Changing the World: The Business Model

What is the business model for the next internet revolution? In this article, I review web monetization issues, especially that of web 2.0. I propose a monetization solution where any site with users, commercial items, and even visitors, can significantly increase its revenue and reduce marketing and advertising expenses. Our affinity targeting system monetizes itself in the process.

Traditionally, business models for web applications, communities, blogs, etc. are an afterthought. Apps and networking sites dream of reaching critical mass and then selling to Google, Microsoft, Yahoo, etc. Thus the revenue model is actually an exit strategy. This dream has been fueled by the observation that the purchase price for such sites is related to reach ("eyeballs", size of the audience). This is reminiscent of Metcalfe's Law. A more thorough analysis of the market value of social networks was recently posted in TechCrunch, by Michael Arrington.

A very few fortunate web startup founders do not need to consider a business model beyond their big exit, even in the current economic climate. The new owners, however, will be forced to monetize their sexy new purchase. For the vast majority of web startup founders the business model will be important and is often considered and tested from the very start.

The default monetization method is advertising, preferred by 58% of web startups (this figure includes affiliate marketing) according to Bizak. Of the strictly advertising sites, Google's AdSense is adopted by 54%. I imagine this number is higher for web 2.0 social sites. Nonetheless, AdSense earnings per visitor (EPV) are the lowest among the various monetization methods. As an example, Tom OKeefe writes about Mahalo's poor Google AdSense earnings, and Allen Stern predicts that affiliate revenue could surpass Google AdSense revenue for Mahalo in the long-term. Decrying AdSense as "worthless", Tom OKeefe asks "What's Next?".

Many of the hugely popular sites are struggling to better monetize. YouTube, for example, is struggling to justify its $1.65 billion purchase price. Also, Facebook faces a rough road ahead, with "only" $150 million in ad sales in 2007 and projections of $265 million in 2008, and Aidan Henry proposes solutions to the "perennial debate surrounding Twitter's revenue model", and the CEO of Mahalo, Jason Calacanis, even chimes in with his own Twitter business model suggestions.

This struggle may no longer be necessary. Our novel Affinity Targeting technology allows a user to be targeted to entities they are most likely to appreciate, in any domain of life. On-line communities and sites with users can increase their earnings by adding both their site and users into our system. Those users are then targeted to entities of interest (products, services, media, jobs, sites, other users, etc.). Targeting, leading to a commercial transaction, will result in affiliate revenue, part of which is shared with the originating site of the purchasing user. According to Bizak.com, affiliate earnings per visitor are 16 times greater than AdSense earnings. An affiliate model with highly specific user targeting should increase such earnings significantly.

The benefits don't end at monetizing eyeballs; sites and sellers can precisely target users to themselves and their items, thereby increasing sales and reducing costs. Communities, groups and fan clubs all seek to attract enthusiastic members. In our system, users will be targeted to the communities they are most likely to appreciate, leading to increased membership and customers. Also, sellers and providers benefit by precise targeting of users to products and services they are most likely to purchase. This will increase sales, and reduce dependence on marketing, advertising, SEO, etc. All sellers and providers are required to do is profile their products, services, jobs, etc. for the system (in the unique way we need the info) and agree to our affiliate model. There are no other costs to them.

The figure above (click to enlarge) depicts a solution to several critical needs: internet sites and sellers must increase their revenue, reduce expenses, and attract the most ideal new users or members. In our solution, sites and sellers add their existing users (no private information is required) and/or items into the system. Users are then targeted (via the targeting engine) to three different kinds of entities (circles): other users (if they are so inclined), groups (sellers, sites, communities, etc.), and items (products, services, media, jobs, etc.). When a user is targeted to a commercial item and makes a purchase, the seller provides an affiliate fee to the system, part of which is shared with the group that brought the user to the system. Also, if a group added an affiliate item into the system that they are not directly selling (for example, an Amazon.com book), part of any affiliate fee earned from that item is shared with that group. Follow the green arrows to see the flow of money. Note that sites and sellers may contribute users and/or items, and users and/or items may be entered independently of a site or seller.

Our plan is to grow the system organically by bootstrapping it on FaceBook and OpenSocial. We will do this in a way where critical mass never becomes a significant issue. At a certain point the affinity matrix of objects will be large enough to attract sites, communities, sellers and providers. At that point, we will offer our own API, customizable web interface, or client software, such that a site and its users can interact with the system the way the site sees fit. In the beginning we will use existing affiliate and payment processors, but eventually this will likely be done with our own systems. Our affinity engine and business model represents the ideal win-win solution for sites, sellers and users: better targeting, discovery, user satisfaction, monetization, reduced expenditures, etc. Ultimately, we see this targeting system attracting a significant fraction of on-line sites, communities and commercial entities.

