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.

Lesson of the NYT Paywall

The controversial NYT decision to reinstate a digital paywall earned some measure of vindication last week…the company’s third quarter earnings were more positive than expected, buoyed by an increase in digital subscribers.

Julie Hucke/Getty Images

Whether this is viewed a success depends on who you read.  To Ryan Chittum (in the Columbia Journalism Review) the reported 324K paid subscriptions in third quarter (up 15% from the previous) puts digital subscriptions on route to roughly 400K this time next year and perhaps $65K in annual revenue, enough to make a difference for supporting news operations… and a positive outcome.

The porous nature of the wall has been widely documented.  Aside from reading less than 20 articles a month there are myriad ways to avoid paying including switching browsers, deleting cookies or getting links from social media or search.  But to Felix Salmon (in Wired) the porous nature of the wall is a point in its favor, extracting revenue from those willing to pay without constricting overall web traffic.   The positive impact of the paywall on the perceived value of being a print subscriber…and an apparent uptick in print subscriptions…has also been noted (Henry Blodget in Business Insider).

The counterpoint, represented by Mathew Ingram, writing in Gigaom, argues that there’s nothing to get excited about.   Whether the audience will ever rise beyond current levels is an open question.  Citing an estimate of roughly $35M annually, Ingram notes that it’s a drop in the bucket compared to total NYT revenue.   But his biggest knock, echoed by others, is that this a defensive rather than forward looking strategy, charging people nickels and dimes as publishers have done for generations rather than developing new business models for the digital world.

The most interesting thing to me is that Times is taking an essentially different approach than it did with Times Select.   And the difference echoes a question I was asked as an analyst within a media company a couple of years ago…what sort of content are people more likely to pay for?

The big aha…is that was the wrong question.  The key variable is not what, it’s who.   In their last paywall experiment, the Times walled off particular types of content.   This time they’re extracting revenue from particular types of users, those that consume more content and those that are either less tech savvy…or more conscientious or more loyal…or perhaps simply too time-pressed to bother to circumvent the paywall.  The user-focused approach seems to have more legs.

New business models will not be born into the world fully clothed.   But digital ad revenue will have to be supplemented by other revenue streams for news publishing to remain viable…yes we will somehow have to extract additional nickels and dimes from readers.   There is a lesson learned from NYT’s tentative success…the critical question is not what content to put behind a wall but what users we can count on for the incremental nickels and dimes.    That insight will lead to more effective business models.    Because we surely have more ability to segment audiences in the digital world than we ever did in the world of paper and ink.

Surprise: Innovators Prefer Android

The Nielsen chart below (sourced from Slashgear, Sept 1) shows that the further people are along the adoption curve the less sure they are about the operating system they want in their next smartphone (based on likely smartphone upgraders).   Only 7% of Innovators are unsure about what operating system they want …but 30% of Late Adopters are unsure.   That’s no surprise, though it may indicate opportunity for players to reshuffle their positions as the market matures.

What is surprising though, at least to me, is the bimodal pattern for Android preference.  I had assumed that the Android phone is perceived by consumers as “the poor man’s iPhone”, with user stereotypes in my mind similar to this piece…that could be summed up as Android: Cheesesteak, iOS: Sushi

But the Nielsen data at least partly contradicts this stereotype, which can be seen more clearly if you take out the “not sures” and base percentages on those who are sure.    Android preference increases as you move to the end of the adoption curve – to the later adopters – that’s  true.   But Android preference also pops up at the top of the curve, among those likely to be the first to adopt new technology.   Apple preference is relatively strongest…among Early Adopters and the Early Majority.

This may relate to a heated discussion on Stackoverflow about developer preference between the operating systems.     The original post and reported data suggest that Android preference is rising sharply among developers; that Android surpassed iOS preference around mid-year.   The many doubting comments point to the non-representativeness of the data (e.g., do iOS developers ask their questions on sites other than Stackoverflow?) and question what it means (e.g., do Android developers ask more questions on Stackoverflow due to the inferiority of Android documentation?)

