Chris Dixon

Seems very relevant to today’s music industry, and potentially relevant to the internet/software industry in the near future as patent lawsuits become increasingly common:

The commons leads to overuse and destruction; the anticommons leads to underuse and waste. In the cultural sphere, ever tighter restrictions on copyright and fair use limit artists’ abilities to sample and build on older works of art. In biotechnology, the explosion of patenting over the past twenty-five years—particularly efforts to patent things like gene fragments—may be retarding drug development, by making it hard to create a new drug without licensing myriad previous patents. Even divided land ownership can have unforeseen consequences. Wind power, for instance, could reliably supply up to twenty per cent of America’s energy needs—but only if new transmission lines were built, allowing the efficient movement of power from the places where it’s generated to the places where it’s consumed. Don’t count on that happening anytime soon. Most of the land that the grid would pass through is owned by individuals, and nobody wants power lines running through his back yard.

From The Permission Problem, James Surowiecki, The New Yorker Magazine.  A very worthwhile read.

The rational way to invest in something – a startup, public company, venture capital firm, real estate project, etc. – is to base your decision on an assessment of its fundamental value. The most common way to do this is to try to predict the asset’s future profits. In reality, many of the largest pools of capital in the world – pensions, endowments, and mutual funds – think in terms of “allocations.” This means they start with a model for how to distribute their funds across a set of dimensions, including asset classes, industries, and geographies. This allocation mentality is based partly on prevalent academic theories (the “Capital Asset Pricing Model” or “CAPM”) and partly on the success of certain famous money managers (the “Yale Model“).

Allocation investing has a number of perverse effects on financial markets. For example, in the 80s and 90s venture capital was deemed to be a successful, independent asset class. As a result, many funds decided to allocate some portion of their capital to VC. These pools of capital were so large that they caused the VC industry to grow orders of magnitude larger – many say larger than it should be. In turn, this led to many bad venture investments that drove down returns in the industry (these problems were further exacerbated by the fee structure of VC that encouraged funds to get large and rapidly “put money to work”).

Another perverse effect caused by allocation investing happens in public stock markets when investors decide to allocate a portion of their funds to specific sectors. I recently heard some money managers saying they wanted to allocate portions of their funds to “social media”. Combining this “allocated” demand with a constrained supply (due to the small float of many of these IPOs) can lead to prices that are disconnected from fundamental values. In this scenario, supply will try to match demand, which means mediocre social media companies will go public and non-social media companies will reposition themselves as social media companies or acquire social media companies. They will be chasing the “social premium.”

We saw this happen in the 90s with the rush of companies to reposition themselves as internet companies. In that case, many non-professional investors ended up owning shares in crappy companies when the music stopped. The primary difference now is that the flagship companies like LinkedIn and Facebook have excellent fundamentals. Hopefully this time the market will be discerning and value investing will win out over allocation investing.

A platform is a technology or product upon which many other technologies or products are built. Some platforms are controlled by a single corporation: e.g. Windows, iOS, and Facebook. Some are controlled by standards committees or groups of companies: e.g. the web (html/http), RSS, and email (smtp).

Platforms succeed when they are 1) financially sustainable, and 2) have a sufficient number of developers that are financially sustainable. Fostering a successful developer community means convincing developers (and, possibly, investors in developers) that the platform is a worthwhile investment of time and money.

Developers who create applications for platforms take on all the usual risks related to launching a new product, but in addition take on platform-specific risks, namely:

1. Platform decline: the platform will decline or go away entirely.
2. Subsumption risk: the platform will subsume the functionality of the developer’s application.

The most successful platforms try to mitigate these risks for developers (not just the appearance of these risks). One way to mitigate platform decline risk is to launch the platform after the platform’s core product is already successful, as Facebook did with its app platform and Apple did with its iOS platform. Platforms that are not yet launched or established can use other methods to reassure developers; for example, when Microsoft launched the first Xbox they very publicly announced they would invest $1B in the platform.

To mitigate subsumption risk, the platform should give developers predictability around the platform’s feature roadmap. Platforms can do this explicitly by divulging their product roadmap but more often do it implicitly by demonstrating predictable patterns of feature development. Developers and investors are willing to invest in the iOS platform because – although Apple will take 30% of the revenue – it is highly unlikely that Apple will, say, create games to compete with Angry Birds or news to compete with The New York Times. Similarly, Facebook has thus far stuck to “utility” features and not competed with game makers, dating apps, etc.

