Is it getting easier or more difficult to monetize content? Conflicting signs abound.

For the first time ever, traditional paid TV services experienced a net industry-wide subscriber loss over a four quarter period.  For the 12 months ending March 31, 2013, the 13 biggest U.S. cable, satellite and telco TV providers lost roughly 80,000 subscribers.  But let’s remember that 95 million households subscribe to paid TV services so we are talking about a roughly 0.084 percent loss.

At the same time, the economic interests of cable companies are diverging as large cable companies want to maintain an all-you-can-eat bundled pricing model, while small and mid-sized cable companies are more willing to explore a la carte pricing and services.

But there is still plenty of research suggesting consumers find value in their paid TV services. Recent research from KPMG finds UK media consumers appear more willing to pay for content – especially easy to access online content. Just over half of respondents (53%) said that one of the advantages of online content was that they could access it for free. That same figure was 80% three years ago. Over of third (36%) of respondents said they prefer to access media online as it offers better ‘value for money’, compared with only 15% in 2009.  Aereo’s business model is largely built on the premise that consumers will pay for convenient online delivery of otherwise available free over-the-air content.

Elsewhere online Netflix of course showed tremendous subscriber growth in their most recent quarter and as I mentioned previously, YouTube recently began paid channel services.

While traditional paid TV services struggle to grow their respective subscriber bases, they are growing revenue as the monthly fee charged subscribers continues to grow.

Monetization of content comes down to distribution which is historically driven by geography.  But in an every-device-connected world,  geography is no longer relevant and so distribution rights have to be completely rethought. Curation is king in a ubiquitous world where any service provide can be on any device.

US consumers spend more on content – and entertainment generally – than ever before.  But like many things in a digital world – audiences are becoming increasingly fragmented. Monetizing in a fragmented world requires a different approach. One must curate a million niche audiences. Those niche audiences are defined by not only content but also by the dimensions of time and space (ie location).  While consumers are showing more willingness to pay for content – it is obviously the curation they are coveting.


The Smithsonian launched their first major crowdfunding campaign to support it’s first-ever exhibition on the yogic art. Crowdfunding is in many ways simply a way of pre-selling an offering. You can gauge interest before bring a product or service to market.  You can go direct to the consumer and avoid being handicapped by lack of distribution.

Moving forward I expect we’ll see more campaigns from the likes of museums and other public works organizations like PBS.  We’ve already seen crowdfunding used to fund movies. Because special exhibits often have niche but enthusiastic audiences or require altruism  crowdfinancing is the perfect fit for museums to not only raise necessary funds but also to determine if planned exhibits or other programs will have the anticipated draw.

Today most of these are unidirectional – museums create the campaign.  But I could also see a future where like-minded consumers join together to raise funds necessary to support programs and exhibits they are interested in – and thereby influencing museums and other organizations.  Creation and curation can steadily become bidirectional because crowdfunding can easily facilitate the creation of campaigns from either the producers or the consumers.

Most think of a second screen experience as one narrowly defined around viewing and engaging with content related to what is happening on a different (first) screen at the same time. Just see the first paragraph of the Wikipedia page for “second screen:”

Second screen, sometimes also referred to as “companion device” (or “companion apps” when referring to software applications), is a term that refers to an additional electronic device (e.g.tablet, smartphone) that allows a content consumer to interact with the content they are consuming, such as TV shows, movies, music, or video games. Extra data is displayed on a portable device synchronized with the content being viewed on television.

But second screening is often much richer than simply consuming and engaging with companion content on two different devices simultaneously. More frequently we are consuming content on a secondary screen that is separate from what is happening on the first screen. Perhaps we call this simultaneous media consumption – mixed second screening.  The idea of mixed second screening is consistent with recently released research commissioned by Microsoft.