But seeing two pieces of information from different sources (and contexts) pointing in the same direction makes me wonder…is Google in fact making headway against Apple at both the bottom and the top of the tech-savvy spectrum?

Soft Programming and the Missing Platform

At the Mediapost Future of Media Forum earlier this week panelists were asked what companies they expect to join Amazon, Apple, Facebook and Google as dominant players in the new media world.

No specific company names were mentioned but there was an interesting discussion between the moderator, Josh Quittner, Editorial Director of Flipboard, and Steve Lacy, CEO of Meredith Corporation about what makes Amazon, Apple, Facebook and Google so dominant.  “Platforms” was the key word of the discussion…the notion that these companies have created an environment for interacting with consumers that other players gravitate to.  As the discussion evolved, the phrase in my mind was “network effect”; the more consumers converge on these platforms the more gravitational power they gain to attract more content…and more usage.

That is not to say that other companies won’t break in…someone on the panel said there will be hundreds of new and successful companies capturing emerging, lucrative niches.  But the implication of the discussion was…if a new major player emerges it will most likely be the creator and owner of a new platform that speaks to some fundamental consumer need.

The question then becomes, is there a missing platform?  The clue is in an article that appeared in today’s New York Times, among the many that paid respects to Steve Jobs.  As per the article, despite the huge impact of Apple products on the way we consume media, TV, the medium that captures the bulk of our time, remains relatively untouched.   Both Apple and Google have taken aim but Apple TV is still a miniscule player and Google TV seems to have little or no traction.   My bet is that somewhere in this area the new platform and perhaps new corporate player will emerge.

What do people want in the area loosely defined as TV?   This includes traditional cable and satellite delivery, multi-platform and over the top delivery of online video, players like Netflix, Hulu, Amazon, iTunes and YouTube… all competing for share of the consumer’s video-viewing time.

I think the consumer wants what they want in every other sphere…choice and control…to find through the mass of everything available the content they want to watch at any particular moment in time.

Soft programming is the phrase I would use to describe the consumer need.   Hard programming is the old-fashioned model – we’ll schedule this show at 8P as a lead-in to this show at 9P.   Video search is on the other side of the spectrum – zero programming – if you know what you want we’ll help you find it.   Soft programming is something in-between…a user-friendly narrowing of the consumer’s choice without forcing anything down his throat.   The Netflix recommendation engine is an example of soft programming that works beautifully within Netflix…though it doesn’t help the consumer cut through the myriad video offerings impinging on him from all sources.   Another example of soft programming is old-fashioned channel surfing.   That’s how the consumer used to deal with the problem rather than fully accepting any hard programmed stream.   But there are going to be too many video options for that venerable method, or existing clunky channel guides, to address the need.

Will one magical solution come to the rescue?   Of the many barriers, I’ll name two.  Content owners and distributors will do anything before they allow a third party filter to come between their assets and the consumer…unless their hand is somehow forced.  And second, perhaps less of a show-stopper but bothersome, the consumer will resist buying any additional piece of equipment, any new “box”….see Apple TV and Google TV.

But any unmet consumer need is like water building up around a dam.  As video content, linear and on demand, continues to inundate the consumer from a myriad of sources, the need for a smart, personalized, soft programming filter will grow.  Eventually some Jobs-like genius will invent the video content platform of the future…and, to get back to the original question, his or her company will be the one that joins Apple, Amazon, Facebook and Google as a major player in the new media age.

What’s The Best Cable Unbundling Strategy?

Last week I wrote a post questioning whether TV Everywhere is a sufficient defensive strategy for cable providers.    If the issue for some customers is simply that the price of cable has become too high offering cross platform access for the same price may not solve it.   Even if we see rising consumer uptake of TV Everywhere it may not indicate effective defense, not if the uptake is focused on core users while the mostly likely cord cutters – less upscale, younger, lighter TV viewers – continue to fall away.

