The Value of Advertising on the Kindle 0

Amazon recently announced they would sell a new Kindle with “Special Offers”version.  Kindle with “Special Offers” has the same specs as their WiFi-only Kindle but will include advertisements as the screen saver and on the home screen bar.  In exchange, Amazon will only change $114. 

In all likelihood Kindle hardware will one day be free (or close to free) because of cross subsidization (give away the hardware and monetize the content). The Kindle app for other devices is logically already free.  And of course, this go-to-market approach is common for other technology categories like gaming.  Gaming hardware doesn’t drop to zero likely in part because of the retail relationships that must be maintained by the OEM, but it isn’t uncommon to see it sold below cost at different times. With Amazon’s Kindle in other retail channels, this might be the approach Kindle takes.  You also don’t want consumers taking more than they’ll use.  With a registered Kindle account this becomes less of a concern.  I won’t be surprised if the Kindle with “Special Offers” remains exclusively available through Amazon because of the confusion it might cause in other retail chains which might help drive volume back through Amazon. 

Decision Curbs: How the Miracle on the Hudson will Impact You 0

Over the weekend I read William Langewiesche’s recent book Fly by Wire: The Geese, the Glide, the Miracle on the Hudsonwhich chronicles the role electronic control systems play in avionic safety generally and US AIR flight 1549’s miraculous landing on the Hudson river specifically. A fly-by-wire approach is something we will begin to see with more frequency.

In avionic application, the fly-by-wire approach establishes certain parameters that guide the actions of pilots – for example making it impossible to stall the airplane, or obtain more than 2.5Gs which could impact the integrity of the aircraft. Creating bounded ranges and cementing curbs allows for quick, decisive decision-making in times of distress.  Bernand Ziegler – the former head of Airbus, and champion of the fly-by-wire approach explains, “we give you guarantees so you can react as fast as you want without having to worry about breaking the plane.”

Using Events to Drive Retail Traffic 0

BestBuy is apparently holding iPad supply so they will presumably have enough supply on stock and in the stores for an “upcoming event.” This highlights the delicate nature of retailing today.  Physical media is no longer the traffic driver it once was, but today’s traffic drivers aren’t providing the margin that retailers need so events have become the focus to drive traffic (think Black Friday, CyberMonday, etc). More to follow on this topic.

On Privacy 0

I’ve written about Xobni for Outlook in the past, but a recent experience illustrated the role data will play in the future and ultimate implications for privacy. 

When it first launched I tried freecycle and several months ago I signed-up again to see how the service had evolved and was progressing.  Because I knew this would be accompanied by a slew of emails and I didn’t want the frequent emails to hit my Inbox, I filtered them to a separate folder.  I recently perused the folder and noted my xobni window began to update. As you know, Xobni pulls information in from sites like LinkedIn and Facebook.  After matching emails, Xobni will retrieve all available information. When a matched LinkedIn profile exists Xobni pulls in all available including location, title, and current employer.  With 100M+ users now, it is becoming more common to see LinkedIn profiles populated. For unconnected “friends” on Facebook where emails are matched it will pull in what information is allowed by the user – which typically consists of at least the profile photo.   

The emails sitting in my freecycle folder also contain information.  For example, A. W———- is giving away “10 baby pacifiers in excellent/like new condition. 4 of them are girl colors, the other 6 are gender neutral. Nuk and Playskool brands.”  This offer seems logical, her Facebook photo – delivered into my inbox via Xobni – presumably shows her son (age 2.5) and daughter (7 months).

Clearly it isn’t a stretch to presume someone giving away pacifiers has children who recently grew out of pacifier use. But what about Nikki C—– who offered a “potty time elmo doll, need batteries. Also comes with potty, potty time elmo book (interactive sound book-works) small book for elmo. I’m also including a cookie monster and cabbage patch doll.” Sounds like the mother of a young, recently potty-trained child.  In fact, Nikki is a 21 year-old college student and “Independent Childcare Provider” in the DC region. She probably cares for a child that is approaching 3 years-old.   

I could go on, but the point in all of this is information is created (or perhaps relinquished is the more appropriate term) for use in a specific setting. Users relinquish information to specific services to extract value from that service. I doubt Nikki realized I would know what she does and where she goes to school when she sent me an email and A. W—- didn’t know she was telling me the gender and approximate ages of her children or Holly who emailed me her mobile phone number and presumably has children in Hayfield Secondary since she belongs to the Hayfield Secondary network on Facebook. 

None of them likely internalized the fact they were actually emailing ME when they hit send and surely didn’t recognize that computing power would in seconds provide layers of potentially rich information on their personal lives. With the simple addition of their email address to my description of the personas listed above, I could have added to those layers. 

Xobni is first and foremost an email management tool.  LinkedIn and Facebook integration are designed to facilitate that management.  But in a very simple way Xobni shows how information is rapidly aggregated and shared. I’m not a privacy hawk, but the simple example above highlights potential externalities of information sharing.