As the release notes, the study found consumers typically follow four multi-screening pathways:

  • Content Grazing: This is the most common pathway 68 percent of consumers Content Grazing. This occurs when consumers use two or more screens simultaneously to access unrelated content; for example, watching a show on TV while at the same time checking email on your PC and texting a friend on your mobile phone.
  • Investigative Spider-Webbing: This is the second most common multi-screening pathway with 57 percent of consumers in this category. It’s a simultaneous path where consumers embark on a content driven investigation across devices at the same time, either to gather more information or for pure exploration. For example this could consist of watching a movie on the TV and looking up what other movies the actors have been in on a tablet or PC.
  • Quantum Journey: Forty-six percent of consumers land in the Quantum pathway. Here, productivity and efficiency are paramount as consumers are trying to accomplish a task.  Each screen separately and additively takes them closer to achieving their goal. For example, you snap a picture of a pair of shoes on your mobile that you see for sale while shopping, and then look up reviews about the shoes on your PC at home before purchasing.
  • Social Spider-Webbing: This is the least common multi-screening pathway with 39 percent of consumers engaging here. Consumers in this instance are extroverted and focused on sharing content and connecting with others across devices. For example, you beat your friend’s high score for a game on your Xbox, and then use Skype or other social channels to brag about your win to friends.

Last month, NPD published research suggesting individuals are heavy mixed second screen consumers and those who do engage in related second screen viewing don’t today rely heavily on the apps designed specifically for related or companion second screening, but rather rely on general Internet properties like IMDb..

Some of the big news out this week came from ABC who announced they would start streaming parts of their entire linear programming schedule in real-time to viewers in specific markets.



    1. IHS IMS Research predicts Google Glass will sell 50K units in 2012, 124K in 2013, 434,000 in 2014, 2.17 million in 2015, and 6.6 million in 2016.  Forecast seems low in the near-term years and high for the further out years in my opinion.
    2. The Ten Commandments of sales from Dan Cole
    3. AT&T recently launched their home connectivity/automation/security system (read more here and here).  A natural evolution of service providers to focus on in-home connectivity.  I expect this service area to be a strongly contested market in the coming years.  Consumers want it, but don’t necessarily want to do it themselves.  Moreover, they want it to work seamlessly.  The rise of small cells seems to fit within this business approach as well (see Qualcomm story).
    4. World’s first Braille smartphone
    5. a few past articles on the Internet and the Boston bombing (here, here, here, and here)
    6. is the future of genealogy all in the DNA
    7. DARPA-sponsored crowd-sourced tank

Several changes are underfoot which could be shifting the direction of curation.  Over the last 24 months major content distribution platforms have been steadily moving towards becoming more curation focused. Curation feels like the natural evolution of content. As companies try to move up the value chain they become more focused on curation. As they seek greater margin – they focus more heavily on becoming a curated platform.

Still today there is talk of traditional (linear and paid) TV being killed by disruptive technologies like Internet TV.  But this believe seems rather shortsighted to me.  First, Internet is just a distribution approach and others could certainly adopt it. Both DirecTV and Dish have examined Internet delivery of their services for example – despite the fact one might argue Internet delivery is at odds with their current use of satellite delivery.  Under that scenario, Internet TV hardly seems disruptive to their business in the way most people are thinking about it. Secondly, I’m not want to quickly rule out innovation from incumbents.  Even when the innovation doesn’t originate with incumbents many are still quick to adapt.  Look at DVR technology. While Tivo really introduced the possibility and potential of the technology, traditional MSOs and telecos integrated the technology quickly into their existing business models and one could argue it was these exact MSOs and telcos who took the technology to mass markets.  MSOs and telcos still feel ready to adopt new innovations.

There has long been talk that free content or user-generated content would disrupt existing business models into nonexistence, but this has yet to come to fruition and I doubt it is on the horizon. Clearly we aren’t completely through the cycle of change, but as Jeff Bewkes, Chairman of the Board and CEO of Time Warner recently posited –  TV is taking over the Internet, rather than the Internet taking over TV.  YouTube is reportedly launching paid subscriptions for some of their video channels which only seems to lend support for this premise.  Multiple business models around  entertainment services are coexisting and many are thriving in the face of perceived competition.

Netflix recently laid out their Long-Term View – most of which is completely consistent with what I’ve laid out above. It is also evident, Netflix too is pushing forward to be not just a distribution platform, but also a curator.  As Ted Sarandos, the company’s Chief Content Office recently put it –

if we believe our own theories, most content will eventually be delivered online to most people on the planet. Then we will have to distinguish ourselves from emerging competitors in other ways…You do not want someone looking at two sets of content from different services, then shrugging their shoulders and thinking that they are about the same. We want to avoid that down the line…Our appetite for non-exclusive content is going to near zero. We are willing to pay more for programming on an exclusive basis and for individual programming on a curated basis but we are not taking on a lot of non-exclusive bulk. It gets very confusing for consumers when they see two different products advertising the same content brands.