Platforms that are controlled by for-profit businesses that don’t yet have established business models have special challenges. These companies are usually in highly experimental modes and therefore probably themselves don’t know their future core features. The best they can do to mitigate developers’ risks are 1) provide as much guidance as possible on future features, and 2) when developer subsumption is necessary, do so in a way that keeps the developer ecosystem financially healthy – for example, by acquiring the subsumed products.

The least risky platforms to develop on are successful open platforms like the web, email, and Linux. These platforms tend to change slowly and have very public development roadmaps. In the rare case where a technology is subsumed by an open platform, it is usually apparent far in advance. For example, Adobe Flash might be subsumed by the canvas element in HTML5, but Adobe had years to see HTML5 approaching and adjust its strategy accordingly. The predictability of open platforms is the main reason that vast amounts of wealth have been created on top of them and investment around them continues unabated.

Reposted from Oct 7, 2010 from cdixon.posterous.com

By “incumbents” I mean the big companies that are loosely competitive to your startup.

- The first thing to do is try to understand the incumbent’s strategy.  For example, see my analysis of Google’s strategy.

- Being on an incumbent’s strategic roadmap is a double-edged sword.  On the one hand, they might copy what you build or acquire a competitor.  On the other hand, if you build a valuable asset you could sell your company the acquirer at a “strategic premium.”

- Incumbents that don’t yet have a successful business model (e.g. Twitter) might think they have a strategy, but expect it to change as they figure out their business model.  An incumbent without a successful business model is like a drunk person firing an Uzi around the room.

- Understand the incumbent’s acquisition philosophy. More mature companies like Cisco barely try to do R&D and are happy to acquire startups at high prices.  Incumbents that are immature like Facebook only do “talent acquisitions” which are generally bad outcomes for VC-backed startups (but good for bootstrapped or lightly funded startups). Google is semi-mature, and does a combination of talent and strategic acquisitions.

- Understand the incumbent’s partnership philosophy.  Yahoo and Microsoft are currently very open to partnerships with startups.  Google and Facebook like to either acquire or build internally. If you don’t intend to sell your company, don’t talk seriously about partnerships to incumbents that don’t seriously consider them.

- Every incumbent has M&A people who spend a lot of their time collecting market intelligence. Just because they call you and hint at acquisition doesn’t mean they want to buy you – they are likely just fishing for info. If they really want to buy you, they will aggressively pursue you and make an offer.  As VCs like to say, startups are bought, not sold.

- Try to focus on features/technologies that the incumbents aren’t good at.  Facebook is good at social and social-related (hard-core) technology.  Thus far they’ve kept their features at the “utility level” an haven’t built non-utility features (e.g. games, virtual goods, game mechanics).  Google thus far has been weak at social and Apple has been weak at web services.

- Try to focus on business arrangements that the incumbents aren’t good at.  Facebook and Google only do outbound deals with large companies.  With small companies (e.g. local venues, small publishers) they try to generate business via inbound/self service. Building business relationships that the incumbents don’t have can be a very valuable asset.

- Be careful building on platforms where the incumbent has demonstrated an inconsistent attitude toward developers. Apple rejects apps somewhat arbitrarily and takes a healthy share of revenues, but is generally consistent with app developers.  You can pretty safely predict what they will will allow to flourish. Twitter has been wildly inconsistent and shouldn’t be trusted as a platform.  Facebook has been mostly consistent although recently changed the rules on companies like Zynga with their new payment platform (that said, they generally seem to understand the importance of partners thriving and seem to encourage it).

- Take advantage of incumbents’ entrenched marketing positioning.  The masses think of Twitter as a place to share trivial things like what you had for lunch (even if most power users don’t use it this way) and Facebook as a place to talk to friends.  They are probably stuck with this positioning.  Normals generally think of each website as having one primary use case so if you can carve out a new use case you can distinguish yourself.

- Consider the judo strategy.  When pushed, don’t push back.  When Facebook adds features like check-ins, groups, or likes, consider interoperating with those features and building layers on top of them.

One of the most important developments of the web 2.0 era is the proliferation of full featured, bidirectional APIs.  APIs provide a way to “federate” web services from a single website to a distributed network of 3rd party sites. Another important web 2.0 development is the proliferation of web Apps (e.g. Facebook Apps). Apps provide a way to make websites “extensible.”

The next step in this evolution is to create web services that are both federated (APIs) and extensible (Apps).