The Affinity Graph

Is the Affinity Graph the anticipated Internet Singularity?

Tim Berners-Lee, the father of the World Wide Web, has been talking about this concept of the future "Internet of things." By "things" he means the people and other objects on the internet, and he argues that those things and the connections between them are the key aspects of the web. This, he argues, is the primary evolution of the walled gardens of "Web 2.0" into something far more important. He calls this evolution the Giant Global Graph, while others call it Web 3.0 or the Semantic Web.

The use of the term "Graph" has been met with a bit of consternation by those who argue that we already have the term "network" to describe these connections. Robert Scoble describes the difference in reference to social relationships where your social network is who you know, while your Social Graph describes who you are associated with based on common objects of interest (passions, concerns, politics, religion, work, school, etc.). He says: "The Social Graph is NOT my social network. My Social Network is my friends list. But the Social Graph shows a LOT more than that." A Graph then is not simply the simple connections, but the types and context of connections and the strengths of those connections.

While the Graph will ultimately know what is currently song #3 on your iPod, some metadata about the song, as well as all the other people who have the same song as #3 on their iPods, one must wonder "what's the point"? How does this help me discover that I should be a dolphin trainer, or to find new people that share my way of thinking? Once the monstrous amount of data on the Graph is accessible to robots, many will be applying data mining and filtering algorithms, and massive amounts of CPU, to try to generate usable information about the people and other objects on the web.

Tim Berners-Lee envisioned the ability to create "intelligent agents", sort of like advanced email filters, to perform many of the more tedious tasks, easier and faster. I talked about a similar kind of agent in the post "Your Identity Proxy". Real progress will be achieved when future technology will be able to offer the users a much more personalized and enjoyable experience, and of course better targeting of those users with commercial objects. In practical terms, this will require the storage of as much data as possible about users and their objects so that futuristic computer programs will be able to make sense of the identities of those users and the meanings of those objects, and also to make predictions about the basic affinities between the objects and users. Some even predict that given enough information, "the machine" will begin to transcend the metadata and attain a kind of sentience (or sapience).

This is similar to the ideas of Gary Flake who hypothesized that continued advancements in networked information and other technologies will create a "virtuous cycle" leading to what he terms the "Internet Singularity". As with the Global Graph, we are far from advanced enough technologically to see these concepts realized in the near future.

Let me propose that both the Internet Singularity and the Global Graph are overlapping concepts that are largely achievable today through the Affinity Graph, a major element of this project. As of late 2007, we have had the technology to begin to store the affinity relationships and strengths between users and all other objects on the internet and mobile devices. This is a much simpler abstraction, where we store the most important kind of meaning (affinity) for the typical user. In other words, the most important benefit of the Graph or Singularity, e.g. searching, personalization, and discovery, can be generated, stored and queried in a much more feasible way than is predicted for the Graph, Semantic Web, or Singularity.

With the Affinity Graph, the similarity in meaning of objects, including people, will be known. Universal categorization, classification, hierarchies and affinity matching will all be made fairly trivial. Users will have immediate access to their future favorites in every domain of life; likewise objects (and those that care about them) will know which users are likely to most appreciate those objects (marketers? advertisers? evangelists?). This is the point at which the Utopian dreams of internet visionaries is realized. The Affinity Graph does not make irrelevant other forms of abstractions or metadata upon which computer scientists are free to set loose their strong AI. There are many other kinds of meaning, and those will be explored by computers in time.

The Singularity is here, as is the Global Graph, in ways that are most important to users.

One Degree of Separation

Social networks rely on your primary network - your existing friends and contacts - to introduce you to THEIR friends and contacts. Each of the people in the network are called 'nodes', each with one or more connections to other nodes. Each of those connections is sometimes called a degree of separation; a friend of a friend (FOAF) would then be two degrees of separation. The famous phrase "six degrees of separation" was based on work by psychologist Stanley Milgram who determined that any two Americans, connected in the nation-wide extended network, are separated by an average of five intermediaries, i.e. six steps or degrees.

Despite their connectedness, two people separated by so long a chain are extremely unlikely to ever meet. In fact, we usually only ever meet the friends of our friends: an extremely small fraction of the larger network. Web services like LinkedIn, the business contact network, tracks your chain to three degrees of separation - though I wonder how often the third degrees ever connect. [Friendster tracked the chain even further, and this pursuit has been credited with Friendster's downfall, as tracking long chains is very difficult computationally and has much larger hardware requirements.]