Some of the key take-aways from Netflix’s Long-Term View:

For most existing networks, this economic transition will occur through TV Everywhere. If a consumer continues to subscribe to linear TV from a multi-channel video program distributor (MVPD), they get a password to use the Internet apps for the networks they subscribe to on linear. The more networks successfully keep their prime-time programming behind this authentication wall, the less “cord cutting” will occur. The same consumer who today finds it worthwhile to pay for a linear TV package will likely pay for a “linear plus apps” package…

We don’t and can’t compete on breadth with Comcast, Sky, Amazon, Apple, Microsoft, Sony, or Google. For us to be hugely successful we have to be a focused passion brand. Starbucks, not 7-Eleven. Southwest, not United. HBO, not Dish…

We are not a generic “video” company that streams all types of video such as news, user-generated, sports, music video, or reality. We are movies and TV shows…

Another area of focus is personalized merchandising, which drives what content we feature on a given member’s initial screen. Google search is an example of a ranking system, where results are automatically computed to show Google’s estimate of the most relevant answer to the query. For Netflix, the user’s home page is the personalized ranking of what we think will be most relevant for that specific user at any given time. By analyzing terabytes of data from every recent click, view, re-view, early abandon, page views and other data, we are able to generate a personalized homepage filled with the content most likely to please. Our aim is to keep inventing and tuning algorithms to generate higher satisfaction, viewing, and retention, for whatever the level of content we can afford in that territory…

All of our algorithm work, like with Google search ranking, is proven or disproven by A/B testing. Only algorithms that lead to an improved experience get rolled out to everyone…

As we’ve gained experience, we’ve realized that the 20th documentary about the financial crisis will mostly just take away viewing from the other 19 such docs, and instead of trying to have everything, we should strive to have the best in each category. As such, we are actively curating our service rather than carrying as many titles as we can..

Over the years, we’ve successfully developed the art of estimating how much our members will watch a given show or movie based upon how it has performed to date in other, earlier channels (theatrical for movie; broadcast and cable first-run for TV) and on how comparable titles have performed on Netflix. This generally enables us to avoid overpaying for content, relative to member enjoyment…

With Originals, we are now extending that concept to estimate the attractiveness of projects that are brought to us by professional producers. There is more judgment required in this process, and more variability due to the art in the production process, but because of the data we have on our members’ viewing habits and our experience in licensing a broad range of content, we think we can do as good or better job than our linear TV peers in choosing projects and setting budgets…

At times we have worried about the strategic motivations of ISPs that are also MVPDs, but the absence of cord-cutting has mitigated this concern. In the USA, MVPDs have remained stable at 100 million subscribers while Netflix has grown to about 30 million members. The stability of the MVPD subscriber base, despite Netflix large membership, suggests that most members consider Netflix complementary to, rather than a substitute for, MVPD video. MVPDs are keeping their subscribers through TV Everywhere authentication. Internet video services like Netflix,, iTunes and YouTube are not currently a material strategic problem for companies that are both an ISP and an MVPD.

In the case of Netflix, HBO or other TimeWarner properties, and even YouTube the great purveyor of “free” content, the move towards margin-rich curation is tangible.  It is increasingly clear that multiple business models will successfully coexist – even over an extended period of time.  Consumers are building suites of entertainment options instead of locking into a single service provider of content. Each business model has their own respective approach and each approach adds value in different ways.  But common denominators do not facilitate differentiation.

If (read: when) all content can easily be delivered via the Internet it will be. In that environment, distribution isn’t a differentiator so companies will increasingly turn to curation in an effort to provide a unique value proposition.  At the same time, consumers will maintain relationships with several “curation providers”.






The world is truly becoming flat when it comes to consumer tech and that has had (and is having) profound ramifications on the competitive nature of the global marketplace for consumer tech.  The global tastes and preferences of consumers are becoming homogeneous and while some subtleties still exist between geographic markets, these differences are quickly becoming marginalized.