Given that line of thought, it was interesting to see yesterday’s item in Reuters on the sudden interest of cable operators in a la carte offers after years of resistance.   In other words, operators seem ready to open another defensive front by offering consumers more limited, lower cost network bundles. Citing some key paragraphs:

“The plan represents a complete reversal from cable operators’ long-held opposition to what is known as ‘a la carte’ programming. Over the last decade, the cable industry battled ferociously with regulators to protect the right to bundle programming, arguing it offered customers the best value.

But executives now say the change is a necessary response to shifting dynamics such as higher carriage costs and using the Web to watch programs, as well as a weak economic recovery that has forced many consumers to cancel cable television subscriptions.”

If unbundling the video offer is an edging its way onto the table, the question becomes how to unbundle to minimize negative impact and maximize retention effectiveness…

The only marketplace example I’m aware of is Time Warner Cable’s TV Essentials package that went into test market last November and is scheduled to expand beyond the test according to press in the last few days.   This is a striped-down basic package that omits ESPN and other sports-focused networks at a price of $30-$40 a month.   The package is not heavily promoted but rather pitched to customers when they call to disconnect service.    No on-demand content is included for free, but for incremental cost.

I understand that operators are under multiple pressures, not just from increasingly price sensitive consumers but from rising programming/carriage costs and from media companies that rely on the bundling of their primary and secondary networks and who are particularly allergic to the notion of a la carte.   And I realize the desire to keep limited low-cost bundles in the background, encouraging as many customers as possible to pay full or premium prices…

Yet I’m not sure the generic bargain-basement approach to unbundling is necessarily best.   There may be a sweet spot in the space between the $30-$40 price of TV Essentials and the average cable video bill of roughly $75.   Though sports programming is most expensive it is also the most irreplaceable; a striped down package that’s only sports or only sports and news may motivate households – particularly lower income households with men – to keep at least one foot in cable rather than cut the cord.

And if younger audiences are among those most likely to defect, some combination of a striped down channel lineup and cross platform on demand access may be most potent…some hybridization of a lower cost bundle and TV Everywhere.   For if Netflix and Hulu (Amazon and iTunes) are the competitors that cord cutters are most likely defecting too, offering an option that’s more similar to these competitors may be the best defensive strategy.

Why The iPad Changes Everything

I would love to know how iPad owners compare the experience of watching full length video on their device versus watching the same content in traditional lean-back mode on their TV screens.   I think this is the critical question.  If the full length video experience on the iPad is judged equivalent or close to equivalent to traditional TV viewing, for most content most of the time, then we can expect the iPad and the tablet form generally will fundamentally change the future of TV.

I bet the same question for laptops would get a very different answer.   There are times, places and circumstances when people watch full length video on their laptops but, given the option, I expect they would mostly prefer to port the content to the big screen.   In contrast, the iPad may be more than an on-the-go, on the train, in the airport alternative; to the degree that it is a strong viewing option for full length video in any circumstance…that makes it a game changer.

Prior to the iPad all full length video was ultimately headed toward one door.    For Netflix, Hulu, Amazon, etc…the critical step was to get ported over-the-top to the TV screen.    It is in this scenario that on demand competitors might actually supplant cable and satellite subscriptions for at least some group of people who cut the cord.  And it is in this scenario that on demand competitors could compete with cable and satellite time –fighting for control of viewing behavior in the 10-foot screen.

In this pre-iPad reality, laptop and smartphone screens would likely play a secondary role for actually consuming full length content; their usage would be tilted to short form.  They would play a key role in helping people find the full length video content they’re looking for and let them socially interact around it.   These roles for other screens remains…but the iPad blows up the centrality of the traditional TV experience and opens another major door for full length video consumption.

Right now the numbers are small.   The latest U.S. penetration number that I’ve seen for tablets is 6%, as cited by Mark Walsh in MediaPost a couple of weeks ago.     Nielsen reported just under 5% earlier this year.    Sales projections are very bullish though:  Gartner is projecting worldwide tablet sales of 63.6M in 2011, up from 17.6M in 2010 and rising to 326.3M in 2015…so there may be 5-6 fold increase in penetration over the next few years.   Most important is data reported by In-Stat : “50% of tablet owners are viewing not only feature-length movies on their device, but TV shows as well”.    We don’t know how much, how frequently…but we have some indication that tablets are being widely used as a multimedia device, as a way to watch long form video.

