.   One of the findings is that online video, which previously peaked mid-day, now peaks in the evening hours; the Yahoo report refers to “online primetime”.   As per their key chart, cited below…

From "Phase 2 Of Video Evolution Revolution", Yahoo/Interpret, 6/2011

This startled me because of both the similarities and differences versus my post of a couple of days ago, Is Your Video Traffic Upside Down.   I argued, for major content sites with a mix of text and video, that people are relatively more prone to watching video on the weekends and in the evenings when total traffic for these sites is at low ebb.   The Yahoo data shows that people are consuming more video in the evenings on an absolute basis.

Of course I was talking about content sites with a mix of text and video while the trend cited above is driven by Hulu and Netflix, video-focused sites.  That may be the difference.   I also wonder, this being self-reported data, whether evening online viewing is more deeply engaged in and therefore better remembered, more likely to be reported in a survey.

But the key data point that that this chart seems to beg for:  how much of total “online” video content is being watched on a computer screen versus how much is being ported to a TV screen?  What’s the trend for this?

What’s of interest to me is how much online viewing is in typical TV lean-back manner, on a big screen 10-feet or so away…versus on a small screen 2-feet or so away.

Because I would think the “online primetime” trend and a “online 10-foot viewing trend” would be happening in tandem.

What’s Driving Online Video Growth?

Nielsen and Comscore online video data look like they come from different planets, as ReelSEO points out.    The most dramatic difference is in hours per viewer per month; 4.7 hours for Nielsen as of January 2011 versus 14.2 for Comscore, December 2010.    Yes, both are for U.S.

But there’s another headscratch, aside from how different the numbers are.   Each source tells a totally different story about where the growth in online video is coming from.   Completely different answers to the question:  more users or more usage?

Take these Jan 2011 Nielsen numbers for example.  They seem to say that the audience for online video is saturated and growth comes almost entirely from dramatically more usage from the same people.  I calculated a number from those provided that suggests: growth in time spent comes from more videos per person; not so much from increased time per stream:

Nielsen Online Video Data: January 2011

Now Comscore, for Dec 2010, from their 2010 Digital Year In Review: 

Comscore Online Video Data: December 2010

Granted the measures are apples and oranges.   Still, the Comscore data seems to say that online video users are increasingly dramatically while usage growth is more modest.   A completely different story.

With no bias toward sources or methodologies, the Nielsen growth story is the one I tend to believe.   I would think, at this point in its evolution, most everyone who’s going to watch online videos is already doing so (not counting new users coming in as kids mature).    I would guess that growth is coming from changing behavior among those who’ve already caught the habit.

Clearly there’s tremendous usage upside for online video.   If you think about the higher (Comscore) number for online video consumption, 14.2 hours a month, and compare it to consumption of TV, at some 35 hours a week.   Given that comparison you’d sort of expect usage to be the dynamic driving online video growth.

The question for either story is the detail behind it:  

  • If new users are pouring into online video, as per Comscore, who are those users; what are their demographics or other characteristics?  
  • If the same users are consuming dramatically more streams as per Nielsen, how are there habits changing?   What types of video content are making up the difference?   

And why do both sources show the average length of stream to be so short (both under 5 minutes) and growing relatively modestly compared to the other metrics?  Wouldn’t we expect, given the growth of Netflix, for this measure to be growing dramatically?   

I would love to break this information down into user segments.   Because I would bet there are segments of consumers for whom average length of stream is much longer than the average and segments for whom this metric is growing more sharply than the others.   When those segments start to drive the total sample average, when average length of stream really starts to grow, that’s when disruption of the TV business will be under way.

Is Your Video Traffic Upside Down?

For content sites with a mix of text and video, are there times when it makes sense to shift the balance towards video?

I would argue, for these types of sites, video traffic tends to be upside down.   Video consumption will be relatively lower during the site’s peak traffic hours, toward the middle of the day on weekdays.  Video consumption will be relatively higher on weekends and in the evenings when total site traffic is at low ebb.

The way to see the pattern is with a calculated metric, video starts/page views.   Call it the video content ratio.   There are issues with this metric, as I’ll note in a couple of paragraphs.  But it indicates a rough percentage of the content consumption on your site accounted for by video, a useful thing to know.   And you can track it across time to see  interesting patterns in video consumption, as related to total site traffic.

What you will likely see, if you go through this exercise, is that page views and video starts both tend to peak during the week versus the weekend and they both tend to peak during the mid-day hours versus the evening.    But video will peak less sharply and trough less, so that the video content ratio will actually peak on the off days and off hours.

The implied consumer behavior behind the pattern is the most interesting thing.    During peak traffic times when people are at work they’re looking for information in quicker, tighter hits.   They’re consuming everything in high quantities, text and video, but there there are inherent efficiencies for text.   During soft traffic times when people are more likely at home they’re less likely to be online and cruising content sites.  But when they are using content sites they are more in lean-back mode… and in a more conducive mood for watching videos.   Perhaps somewhat longer videos as well.

There may be a number of ways for site programming to take advantage of this picture…

Before leaving the topic, a few words on the video content ratio.   What’s wrong with this, aside from being yet one more calculated metric, are the various fudge factors.   Are there auto starts on various pages?    That will distort the ratio.   Does the implementation count some video starts as page views; are these completely exclusive definitions or is there some fuzzy overlap?   So there are certainly issues…let’s call it crude.

And yet there are various uses, as you can see.   It’s helpful, when looking at video trends for a site to benchmark them against total traffic trends, to see if video is merely trending with the site or on a distinct trajectory.   It’s useful, when there are a number of sites in a portfolio, to see which are doing relatively better in delivering video content relative to each traffic base.   Accepting its warts, the video content ratio is a way to break down data silos and look at the big picture.   And that’s always a good thing.

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