Take for example mobile telephones. In the last 24-36 months we’ve witnessed the rise of global preferences for smartphones or traditional mobile telephony. Not news of course.  But what is perhaps interesting is that these preferences have largely materialized around a very few specific models.  Because of this, the global market has truly become a winner (can) take-all market. While mobile phone manufacturers will broker specific carrier deals within a given region, they are still selling the same handset across these markets for the most part. This has ramifications for accessory manufacturers and more broadly it has ramifications for the entire suite of devices, services, and software/applications within the accompanying ecosystem of a successful product – especially if the ecosystem is built around a specific OS.

Even when usage patterns differ across geographic markets do we care? Perhaps when it comes to the nuances of actually marketing a product or service, but because products and services will have all of the bells and whistles built in anyways there isn’t really much customization that needs to be done on a geographic basis.

But it does mean that the initial design of a device or service is extremely important.  It must scale globally.  Devices and services must speak a global design language.  Brands must work on a global scale. One need only look at Apple, Samsung, or Beats to see this working in practice.

I’m a fan of  mirroring.  At least I’m a fan of the idea.  I’m not a heavy user. Actually, I don’t really use it at all.  I guess I’m not alone.  According to a recent study from NPD, only about seven percent of tablet or smartphone owners actually use screen sharing technologies.

NPD suggests the technology is simply new so consumers just haven’t adopted it yet.  Certainty this could be true.  We know adoption follows power laws so perhaps we just haven’t hit the point of accelerating adoption yet. There probably is some truth to this. According to NPD’s results,  less than 20 percent of those surveyed are even aware of the capabilities of screen sharing across devices.

But I think there is more.  I think the feature is largely a novelty today and we simply haven’t hit on any real killer applications. Sharing photos on a secondary screen is nice, but not necessary or sufficient. The step of  mirroring the personal device with the shared screen in order to share the content – the time cost to the user – isn’t worth the benefit.  One can simply just “share” the first screen of the tablet or smartphone. Of the seven percent who are using mirroring, about half are using it to share photos – though I would imagine this is something they have done instead of something they do regularly.

About three-quarters of those who actually use screen sharing technology are streaming video. This makes sense to me.  Utility/enjoyment of video consumption is probably correlated with screen size as viewing duration increases.  The longer you watch a given video, the more likely you might be to want to toggle it to a bigger screen.

NPD reported only about 20 percent reported sharing video games from a personal device to a shared screen. Again, I think this speaks to the way individuals are interacting with the content.  Playing a video game on a personal device like a smartphone or tablet is involved.  It is more interaction than simple consumption.  Toggling to a larger screen – one that is further from you in distance – probably doesn’t help you out when the input still has to go through the screen of the personal device.

There are two key points here. Mirroring makes sense if there are others with whom you want to share content and simply sharing the first screen of the tablet or smartphone is cumbersome. Secondly, mirroring makes sense if those who are consuming the content on the shared screen aren’t involved in the input/manipulation of the content. Because one still needs to do control the content using the personal device, mirroring only really makes sense if those who are viewing the content on the shared screen don’t want to also control it on the personal screen.

So what are the killer applications for screen mirroring?  Education is probably one.  I can see potential if there is a tablet on every desk and the teacher can toggle an individual screen either to her own screen or to a screen in front of the classroom for broader sharing across the entire class.  I think gaming does make sense – when multiple players are involved and the personal screen can be used in conjunction with the shared screen. In other words, the tablet becomes a true second screen with additional information or the  shared screen has unique information that is relevant to the personal screen.


I wrote early this month about the features of connected wristwatches. Since this time there has been significant digital ink spilled discussing the connected wristwatch space with a focus on Apple’s potential foray into the market (see: 100 people are working on the Apple watch, Apple’s entry into wearable tech, On the Apple Watch watch, Apple watch that talks to your iPhone appears in patent, and a thousand more articles).

There is always some trepidation in throwing a number out for the potential addressable market for very nascent – and in this case nearly nonexistent – categories. A back-of-the-envelope forecast  for connected wristwatches will surely haunt me and in these exercises I always think of the cellular telephony forecast McKinsey constructed in 1980 at the request of AT&T (whose Bell Labs had invented cellular telephony).  McKinsey & Company predicted 900,000 subscribers by 2000 – only slightly less than the 109 million that actually existed by that year.