And in that role they have the potential to change everything.

TV Everywhere: How To Assess Success?

With widespread availability of TV Everywhere in North America as of this summer according to a Parks Associates study and with a consumer awareness campaign recently launched by Turner Broadcasting it is interesting to think about what success would look like…in terms of what distributors and their network partners are trying to achieve.

It seems to me there are three goals:  (1) stimulate cross-platform uptake and usage of programming and thereby extend the reach of the advertising, (2) reduce the likelihood of cord cutting behavior and (3) reduce cannibalization of cable or satellite time by on demand alternatives.  Though there’s some payout associated with the first goal the second two defensive goals are the key to why TV Everywhere platforms are being implemented…to subsume evolving consumer behavior into the existing business model and prevent the dynamics that disrupted the music business from affecting TV.

At this point I haven’t seen uptake or usage numbers surface in the public domain.   The NYT piece about the Turner campaign launch cites nothing more definitive than “millions”of users of HBO GO…since its launch earlier in 2011.   I’ve seen no numbers for Fancast Xfinity TV though its been available to Comcast subscribers since December 2009.

But, per my argument above, if we want to asess the success of this strategy, uptake is only part of the story.   We’d want to show that availability and usage of TV Everywhere makes customers less likely to cut the cord…because they can get a wide variety of on demand TV shows and movies along with their cable subscription they are less likely to cancel that subscription in favor of on demand options.   And we’d want to show that those who use TV Everywhere are less likely to dip into Netflix streaming or other on demand options…that one behavior effectively supplants the other.

It is possible, for example, that people likely to adopt TV Everywhere are a different set of people than those likely to cut the cord.   The former may be happy to expand cross platform options from their cable or satellite provider for no extra cost while the latter, under stronger financial pressures, feel a need to reduce their spending.   One group coming in the top may not forestall others falling out the bottom.

Of course there is serious question about how many people really are falling out the bottom.   As cited in a previous post,  a J.D. Power and Associates study released in June showed just 3% of cable or satellite customers had cut the cord, 6% among Generation Y…

Still, if one of the goals of TV Everywhere is to keep this behavior from expanding to more customers and to the industry’s core demographics, we need to explicitly monitor if A really does prevent B.    And if it does not, if cord cutting continues despite operators providing and touting TV Everywhere, we have to consider (as per recent comments by Bernstein Research’s Craig Moffett) that perhaps prices are simply too high; offering cross platform access for the same price just can’t match the allure of a la carte on demand services replacing the cable bill:

“Perhaps the most consistent theme in our research over the past two years has been the widening disconnect between flat-to-declining consumer disposable income, particularly in the bottom two quintiles of household income, and the rising price of media and telecommunications services”

The other defensive role that should be monitored is whether TV Everywhere customers are actually less likely to tap into on demand video services like Netflix or Hulu.   This is another case of whether A really does prevent B.   One question to keep an eye on is whether consumers tend to use TV Everywhere for a limited, specific purpose…catching show episodes that they’ve missed… while continuing to use competing on demand services for another function, mining a broad movie database for something, old or new, that fits their mood and preferences.   Just as Netflix, entering the streaming world, is struggling with their lack of new and original program content, cable and satellite operators expanding their presence in the on demand world may need to tweak the depth, organization and positioning of their offerings to keep on demand competitors at bay…for all the needs that people want from these services.

Implementing a defensive plan is an important first step for the industry.   The next step is making sure that it is, in fact, serving all the intended defensive functions.

 

Media Multi-Tasking And The Battle For Attention

The average amount of time that people give to some media platforms is trending up (mobile and Internet) and others are trending down (magazines and newspapers).  But the average amount of time they give to all media combined is rising inexorably.

This is shown in an eMarketer item with the figures below: an average of 660 minutes or 11 hours a day across all media in 2010, up 1.5% from 2009 and up 3.9% from 2008.   This analysis does not include pre-recorded music which would surely drive the numbers higher.   You have to wonder where it will end; is there no limit to the amount of media that people will consume?