More, we are just seeing the beginning of an approaching wave of innovation around data aggregation. Data creation – of which we are doing more than ever before – begets organization. With inexpensive computing power data creation also begets more data. Algorithms can identify previously unrecognized information.  In this way, computers take a mosaic approach to information organization – and ultimately reveal thing that hadn’t been explicitly released.  Over the next 36 months we are going to see a plethora of services intent on rearranging information and squeezing out hidden value.  

I’ll write more about it in another post, but I believe one of the key elements behind wildly successful ideas or companies – and especially in the digital realm – are the ability to organize dispersed data and create meaning. This will be a major influence on the companies sprouting in the next few years.     

Users (and especially American users) give their information away and that won’t change.  Many cry foul when this information is misused but we quickly forgive when offered something in exchange. The foundation of (potentially intrusive) mobile coupons/discounts is built on this premise. 

So what do we learn about privacy from all of this? Managing your online identity is no longer solely about controlling what lands on the top results of a search engine query of your name.  Managing your digital identity is about (1) recognizing what information you disseminate where, (2) what information will leak from that sharing, and (3) what the sum of these information tell about you.

Making the Social Graph Linear 0

John Battelle writes about Color, a new social photo app. Color creates a visual (user-generated photos) public (anyone sharing photos through Color) timeline of any given location (using a proximity algorithm). (It is worth noting Dave Winer suggested the need of a “social camera” four years ago.)  Battelle suggests color matters because of location (“colors has the opportunity to be the first breakout application fueled by the concept of “augmented reality”).  Fred Wilson gives his take on Color – suggesting it has promise as a social graph because it implicit.  In other words, location is defining the social graph which will minimize the manual curating users have to do.  Proximity is clearly a key value of services – especially for mobile services.  But proximity should be defined broadly.  It is location – a physical proximity.  It is also time – proximity to know.  It can also be less tangible – proximity to my interests.  I often see individuals looking at these in isolation.  They focus on location being the killer aspect of services – as in LBS. Or time as in “real-time” recommendations.  Or proximity to interests – as in recommendation algorithms.  Nearness to what matters includes place, time, order, or occurrence. If Color – and other services and apps like it – show real value to users it isn’t solely because of location. 

Color also has potential because it makes the social graph linear.  Sensors (cameras, microphones, GPS, etc) are becoming ubiquitous which in turn is enabling mass data collection (photos, sounds, location, temperature, etc).  Because Moore’s Law drives the cost of data retention to zero we will increasingly see these data archived.  Economists love long time series and we are beginning to create a myriad of long time series.  What we’ll do with these long time series is just beginning to be uncovered.  Take for example, MIT researcher Deb Roy’s work on language acquisition. Roy wanted to explore how his son learned language so he filled his house with video cameras to catch every moment.  This exploration was only made possible by inexpensive sensors and the computing power to parse that information (you can see a Ted talk on the topic by Roy here: http://s.dbr.vc/fzXPn6).

One of the key elements of Roy’s work on how language acquisition progresses is his reliance on the linear nature of these data.  His work could have implications on the learning process which could help inform and improve our education methods.  This is just one example.  I’m seeing increasing instances of linear data creation and I suspect we have just begun to see the ways in which linear data will be leveraged and analyzed.

For Color, proximity clearly matters. But more, the linear nature of these data is being overlooked and might in the end represent the most promising aspect of the service.

What Market Share Matters? 0

Both Lessien and John Gruber take on the topic of market share and I think they miss some of the nuances.  

Lessien applies the basic business school approach: 

Large market share attracted developers who built software exclusively for the dominant platform. That software, in turn, created further lock-in as users grew accustomed to the workflows and proprietary data formats that emerged. Typified by Microsoft’s “embrace and extend” strategy, market leadership yielded a nearly permanent advantage, which suffocated competing platforms and deprived customers of choice. Essentially, the historical advantage of dominant market share has been the ability to raise (discriminately) the switching cost of competing platforms.

In other words, there are massive network effects in technology.  These network effects can lead to monopoly rents.   

While she doesn’t do so explicitly, Lessien goes on to suggest these network effects aren’t applicable to mobile. Despite even a commandeering market share, monopoly rents can’t and won’t be created and therefore market share is largely irrelevant.       

Gruber takes a slightly different tack by suggesting market share and profitability are loosely correlated, but that this correlation has been minimized in the world of mobile. In paraphrasing Lessien, Gruber states, “profit share seems a better indicator of success than market share — both today, and historically.”

I think the three of us agree that the most desired applications from a user perspective, the “table stakes applications” that represent the top 85-90 percent of desired applications will be ubiquitous to all platforms. I think we also agree that the perceived horse race created by pundits shouting every month when the market share metrics drop is overdone.  Everyone wants to catch the inflection points, but these inflection points will never materialize as a single number.

But let’s take some of this to its limit.  Developers are constrained.  Big players do have the ability to ensure their services are ubiquitous to all platforms and thanks to web applications the  “table stakes applications” are (or will be) available on the leading mobile platforms. But with what lag? Even a short lag creates network effects. Consumers, knowing that their horse will always finish, but never first (sport analogy for Gruber) will be inclined to change their bet to a platform that gets the newest and next table stakes applications first.

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