But with that caveat squarely attached, I want to walk through some of my thinking on this topic.

Background Assumptions

Today there are roughly 240 million adults in the U.S. living across about 119 million households  (There are about 314 million total living in the U.S., but for this estimate – and simplicity – we’ll focus on the adult population).  Roughly 87 percent of American adults have a cell phone and about 45 percent of American adults have a smartphone.

With these type of exercises, it is always important to remember two things: (1) rarely does a product see 100 percent adoption (and only a few tech devices have ever even seen household adoption above 85 or 90 percent), and (2) adoption follows logistic functions.  This second point means slow adoption in the early years followed by several years of accelerating adoption before eventually the second derivative of the growth function turns negative (adoption grow continues but at a slower pace).  While not always evident, the first derivative of the growth function often turns negative in the end (adoption/ownership actually declines as consumers move to new products and forego replacement).

I prefer the term connected wristwatch over “smart” watch because we are really talking about watches that primarily connect to the Internet by piggybacking on the connection of the smartphone or some other Internet-enabled device. Because most connected watches will leverage the embedded connectivity and functionality of smartphones the addressable market today is probably the 45 percent or so of U.S. adults that have smartphones.  Over the long-run many and perhaps most mobile phone users will likely adopt smartphones so the longer-run addressable market is probably closer to 80 percent or 85 percent of U.S. adults. This suggests a current addressable market of roughly 108 million individuals and a potential long-term addressable market of say 190-200 million adults.

Anything that attaches to mobile phones is by definition one of the largest addressable markets in tech because of the high ownership rate of the underlying device.  This is one of the largest reasons connected watches deserve the attention they are getting. But obviously not all smartphone users will adopt connected watches. The global watch market is itself a not small addressable market,  with some estimates suggesting a $45 billion global market. I’d guess 25 percent to 40 percent of this market is in the U.S.  The wristwatch market today is not surprisingly driven heavily by luxury brands and high-end watches.  The watch market has become more of a fashion accessory than the utility device it once was because individuals are using their mobile phones as their timepiece in most cases.  But these dynamics could reverse as the connected watch becomes more than just a timepiece device.

Without doing any real research, if I had to guess I imagine long-term attachment rates of perhaps 30 to 40 percent seem reasonable if the category is successfully established so you are looking at an installed base of maybe 60 million to 80 million owners in the U.S. If the category never materializes of course then you are looking at maybe one to two percent adoption over the life of the category.

The average smartphone is replaced roughly every 18 months in the U.S. and U.S. carrier subsidy models accelerate the replacement cycle compared to other markets. While smart watches are less expensive than smartphones they aren’t likely well suited for subsidy programs since they leverage the connectivity of the mobile phone.  But they would be influenced by fashion which might shorten the replacement cycle.  Guessing, I imagine connected watches would be replaced every 36-48 months.

Summarizing, here are my (early) basic assumptions:

  • Long-term (underlying) addressable market= roughly 200 million smartphone users
  • Attachment rates to that addressable market = 30 percent to 40 percent or 60 million to 80 million
  • Replacement cycle = 3-4 years
  • Density rates = 1.  I assume adopting consumers own about one on average.
  • Replacement rate.  In this exercise I’m primarily focused on initial adoption, but could also factor in replacement cycles. My starting estimate is that 80 percent of users actually replace the product. This 80 percent figure would fluctuate higher or lower depending on how committed users are to the device and I imagine it naturally decays over time. An 80 percent replacement figure suggests a pretty strong commitment to the device and an otherwise successful category.

With these starting assumptions, I’m suggesting the category is generally successful with the portion of the addressable market that adopts the technology relatively committed to the category.  Whether the category can bring value to the consumer and realize this potential (or even surpass it) remains to be seen.

Sizing the Market for Connected Watches

We are already getting a sense for early demand for connected watches.

0213 adoption

Kickstarter darling Pebble reports they’ve sold about 85,000 watches to-date. Here I use some relatively simple diffusion equations to approximate what sales would look like over the next 30 years given the assumptions above.  A few things to note in the following charts.