In my ideal world, the social graph would not be controlled by a private company. That said, Facebook, to its credit, has aggressively promoted a fairly open API through Facebook Connect. Facebook has also been a leader in promoting Apps. For Facebook, creating extensible, federated services would mean providing a framework for Facebook Connect Apps – apps that extend Facebook functionality but reside on non-Facebook.com websites.

Consider the following scenario.  Imagine that in the future a geolocation data/algorithm provider like SimpleGeo takes Facebook Places check-in data and, using algorithms and non-Facebook data, produces new data sets, for example: map directions, venue recommendations, and location-based coupons. The combination of Facebook’s data (social graph and check-ins) and SimpleGeo data/algorithms would create much more advanced feature possibilities than either service acting alone.

With today’s APIs, if, say, Gowalla wanted to integrate Facebook plus SimpleGeo into their app*, they would basically have 3 choices:

1) Embed Facebook widgets in Gowalla.  These are simple iframes (effectively separate little websites) that don’t interact with SimpleGeo.  Gowalla would just have to sit and wait and hope that Facebook decided to bake in SimpleGeo-like functionality.

2) Pre-import SimpleGeo data. This significantly limits the size and dynamism of the SimpleGeo data sets and doesn’t incorporate SimpleGeo algorithms, thus severely limiting functionality.

3) Host an instance of SimpleGeo’s servers internally.  This requires heavy technical integration, undermining the main benefit of APIs.

In a world of extensible APIs (or “API Apps”), Gowalla could instead send Facebook data back to SimpleGeo.  The data flow would look something like this:

(Note how there are three parties involved – @peretti calls this a “data threesome”). This configuration is much simpler to integrate – and potentially much more powerful and dynamic – than the other configurations listed above.  You could implement this today, but it would create user experience challenges.  For example, Gowalla would be sending Facebook data to a 3rd party (step 3), which might (depending on the data sent) require explicit user opt-in. Things become more onerous if SimpleGeo wanted to share its own user data with Gowalla. That would require an additional oAuth to SimpleGeo (authorizing step 4).

Allowing websites to be federated and extensible will open up a whole new wave of innovation.  Ideally some spec like oAuth could include the multiple authorizations in a single authorization screen.  Facebook could also do this by allowing 3rd parties to be part of the Facebook Connect authorization process.  Inasmuch as Facebook’s seems to be trying to embed their social graph as deeply as possible into the core experiences of other websites, allowing extensible APIs would seem to be a smart move.

* I have no connection to any of these companies (Facebook, Gowalla, SimpleGeo) and have no knowledge of their product plans beyond their public websites.  I am imagining functionality that Gowalla and SimpleGeo might include someday but for all I know they have no interest in these features – I just picked them somewhat arbitrarily as examples.

It has become customary to use “graph” to refer to the underlying data structures at social networks like Facebook. (Computer scientists call the study of graphs “network theory,” but on the web the word “network” is used to refer to the websites themselves).

A graph consists of a set of nodes connected by edges. The original internet graph is the web itself, where webpages are nodes and links are edges. In social graphs, the nodes are people and the edges friendship. Edges are what mathematicians call relations. Two important properties that relations can either have or not have are symmetry (if A ~ B then B ~ A) and transitivity (if A ~ B and B ~ C then A ~ C).

Facebook’s social graph is symmetric (if I am friends with you then you are friends with me) but not transitive (I can be friends with you without being friends with your friend).  You could say friendship is probabilistically transitive in the sense that I am more likely to like someone who is a friend’s friend then I am a user chosen at random. This is basis of Facebook’s friend recommendations.

Twitter’s graph is probably best thought of as an interest graph. One of Twitter’s central innovations was to discard symmetry: you can follow someone without them following you. This allowed Twitter to evolve into an extremely useful publishing platform, replacing RSS for many people. The Twitter graph isn’t transitive but one of its most powerful uses is retweeting, which gives the Twitter graph what might be called curated transitivity.

Graphs can be implicitly or explicitly created by users. Facebook and Twitter’s graphs were explicitly created by users (although Twitter’s Suggested User List made much of the graph de facto implicit). Google Buzz attempted to create a social graph implicitly from users’ emailing patterns, which didn’t seem to work very well.

Over the next few years we’ll see the rising importance of other types of graphs. Some examples:

Taste: At Hunch we’ve created what we call the taste graph. We created this implicitly from questions answered by users and other data sources. Our thesis is that for many activities – for example deciding what movie to see or blouse to buy – it’s more useful to have the neighbors on your graph be people with similar tastes versus people who are your friends.