Media multitasking is one of the things that keeps the total number rising; people using two or more media simultaneously.   eMarketer is explicit; the time that they report is for each medium separately; an hour spent watching TV while online is counted in both the TV and the online numbers.  The rise of the total suggests that as more media find their place in people’s lives they are increasingly layered on top of one another.  So the question becomes not what medium are people using at any given time but which of the various media they’re using is capturing most of their attention; what medium is in the foreground while others are playing in the background.

A study conducted for Yahoo! by Nielsen, reported in mid-2010, suggests that when TV and online are used together online is likely to be in the foreground and TV in the background.    The way I read this press release, 75% of respondents ever use TV and Internet together and 51% of the 75% do so daily.   So 38%, a bit more than a third, show daily simultaneous use of TV and Internet.   What’s really telling, beside the frequency of the behavior, is that the online activity is generally unrelated to the TV programming or commercials being viewed – and 54% report that the Internet is the primary focus of their attention.   54% is not overwhelming; plenty of people are reporting background Internet usage.    But the picture you get, at least for some of the people some of the time: unrelated Internet activities like Google or Facebook are in the foreground of their attention while the TV plays in the background. The frequency of this pattern will of course be higher for younger people.

An implication of this for programmers and TV advertisers:  you need to be (or be advertising on) foreground TV, not background TV.   TV that’s winning the cross-media battle for attention.

In this regard I’ll suggest a hypothesis.  The medium that wins the battle of attention, for any given consumer at any given time, is the one where the consumer is making the most deliberate content choices.    Online tends to win against TV, though not overwhelmingly, because simultaneous users are more active online, choosing what they want to see and do while the TV plays on.

And so…if people choose to watch their TV fare on-demand, from over-the-top sources like Netflix or Hulu, that deliberately selected content will be more likely than more their more casual TV choices to capture attention versus other simultaneous media the user is engaged in.   To the degree that there is advertising on on-demand and over-the-top TV content, that real estate will be increasingly valuable in a media-multitasking world.

Driving Vertical Content Recommendations

One of the recurring patterns I’ve run into with web content, illustrated here with the upside down triangle, is the inverse relationship between traffic and value.   The areas of a site where traffic is high, value tends to be low and vice versa.  The pattern reflects a basic dynamic: high traffic generally indicates breadth of content appeal while high value generally indicates specificity of audience that advertisers are willing to pay a premium for.  A more specific audience….tends to generate lower traffic.

The inverted relationship is not invariably true; there is high traffic, high value content (and unfortunately low traffic, low value).   But it is a recurring tendency.   And the more that content narrows within a site, from a broad overall positioning to specific topic verticals, the more the triangle visual will apply.

This concept relates to another, the importance of maximizing monetization within each site visit.  In a previous post, Is Increasing Visit Frequency a Realistic Goal? I’ve laid out some public domain Quantcast data to show that the visits per visitor dimension of loyalty has less variability across sites than the pages per visit dimension.    Visits per visitor tend to fall into a more narrow range most likely because of the mind-bogglingly enormous set of possible destinations on the web.    It’s just hard to squeeze another visit per month from a site visitor; getting another page or two per visit is a lower hurdle.   To monetize most effectively you’ve got to monetize them when you’ve got them.

The logic and mathematics of recommendation algorithms are beyond me.  But based on the theories above I believe they can be key to driving increased loyalty along the path of least resistance, getting another page or two from the visitor on the occasions when he/she happens to visit.

Furthermore, recommendations that drive the visitor deeper into the triangle, into content verticals that appeal specifically to a visitor’s profile and command higher value, are worth more than recommendations that drive visitors across the top, to other broadly appealing but lower value content.   The more recommendation algorithms can achieve this goal the more effectively they can monetize for the publisher.

Along these lines, here is a link to a cool visualization from the site Online Behavior that shows how a page can be personalized for a specific visitor:

“A visitor arrives to a website from a search engine using search keywords including “health”.  Why not display a personalized version of the page based on the visitor’s interest?”