First, total U.S. sales hit about 220,000 this year and 320,000 next year. Annual sales break the million market for the first time in year 6 and subsequently annual sales peak in year 13 at about 5.8 million.  Over the 30 year period, 60 million devices are sold and if you consider replacement cycles another 47.7 million devices are sold just by replacing 80 percent of the first cycle of purchases. This latter figure grows if you consider multiple replacements over this forecast horizon.

Given the simplified model I’ve used, five percent of U.S. adults own the product within 9 years and 10 percent own it with 11 years. By year 24 adoption rates have reached 30 percent at which point I’ve assumed they reach their steady state.  If I were to project broader adoption then ownership rates would accelerate over the forecast horizon. In other words, we’d see a higher rate of ownership rates more quickly.

0213 cumulative adoptionI actually believe adoption rates are broadly accelerating.  I’ve written about this in the past. Information diffusion is happening more rapidly today. Potential buyers are learning more quickly about new technologies. Adoption rates are still following logistic functions but those logistic functions are being compressed over a shorter time period.  New products are finding life (or conversely death) much more quickly today.

The above approach is a simplistic model that suggests what adoption might look like given some average parameters and assumptions. Clearly, reality will look much different.  The first few hundred thousand units of any device are relatively easy to sell. I like to say there is a 50,000 unit market for everything.  It is the next few hundred thousand that are more difficult to sell.


Does the Entry of Apple Change these Estimates?

Maybe. By some estimates, Apple controls about half of the U.S. smartphone market so about 54 million U.S. adults have Apple iPhones. Presuming maybe five percent to ten percent of the installed base are early adopters of Apple products and buy within the first 12 to 18 months, so you are looking at maybe two to five million iWatches selling over the first 12 to 18 months. That figure is four to ten times what I estimated above. But I think an Apple entry influence is more of brand story than a product viability story. Long-run adoption dynamics and replacement cycles will be less influenced. I think Apple’s entry could shift the market and compress the adoption cycle as I discussed above, but I don’t know that it changes the market size for the category over a longer horizon.

What Do Connected Watches Do for a Company’s Bottom line? (ie Why Enter the Connected Watch Market?)

At the end of the day, companies like Apple are hardware companies.  As public companies they have investor communities they must appease.  They do this by growing both top-line and bottom-line revenue. They need to grow both sales (top-line revenue) and net income (bottom-line revenue). They do this by entering into new markets and selling more stuff.  At the same time, they must maintain (or increase) margin which ensures net income grows inline with top-line revenue growth.  Companies want to grow sales but not if it sacrifices profitability (obviously). Companies must think carefully about the type of new markets they enter.

Service markets are generally attractive new markets because they typically have relatively high margin.  This is one of the reasons you see companies from telcos to cable companies to utility companies to hardware companies entering into new service and entertainment markets.  It is also the reason you see companies like Cisco exit certain markets.  Cisco recently announced they were selling off their Linksys business and they completely shuttered what was believed to be a successful Flip division simply because these divisions had lower margins than they were accustomed to within their core business units.

For well over a year there have been rumors Apple would enter into the TV business. This would certainly help grow top-line revenue, but the impact on company margin is less clear.  On the other hand, connected watches are a category that are relatively margin rich so they represent a pretty attractive new market for a company looking to maintain margin while growing sales.


Tech has always had a pronounced impact on how we teach – from prehistoric times of passing on survival skills to Johannes Gutenberg’s 1450 invention of the printing press to the most recent two decade push in online education.  Tech within a classroom continues to change with the advent of teaching aids like smartboards and software solutions like blackboard and recent pushes in massive open online courses which are once again redefining how we think about organized higher education.

Today, companies like Knewton are working with universities like Arizona State University to create adaptive learning environments that take advantage of the ability to capture and analyze “big data” (see The New Intelligence in Insider Higher Ed). These new approaches are building adaptive learning systems that essentially measure how much time a given student spends on a particular concept and how well they do on related tests and assignments.  It can then make recommendations specific to the individual.  Modern approaches also restrict students from moving to new material until they have sufficiently mastered a given concept – allowing for individualized timelines.

