There’s a reason that the world fully embraced HTTP but not Gopher or Telnet or even FTP. That’s because the power of the Internet is best expressed through the concept of a network, lots of interlinked pieces that make up something bigger rather than tunnels and holes that end in a destination.

The World Wide Web captured people’s imaginations, and then everything changed.

I was reminded of this while reading a recent interview with Tim Berners-Lee (via TechCrunch). He talked a bit about the power of linking data:

“Web 2.0 is a stovepipe system. It’s a set of stovepipes where each site has got its data and it’s not sharing it. What people are sometimes calling a Web 3.0 vision where you’ve got lots of different data out there on the Web and you’ve got lots of different applications, but they’re independent. A given application can use different data. An application can run on a desktop or in my browser, it’s my agent. It can access all the data, which I can use and everything’s much more seamless and much more powerful because you get this integration. The same application has access to data from all over the place…

Data is different from documents. When you write a document, if you write a blog, you write a poem, it is the power of the spoken word. And even if the website adds a lot of decoration, the really important thing is the spoken words. And it is one brain to another through these words.”

Data is what matters. It’s a point of interest in a larger context. It’s a vector and a launchpad to other paths. It’s the vehicle for leverage for a business on the Internet.

What’s the business strategy at the data layer?

I have mixed views on where the value is on social networks and the apps therein, but they are all showing where the opportunity is for services that have actually useful data. Social networks are a good user interface for distributed data, much like web browsers became a good interface for distributed documents.

But it’s not the data consumption experience that drives value, in my mind.

Value on the Internet is being created in the way data is shared and linked to more data. That value comes as a result of the simplicity and ease of access, in the completeness and timeliness, and by the readability of that data.

It’s not about posting data to a domain and figuring out how to get people there to consume it. It’s about being the best data source or the best data aggregator no matter how people make use of it in the end.

Where’s the money?

Like most Internet service models, there’s always the practice of giving away the good stuff for free and then upselling paid services or piggybacking revenue-generating services on the distribution of the free stuff. Chris Anderson’s Wired article on the future of business presents the case well:

“The most common of the economies built around free is the three-party system. Here a third party pays to participate in a market created by a free exchange between the first two parties…what the Web represents is the extension of the media business model to industries of all sorts. This is not simply the notion that advertising will pay for everything. There are dozens of ways that media companies make money around free content, from selling information about consumers to brand licensing, “value-added” subscriptions, and direct ecommerce. Now an entire ecosystem of Web companies is growing up around the same set of models.”

Yet these markets and technologies are still in very early stages. There’s lots of room for someone to create an open advertising marketplace for information, a marketplace where access to data can be obtained in exchange for ad inventory, for example.

Data providers and aggregators have a huge opportunity in this world if they can become authoritative or essential for some type of useful information. With that leverage they could have the social networks, behavioral data services and ad networks all competing to piggyback on their data out across the Internet to all the sites using or contributing to that data.

Regardless of the specific revenue method, the businesses that become a dependency in the Web of data of the future will also find untethered growth opportunities. The cost of that type of business is one of scale, a much more interesting place to be than one that must fight for attention.

I’ve never really liked the “walled garden” metaphor and its negative implications. I much prefer to think in terms of designing for growth.

Frank Lloyd Wright designed buildings that were engaged with the environments in which they lived. Similarly, the best services on the World Wide Web are those that contribute to the whole rather than compete with it, ones that leverage the strengths in the network rather than operate in isolation. Their existence makes the Web better as a whole.

Photo: happy via

Esther Dyson wrote about a really interesting area of the advertising market in an article for The Wall Street Journal.

She’s talking about user behavior data arbiters, companies that capture what users are doing on the Internet through ISPs and sell that data to advertisers.

These companies put tracking software between the ISP and a user’s HTTP requests. They then build dynamic and anonymous profiles for each user. NebuAd, Project Rialto, Phorm, Frontporch and Adzilla are among several companies competing for space on ISPs’ servers. And there’s no shortage of ad networks who will make use of that data to improve performance.