Not a recommendation algorithm per se but an example of how a specific visitor could be driven to higher value content that specifically appeals to his/her profile.

 

Are Heavy Online Streamers Watching Less TV?

Nielsen’s first quarter 2011 Cross-Platform Report shows that the top quintile of online video streamers, in terms of time spent, consume somewhat less TV than other groups.    We can’t assume causality from the findings; heavy online streaming may reduce TV viewing or heavy online streamers may be lighter TV viewers to begin with.    But it’s an interesting finding either way, as shown by the squiggly line charts in the Nielsen report that I’ve lifted below:

There are a couple of different threads that can be pulled out of this information; an alternate visual may help to tease them out.   What I’ve done below is plot the online streaming quintiles, ranging from lightest (5) to heaviest (1), on a scatter plot with average daily minutes of streaming and average daily minutes of TV as x and y axes.   I’ve put 4Q 2010 and 1Q 2011 on the same scatter plot and connected the dots for each time period.

The first thing to note from this reconfigured chart:  TV viewing for the first quarter is on a much higher plane than the fourth quarter.   The two periods seem so different, as far as media behavior is concerned, that we can’t really trend between the two; all we can do it see if there’s consistency to the story.

There seems a great deal of consistency in the behavior patterns reflected by the streaming quintiles:

  • Quintile 5 in 1Q 2011: very heavy TV with virtually no online video.  I bet if we dug into this group we’d find an older demographic profile.
  • Quintile 5 in 4Q 2010 and quintile 4 across both time periods:  relatively light TV viewers with little online streaming.  This light/light pattern may reflect an upscale group that skews toward print rather than video and/or young males who skew low across all media.
  • Quintiles 2 and 3 across both time periods:  heavy TV viewers who are also moderate online streamers.   This may represent the mainstream condition.   At this point in the story, online streaming and TV viewing are rising in tandem…
  • And then there’s quintile 1, the heaviest online streamers who, as the Nielsen report points out, show somewhat lower TV consumption than the other groups.

A couple of points about the heavy online streamers:

  • Streaming behavior is highly concentrated into this top quintile.   The graphic shows how sharply the heaviest users pull away from the other four groups in terms of time spent with streamed content.  My back-of-the-envelope from these numbers shows that the top quintile accounts for 80% of the total time spent with streamed content; in contrast the top TV quintile accounts for just 45% of total TV time spent.
  • The data begs for deeper drill-down into this quintile; demographic and behavioral characteristics.  Why are they consuming so much streaming content?  Are they sending online video over-the-top to their TV’s?
  • Yes, their TV consumption is lower than other groups but not by a whole heck of a lot.   The graphic shows, as their online streaming behavior shoots away from the pack, their TV behavior declines a bit, but nowhere near in proportion to the way their streaming behavior accelerates.

Another way to look at this is to compare TV viewing for the top streaming quintile against average TV viewing across all the quintiles.   We can see the shortfall is slight; the under-consumption of TV is far smaller than the streamed content that these consumers have added to their lives:

  •  In 4Q 2010, among P2+, the heaviest streaming quintile consumed 14.5 minutes of online streaming a day but only 4.3 minutes less TV than average
  • In 1Q 2011, among P2+, the heaviest streaming quintile consumed 18.8 minutes of online streaming a day but only 8.0 minutes less TV than average
  • There’s a much sharper equivalence between minutes of streaming and dampened TV viewing among 18-34′s specifically.   Among this demo, for 1Q 2011, the heaviest streaming quintile consumed 27.0 minutes of online streaming a day and 21.5 minutes less TV than average.   It may be, among this demo, that the sharper trade-off reflects cord cutting; I cited a J.D. Powers and Associates study in previous post that suggests perhaps 6% of younger consumers have cut the cord.

I think this analysis shows a truism about people and media; the more options we throw at them the more media they consume.   Yes, the heaviest online streamers may consume a bit less TV than other groups but, as streaming becomes a bigger part of their lives, they consume more video overall.  They don’t trade-off one medium for another to the degree that they layer them all together.    The question then becomes:  how do they make these integrations and what role does each medium play?