Financial Trust: Social payment startups like Square and Venmo are creating financial graphs – the nodes are people and institutions and the relations are financial trust. These graphs are useful for preventing fraud, streamlining transactions, and lowering the barrier to accepting non-cash payments.

Endorsement: An endorsement graph is one in which people endorse institutions, products, services or other people for a particular skill or activity. LinkedIn created a successful professional graph and a less successful endorsement graph. Facebook seems to be trying to layer an endorsement graph on its social graph with its Like feature. A general endorsement graph could be useful for purchasing decisions and hence highly monetizable.

Local: Location-based startups like Foursquare let users create social graphs (which might evolve into better social graphs than what Facebook has since users seem to be more selective friending people in local apps). But probably more interesting are the people and venue graphs created by the check-in patterns. These local graphs could be useful for, among other things, recommendations, coupons, and advertising.

Besides creating graphs, Facebook and Twitter (via Facebook Connect and OAuth) created identity systems that are extremely useful for the creation of 3rd party graphs. I expect we’ll look back on the next few years as the golden age of graph innovation.

With the introduction of the iPhone, Steve Jobs achieved something that might be unique in the history of business: he single-handedly upended the power structure of a major industry.  In the US, before the iPhone, the carriers (Verizon, AT&T, Sprint, T-Mobile) had an ironclad grip on the rest of the value chain – particularly, handset makers and app makers.

Ask anyone who ran or invested in a mobile app startup pre-iPhone (I invested in one myself). Since the carriers had all the power, getting any distribution (which usually meant getting on the handset “deck”) meant doing a business development deal with the carriers. Business development in this case meant finding the right people at those companies, sending them iPods, taking them to baseball games, and basically figuring out ways to convince them to work with you instead of the 5,000 other people sending them iPods and baseball tickets.  The basis of competition was salesmanship and capital, not innovation or quality.

The carriers had so much power because consumers made their purchasing decisions by choosing a carrier first and a handset second. Post-iPhone, tens of millions of people started choosing handsets over carriers. People like me suffer through AT&T’s poor service and aggressive pricing because I love the iPhone so much.

I’ve talked to a number of mobile app startups lately who say their former contacts at the carriers are shell shocked: no one is knocking on their doors anymore. I guess they have to buy their own iPods and baseball tickets now.

Yes, Apple has rejected some apps for seemingly arbtrary or selfish reasons and imposed aggressive controls on developers. But the iPhone also paved the way for Android and a new wave of handset development. The people griping about Apple’s “closed system” are generally people who are new to the industry and didn’t realize how bad it was before.

Google is fighting battles on almost every front:  social networking, mobile operating systems, web browsers, office apps, and so on.  Much of this makes sense, inasmuch as it is strategic for them to dominate or commoditize each layer that stands between human beings and online ads.  But while they are doing this, they are leaving their core business vulnerable, particularly to Amazon.

When legendary VC John Doerr quit Amazon’s board a few months ago, savvy industry observers like TechCrunch speculated that Google might begin directly competing with Amazon:

[Google] competes with Amazon in a number of areas, particularly web services and big data. And down the road, Google may compete directly in other ways as well. Froogle was a flop, but don’t think Google doesn’t want a bigger chunk of ecommerce revenue from people who begin their product searches on their search engine.*

In fact, Google and Amazon’s are already direct competitors in their core businesses. Like Amazon, Google makes the vast majority of its revenue from users who are looking to make an online purchase. Other query types – searches related to news, blog posts, funny videos, etc. – are mostly a loss leaders for Google.

The key risk for Google is that they are heavily dependent on online purchasing being a two-stage process:  the user does a search on Google, and then clicks on an ad to buy something on another site. As long as the e-commerce world is sufficiently fragmented, users will prefer an intermediary like Google to help them find the right product or merchant. But as Amazon increasingly dominates the e-commerce market, this fragmentation could go away along with users’ need for an intermediary.**

Moreover, Google’s algorithmic results for product searches are generally poor. (Try using Google to decide what dishwasher to buy). These poor results might actually lead to short term revenue increases since the sponsored links are superior to the unsponsored ones.  But long term if Google continues producing poor product search results and Amazon continues consolidating the e-commerce market, Google’s core business is at serious risk.

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* Froogle (and Google Products) have been unsuccessful most likely because Google has had no incentive to make them better: they make plenty of money on these queries already on a CPC basis, and would likely make less if they moved to a CPA model.