Approaches likes this could even be developed for live classroom settings wherein short quizzes are built into the curriculum.  With every student having a tablet, smartphone, or computer, deployment and grading of the quiz would be easy and it would force students to stay focused in a classroom that is increasingly dominated by technological distractions.  It would also provide real-time feedback to the instructor on how well students are learning the subject.

College courses and university degrees have long provided a signal to the labor market, but most agree they say less about what one exactly knows. As new data-driven approaches begin to not only test a myriad of concepts, but also record a variety of metrics about one’s ability to master each of those concepts it isn’t difficult to envision an educational world that is driven by thousands of metrics as opposed to one single course listing and a corresponding grade.

There has been significant talk about Facebook’s revenue future.  Two weeks ago Facebook introduced gift cards consumers can use at retailers like Target and restaurants like Olive Garden (see here and here).

Facebook’s CFO, David Ebersman said during the quarterly earnings call in the same week that the long-term potential revenue will remain small for the immediate future. But the potential is interesting and that is where I want to focus for a few minutes.

Here is a screenshot I took from Facebook in December:

Facebook 2012

This screenshot was taken on December 23rd – just days before Christmas.  At this point, it was too late to order a gift online and have it shipped by Christmas.  If you wanted needed to buy a gift you had to go into the store, battling crowds, and hoping inventory was available. Or you could turn to gift cards. You could turn to online gift cards.  I would imagine well over 50 percent of gift cards are bought within two days of actually gifting the gift card.  And I wouldn’t be surprised if it was as high as 75 percent within a 24 hours of actually giving the present to the gift recipient.

An ad like this with the correct timing can become highly relevant. Add to that the behavior of Facebook’s installed base of users. Some 400M users access Facebook everyday. Facebook is also a major platform for birthday wishes, well wishes, and general positive reinforcements when someone is feeling down. I think lower denomination gift cards in the $5 to $10 range could grow into high volume transaction items on the Facebook platform – especially if timed and placed well.

The essential worry of Wall Street analysts and investors is that these streams of revenue will not materialize quickly enough and sufficiently enough before users inevitably move from Facebook to the next big thing.

I’ve talked a lot about curation in the past.  This is simply one form of curation. An extension of curation. Facebook is curating a user experience that (presumably) has relevancy to the end user.  There is significant digital ink spilled on the large volume of information Facebook knows about you.  But what they know about you also has a time component – and this receives little attention.

Approaching gift card sales as they did in the few days leading up to Christmas, Facebook is clearly seeking to take advantage of impulse purchase dynamics.  To date, e-commerce platforms like eBay and Amazon have been successful at being the online clearinghouse for impulse purchases. Arguably they’ve expanded these impulse purchases well beyond what was ever available in the store because of the ability to exponentially and infinitely expand the digital shelf space.

Take for example this screenshot taken from Amazon:amazon impulse purchase positioning This comes from the Amazon page for the Cuisinart DLC-105 Pro Classi 7-Cup Food Processor in White. I literally selected this page at random.  I typed in Cuisinart and picked one of the first Cuisinart food processors listed.  Almost every Amazon page is designed in this way. Below the initial item, you will find the item bundled with one or two other related (and popular) items.  Then you see a series of other items purchased by those who also bought the main item featured on the page.  In this case there are 11 pages of items consumers also purchased. In many ways this is equivalent to the checkout aisle of the brick and mortar store. Right before you finalize your purchase the retailer puts other things in front of you that you might also want.  In the case of digital retailing, the retailer knows a lot about you and also has essentially unlimited shelf space so they can put highly relevant and nearly unlimited choice before you.  Just like with Brick and Mortar stores, these  “impulse purchases” are designed to increase margin for the retailer.

Facebook has additional information not commonly available to other retailers – even other digital retailers.  Facebook knows two unique things.  They potentially know about the intended gift recipient and I think they’ll get even better at identifying the gift recipient. For events like birthdays, they also know the relevant timing. Presumably these two things will enable them to more effectively provide you timely and appropriate offers. Gift cards make sense, but they are just a start.

Facebook’s past is built upon a connection platform, but Facebook’s future will be defined by its ability to curate a meaningful and relevant experience. This experience could be a much larger and more involved retail experience than just gift cards.