Esther gives an example:

“Take user number 12345, who was searching for cars yesterday, and show him a Porche ad. It doesn’t matter if he’s on Yahoo! or MySpace today — he’s the same number as yesterday. As an advertiser, would you prefer to reach someone reading a car review featured on Yahoo! or someone who visited two car-dealer sites yesterday?”

Behavioral and demographic targeting is going to become increasingly important this year as marketers shift budgets away from blanket branding campaigns toward direct response marketing. Over the next few years advertisers plan to spend more on behavioral, search, geographic, and demographic targeting, in that order, according to Forrester. AdWeek has been following this trend:

“According to the Forrester Research report, marketer moves into areas like word of mouth, blogging and social networking will withstand tightened budgets. In contrast, marketers are likely to decrease spending in traditional media and even online vehicles geared to building brand awareness.”

We tried behavioral targeting campaigns back at InfoWorld.com with mild success using Tacoda. The main problem was traffic volume. Though performance was better than broad content-targeted campaigns, the target segments were too small to sell in meaningful ways. The idea of an open exchange for auctioning inventory might have helped, but at the time we had to sell what we called “laser targeting” in packages that started to look more like machine gun fire.

This “edge targeting” market, for lack of a better term, is very compelling. It captures data from a user’s entire online experience rather than just one web site. When you know what a person is doing right now you can make much more intelligent assumptions about their intent and, therefore, the kinds of things they might be more interested in seeing.

It’s important to emphasize that edge targeting doesn’t need to know anything personally identifiable about a person. ISP’s legally can’t watch what known individuals are doing online, and they can’t share anything they know about a person with an advertiser. AdWeek discusses the issue of advertising data optimization in a report title “The New Gold Standard“:

“As it stands now, consumers don’t have much control over their information. Direct marketing firms routinely buy and sell personal data offline, and online, ad networks, search engines and advertisers collect reams of information such as purchasing behavior and Web usage. Google, for instance, keeps consumers’ search histories for up to two years, not allowing them the option of erasing it.

Legalities, however, preclude ad networks from collecting personally identifiable information such as names and addresses. Ad networks also allow users to opt out of being tracked.”

Though a person is only identified as a number in edge targeting, that number is showing very specific intent. That intent, if profiled properly, is significantly more accurate than a single search query at a search engine.

I suspect this is going to be a very important space to watch in the coming years.

I spent yesterday at the Right Media Open event in Half Moon Bay at the Ritz Carlton Hotel.

Right Media assembled an impressive list of executives and innovators including John Battelle of Federated Media, David Rosenblatt of DoubleClick, Scott Howe of Microsoft, entrepreneur Steve Jenkins, Jonathan Shapiro of MediaWhiz, Ellen Siminoff of Efficient Frontiers, and Yahoo!’s own Bill Wise and the Right Media team including Pat McCarthy to name a few.

It was an intimate gathering of maybe 120 people.

Much of the dialog at the event revolved around ad exchange market dynamics and how ad networks differ from exchanges. DoubleClick’s Roseblatt described the 2 as analagous to stock exchanges and hedge funds…there are a few large exchanges where everyone can participate and then there are many specialized networks that serve a particular market or customer segment. That seemed to resonate with people.

The day opened with a very candid dialog between Jerry Yang and IAB President Randall Rothenberg where Jerry talked about his approach to refocusing the company and his experiences at Yahoo! to date.

Battelle’s panel later in the afternoon was very engaging, as well. The respective leaders of the ad technology divisions at Yahoo! (Mike Walrath of Right Media), Miscrosoft (Scott Howe of Drivepm and Atlas) and Google (David Rosenblatt of DoubleClick) shared the stage and took questions from John who, as usual, didn’t hold back.

The panelists seemed to have similar approaches to the exchange market, though it seems clear that Right Media has a more mature approach, ironically due in large part to the company’s youth. Microsoft was touting its technology “arsenal”. And DoubleClick wasn’t afraid to admit that they were still testing the waters.

I also learned about an interesting market of middlemen that I didn’t know existed. For example, I spoke with a guy from a company called exeLate that serves as a user behavior data provider between a publisher and an exchange.