** Most Amazon Prime customers probably already do skip Google and go directly to Amazon.  I know I do.

It is customary to divide online advertising into two categories: direct response and brand advertising. I prefer instead to divide it according to the mindset of users: whether or not they are actively looking to purchase something (i.e. they have purchasing intent).*

When users are actively looking to purchase something, they typically go to search engines or e-commerce sites. Through advertising or direct sales, these sites harvest intent. Google and Amazon are the biggest financial beneficiaries of intent harvesting.

When the user is not actively looking to buy something, the goal of an online ad is to generate intent. The intent generation market is still fairly fragmented and will grow rapidly over the next few years as brand advertising increasingly moves online. P&G – which alone spends almost $4B/year on brand advertising – needs to convince the next generation of consumers that Crest is better than Colgate. This is why Google paid such a premium for Doubleclick, Yahoo for Right Media, and Microsoft for aQuantive (MS’s biggest acquisition ever).

In 2003, Google introduced AdSense, a program to syndicate their intent harvesting text ads beyond Google’s main property Google.com.  The playbook they followed was: use their popular website to build a critical mass of advertisers; then use that critical mass to run an off-property network that offers the highest payouts to publishers. AdSense became so dominant that competitors like Yahoo quit the syndicated ad business altogether. Today, Google has such a powerful position that they don’t disclose percentage revenue splits to publishers and extract the vast majority of the profits.

It is widely believed that Facebook will soon follow the AdSense playbook by introducing an off-property ad network. They’ll try to use their strong base of advertisers to dominate intent generating ads the way AdSense dominated intent harvesting ads.

But to win the intent generation ad battle, data is as important as a critical mass of advertisers. For intent harvesting, users simply type what they are looking for into a search box. For intent generating ads, you need to use data to make inferences about what might influence the user.

This is what the introduction of the Facebook Like button is all about.  Intent generating ads – which mostly means displays ads – have notoriously low click through rates (well below 1%). Attempts to improve these numbers through demographics have basically failed. Many startups are having success using social data to target ads today. But the holy grail for targeting intent generating ads is taste data – which basically means what the user likes. Knowing, for example, that a user liked Avatar is an incredibly useful datapoint for targeting an Avatar 2 ad.

Publishers who adopt Facebook’s Like feature may get more traffic and perhaps a better user experience as a result.  But they should hope the intent generation ad market doesn’t end up like the intent harvesting ad market – with one dominant player commanding the lion’s share of the profits.

* Most text ads are about intent harvesting and most display ads are about intent generation, but they are not coreferential distinctions. For example, with techniques like “search retargeting” (you do a Google search for washing machines and the later on another site see a display ad for washing machines), sometimes intent harvesting is delivered through display ads.

The brewing fight between Facebook and Zynga is what is known in economic strategy circles as “buyer-supplier hold up.” The classic framework for analyzing a firm’s strategic position is Michael Porter’s Five Forces. In Porter’s framework, Zynga’s strategic weakness is extreme supplier concentration – they get almost all their traffic from Facebook.

It is in Facebook’s economic interest to extract most of Zynga’s profits, leaving them just enough to keep investing in games and advertising. Last year’s reduced notification change seemed like one move in this direction as it forced game makers to buy more ads instead of getting traffic organically. This probably hurt Zynga’s profitability but also helped them fend off less well-capitalized rivals. Facebook could also hold up Zynga by entering the games business itself, but this seemed unlikely since thus far Facebook has kept its features limited to things that are “utility like.”

The way Facebook now seems to be holding up Zynga – requiring Zynga to use their payments system –  is particularly clever.  First, payments are still very much a “utility like” feature, and arguably one that benefits the platform, so it doesn’t come across as flagrant hold up. It is also clever because – assuming Facebook has insight into Zynga’s profitability – Facebook can charge whatever percentage gets them an optimal share of Zynga’s profits.

The risk for Zynga is obvious — if they don’t diversify their traffic sources very soon, they are left with a choice between losing profits and losing their entire business.  But there is a risk for Facebook as well. If buyers of traffic (e.g. app makers) fear future hold up, they are less likely to make investments in the platform. The biggest mistake platforms make isn’t charging fees (Facebook) or competing with complements (Twitter), it’s being inconsistent.  Apple also charges 30% fees but they’ve been mostly consistent about it. App makers feel comfortable investing in the Apple platform and even having most of their business depend on them in a way they don’t on Facebook or Twitter.