Online Social Networks are not really social, and the network - as degrees of separation - serves mostly to separate. So, if one really wants to 'kill' social nets, one needs to get rid of the 'net' (the multiple degrees of separation that separate people) in order to bring people together. Jyri Engeström argues that social networks should not be based on individual connections between people that can be counted and accumulated, rather people must be connected by shared objects. We agree and take this to the next level by making everything in the virtual community an object, where each object is connected to every other object.

The New Paradigm

As proposed in the last post, what is lacking in the current data islands and the proposed schema solutions is a way of harnessing the true power of the collective to actually reduce information overload and increase discovery. This will require a revolution in content and relationship discovery that can only arise with a completely new kind of information filtration and recommender technology.

"The social web will be powered by recommender systems".
Open Issues in Recommender Systems
John Riedl, Bilbao Recommenders School, 2006

The true power of the collective will be realized with the proper integration of social media, new universal discovery techniques, and associated detailed portable identity and personalization info. The result is a Social Web based on one degree of separation: all people and things are related to each other directly, with each such relationship differing only in type and strength. The following graphic is a representation of such a "one degree" circle of people relationships, but keep in mind that each person is also similarly related to all items, ideas, endeavors, etc. in the system as well.

Critical to this new paradigm are the new universal discovery techniques that I've hinted at previously. Current recommender systems, including collaborative filters, are too primitive and limited to accomplish the task. Instead, we have applied certain bioinformatics concepts to solve the puzzle of simulating the human preference engine without requiring "strong AI". This starts with a quick determination of a person's "core identity", that internal mechanism which is responsible for generating appreciation, and sifting through the chaos and making choices.

Determining that "core identity" is a critical breakthrough as it allows us to quantify the relationship (strength and type) between all people, and between all people and all other things in the system. It also can yield portable data that can be used to quantify such relationships between users and items from multiple data islands, and can even be used in mobile devices and in real-world activity. This discovery system involves no collaborative filtering, psychological testing or interpretation, statistical or stochastic methods, etc.

"But there is no go-to discovery engine - yet. Building a personalized discovery mechanism will mean tapping into all the manners of expression, categorization, and opinions that exist on the Web today. It's no easy feat, but if a company can pull it off and make the formula portable so it works on your mobile phone - well, such a tool could change not just marketing, but all of commerce."
The race to create a 'smart' Google
by Jeffrey M. O'Brien, writing for Fortune Magazine

In addition to the current benefits of the social web, the integration of these universal discovery techniques will allow:

• A brief one-page registration with no need for private information. Qualifies as 'Cold-Start' for people and also items, ideas, endeavors, etc.
• Immediate access to promising relationships of all types, i.e. universal recommendations. These relationships are the predicted interest and affinity between a person and all other people, music, movies, books, recreation, groups, products, services, ads, travel destinations, vocations, jobs, teams, politics, religion, ideas, websites, articles, news items, games, etc.
• Portable data that can be compared and relationships quantified. This portable data can be used between social and data islands, for mobile devices and in real-world activity.
• No language or cultural barriers: no folksonomy or semantic constraints.
• No need for existing relationships. Emphasis is on relationship discovery, though existing friends and contacts are revealing.
• No need to observe history of actions and choices. A one-page registration is enough to provide significantly more information, and better information, than collaborative filters can accumulate.
• The new system will act as a good friend who knows you well and delivers trusted recommendations of all types, both solicited and unsolicited.
• Reduced privacy concerns as personal or demographic data is unnecessary.
• Automatic person-level granularity. Each relationship has a strength and type.
• Universal recommendations allows for highly successful affiliations of all types, direct sales and downloads, and highly targeted advertising as the diverse business model.
• Ratio of discovery to effort is high. No need for constant messages, spam, requests, friend searches, etc.
• Discovery is filtration, so 'information overload' and the 'tyranny of choice' are greatly reduced.
• Enables highly personalized search engine functionality, news aggregation, and many other forms of person-level information filtration.
• Constant excitement of discovery, so no "what's next?" reaction. No limit to novelty and interest, little boredom. No feeling of wasted time.
• Highly useful and usable: the keys to success of any product or service.

Social Standardization and the Death of Social Networks

"...we’re reaching an inflection point where some fundamental conceptions of the web (and social networks) need to change".
from Stop building social networks, by Chris Messina

It seems that everybody is predicting the end of something due to something else, typically calling the later a 'killer app'. Are VOIP and email replacing the phone and fax? Is social media replacing Google search, email, communication in general? Is IM replacing email? Well, who would have predicted that the trusty typewriter would disappear in the span of a few years? It seems many are making another prediction: Social Nets are on their way out, at least in their current configuration. In this post, I'll talk about the problems and proposed solutions.

Social Nets are hugely popular and are obviously doing something right. They were clearly a revolution in online communication and information sharing. Let's first list why people enjoy them. They allow you to:

1. express yourself and try to look cool
2. people-watch / voyeurism / "gawk at strangers"
3. 'collect friends' and compete to see who has more
4. waste time doing semi-fun alone stuff with apps, etc.
5. keep in touch with existing friends (the primary network)
6. make new friends, dates and business contacts (the largely unfulfilled promise of the 'network')
7. manage your personal data
8. exchange knowledge and information
9. re-connect with old friends and colleagues

As for the negatives, here are some of the points mentioned on the blogosphere:

1. 'Friend collecting' is not 'social'. No real communication takes place, and no real friends are made. Checkmarking someone as a friend is not being social. Not much relationship building going on.
2. Information Overload is not reduced, quite the opposite: too many people, messages, spam, etc. There is a limit to our ability to absorb information: our internal filters cannot handle it.

   "There isn’t enough time in the day for any person to find value in what a 1,000 people have to say - our internal filters just won’t allow it. At some point all that information; whether it be valuable or just fluff, becomes nothing more than white noise".
   from Enough with the social crap I think I’m gonna puke, by Steven Hodson

3. "Massive waste of time" / "It takes too much time" / 'Social Net Fatigue'
4. Privacy concerns / 'abuse of trust'. Services track user activity on and off the service, and post some of those activities to the "friends". Combining information from multiple sources may reveal private information.
5. Social nets are 'Walled Gardens'. They are not portable - information is trapped within the bounds of each service. New users must re-enter profile information, must search and re-add network contacts, and must reset notification and privacy preferences for each new social net joined.
6. Social nets are by definition 'network-centric'. Most users are exposed only to friends of friends (i.e. two degrees of separation). This presents an obstacle to discovering true friends and contacts, most of the potential being outside of your network.
7. No Business Model beyond popularity and possibly advertising. Also, because new users on social networks often misrepresent themselves and enter false personal information, demographic data for advertisers is therefore unreliable.
8. The "superficial emptiness"
9. The "what's next?" phenomenon (after exhausting the novelty of the site) / Lack of Innovation
10. Not granular enough - no ability to group friends and contacts in categories, or indicate how close or trustworthy those relationships are.
11. Tired of having to add friends or accept friend requests in all of these networks.
12. Use a given service only because that's where your friends are.

Proposed Solutions:

Many feel that Identity/Info concepts like OpenID, OpenSocial, FOAF, the 'Semantic Web', Microformats, have great potential in solving a few of the above problems.

"a distributed, user-centric identity scheme would destroy almost every "walled garden" social software application on the web".
from Identity Management Will Destroy Social Software, by Brian 'Bex' Huff

The idea is that each internet user would have a single universal and portable profile that would be used and understood by all services, thereby elimiating the need to enter and configure the same information and connections on every new service. Ideally, this would have the effect of removing the walls between services, creating a single large community or 'cloud' where "relationships transcend networks/documents".

The social and data islands that dot the internet can clearly be helped by some kind of standardized profile that can be uploaded to (and modified by) each service. The burden of registration and establishing relationships would be greatly reduced. Such a profile can grow to include all the data that a person might share, including photos and information, music, movie, web site favorites, etc. As long as all services agreed on standardization, this should work pretty well. As an example, browser standardization is largely successful - though differences do exist and can be frustrating for developers and surfers alike.

The Next Revolution:

Schemas, however, will not solve most of the issues mentioned above, and some are made worse (like privacy concerns). Some even argue that standardization and identity aggregation would not be entirely apprieciated. As much as schemas depend on FOAF information, most of the problems with social networks will remain. If one really wants to 'kill' social nets, one needs to get rid of the 'net' part, i.e. the degrees of separation. What is lacking in the current data islands and the proposed schema solutions is a way of harnessing the true power of the collective to actually reduce information overload and increase discovery. The next revolution in content and relationship discovery can only arise with a completely new kind of information filtration and recommender technology.

"The social web will be powered by recommender systems".
Open Issues in Recommender Systems
John Riedl, Bilbao Recommenders School, 2006

The true power of the collective can only be realized with the proper integration of social media, new universal discovery techniques, and associated detailed portable identity and personalization info. The result is a Social Web based on one degree of separation: all people and things are related to each other directly, with each such relationship differing only in type and strength. More on this new paradigm shortly.

The Future of the Internet

I found an interesting analysis of existing applications and ideas about the future of the internet on the CNN website by Jeffrey M. O'Brien, writing for Fortune Magazine. He says:

But there is no go-to discovery engine - yet. Building a personalized discovery mechanism will mean tapping into all the manners of expression, categorization, and opinions that exist on the Web today. It's no easy feat, but if a company can pull it off and make the formula portable so it works on your mobile phone - well, such a tool could change not just marketing, but all of commerce.

"The effect of recommender systems will be one of the most important changes in the next decade," says University of Minnesota computer science professor John Riedl, who built one of the first recommendation engines in the mid-1990s. "The social web is going to be driven by these systems."

I see a growing interest in recommender systems everywhere I look, and I tend to agree with the above that the next big thing likely involves personalized discovery and recommendations. It seems clear that in order to improve the current state of the internet information overload must be reduced as well as the burden of choice - this will require advancements in recommender technology. One can also assume that the internet will continue and expand the benefits of "Web 2.0" and the collaborative internet. These benefits are, like most products and services, increased ease of use and increased usefulness.

Some feel that the "Semantic Web" or similar technologies are the future. Essentially this involves "teaching the machine" about content through the creation of universal, machine readable formats. Those critical of the limited scope of "folksonomies" champion a more standardized approach, thinking that if only people could be compelled to be disciplined in their approach toward organization of content, that some kind of utopia would emerge. There are as many critics of the Semantic Web as there are of folksonomy, and the fact that people have been talking about schemas and such for years, seems to indicate that - short of some radically new approach - there will be no utopia there. Interestingly, it may be a phenomenon called "social network fatigue" that finally forces services to adopt a standardized portable social/data/identity ontology.

The new revolution must also bring people together in much better ways than those that employ the "degrees of separation" format. Online Social Networks are extremely popular because they allow people to keep in virtual contact with their existing friends and contacts, and they can facilitate personal expression and PR. Unfortunately, social nets are not really social, and the network - as degrees of separation - serves mostly to separate. Registering for one of these sites is a rather cold experience unless you already have tons of friends and contacts already registered. Otherwise you have to spam your friends and nag them to register - something that they may not appreciate. The burden of registration and establishing relationships is compounded as more and more social nets are created, each of them requiring the time consuming input of the same personal data.

The next big thing must facilitate discovery of new people based only on similarities of their core identities, rather than focusing only on a user's primary social network. Two identical twins, separated at birth and raised in countries on opposite sides of the planet, speaking different languages, should be able to find each other. Bringing people together must include the separate objectives of: romance, friendship, business relationships, work team formation, roommates, travel and recreation buddies, etc.

In addition to people finding other people of similar core identity, the next big thing will need to do the same for non-human entities, like music, movies, TV, books, news, web pages, articles, games, products, services, vocations, jobs, travel destinations, politics, religion, advertising, or any other activity, enterprise, product, service, endeavor, idea, belief, passion or item.

In order for such matching to be accurate and satisfying for the user, there must be low false positives ("trust busters"), low false negatives ("missed opportunities") and sufficient true positives ("new favorites"). No current recommendation or recommender system comes close to even approaching this goal. Matching cannot be based on identical answers or choices, as there can never be enough questions to encompass all of human individuality. More importantly, people's existing interests in music, books, movies, etc. is not strictly linked to their core identities, but rather often more on prevailing cultural and social influences.

In our short lives, we are unlikely to ever find the people and things that we would most enjoy and appreciate. This is unfortunate.

The new internet revolution must match people to other people and things based solely on that core identity. It must do it with only a brief registration, where, upon registering, you are immediately presented with your ultimate best friends and soulmates, ideal potential business partners, as well as new favorites in every area of life. It should do it without language barriers (i.e. folksonomy or schemas), without the need for a large staff (i.e. Pandora), without a tedious registration (i.e. eHarmony), without having to observe your history (i.e. Amazon.com, Netflix, Last.fm, etc.), without requiring existing friends or contacts (i.e. Facebook, MySpace, LinkedIn, etc.), and it must be completely free for users but able to convert many of those recommendations into revenue.