There were also ad services providers like Text Link Ads and publishers like Jim Mansfield’s PhoneZoo all discussing the tricky aspects of managing the mixture of inventory, rates and yield, relationships with ad networks, and the advantages of using exchanges.

I’ve been mostly out of touch with the ad technology world for too long.

Our advanced advertising technology experiments at InfoWorld such as behavioral targeting with Tacoda, O & O contextual targeting services like CheckM8, our own RSS advertising, lead generation and rich media experiences were under development about 3 years ago now.

This event was a great way to reacquaint myself with what’s going on out in the market starting at the top from the strategic business perspective. I knew ad exchanges were going to be hot when I learned about Right Media a year ago, but I’m even more bullish on the concept now.

The Internet platform business has some unique challenges. It’s very tempting to adopt known models to make sense of it, like the PC business, for example, and think of the Internet platform like an operating system.

The similarities are hard to deny, and who wouldn’t want to control the operating system of the Internet?

In 2005, Jason Kottke proposed a vision for the “WebOS” where users could control their experience with tools that leveraged a combination of local storage and a local server, networked services and rich clients.

“Applications developed for this hypothetical platform have some powerful advantages. Because they run in a Web browser, these applications are cross platform, just like Web apps such as Gmail, Basecamp, and Salesforce.com. You don’t need to be on a specific machine with a specific OS…you just need a browser + local Web server to access your favorite data and apps.”

Prior to that post, Nick Carr offered a view on the role of the browser that surely resonated with the OS perspective for the Internet:

“Forget the traditional user interface. The looming battle in the information technology business is over control of the utility interface…Control over the utility interface will provide an IT vendor with the kind of power that Microsoft has long held through its control of the PC user interface.”

He also responded later to Kottke’s vision saying that the reliance on local web and storage services on a user’s PC may be unnecessary:

“Your personal desktop, residing entirely on a distant server, will be easily accessible from any device wherever you go. Personal computing will have broken free of the personal computer.”

But the client layer is merely a piece of the much larger puzzle, in my opinon.

Dare Obasanjo more recently broke down the different ideas of what “Cloud OS” might mean:

“I think it is a good idea for people to have a clear idea of what they are talking about when they throw around terms like “cloud OS” or “cloud platform” so we don’t end up with another useless term like SOA which means a different thing to each person who talks about it. Below are the three main ideas people often identify as a “Web OS”, “cloud OS” or “cloud platform” and examples of companies executing on that vision.”

He defines them as follows:

1. WIMP Desktop Environment Implemented as a Rich Internet Application (The YouOS Strategy)
2. Platform for Building Web-based Applications (The Amazon Strategy)
3. Web-based Applications and APIs for Integrating with Them (The Google Strategy)

The OS metaphor has lots of powerful implications for business models, as we’ve seen on the PC. The operating system in a PC controls all the connections from the application user experience through the filesystem down through the computer hardware itself out to the interaction with peripheral services. Being the omniscient hub makes the operating system a very effective taxman for every service in the stack. And from there, the revenue streams become very easy to enable and enforce.

But the OS metaphor implies a command-and-control dynamic that doesn’t really work in a global network controlled only by protocols.

Internet software and media businesses don’t have an equivilent choke point. There’s no single processor or function or service that controls the Internet experience. There’s no one technology or one company that owns distribution.

There are lots of stacks that do have choke points on the Internet. And there are choke points that have tremendous value and leverage. Some are built purely and intentionally on top of a distribution point such as the iPod on iTunes, for example.

But no single distribution center touches all the points in any stack. The Internet business is fundamentally made of data vectors, not operational stacks.

Jeremy Zawodny shed light on this concept for me using building construction analogies.

He noted that my building contractor doesn’t exclusively buy Makita or DeWalt or Ryobi tools, though some tools make more sense in bundles. He buys the tool that is best for the job and what he needs.

My contractor doesn’t employ plumbers, roofers and electricians himself. Rather he maintains a network of favorite providers who will serve different needs on different jobs.

He provides value to me as an experienced distribution and aggregation point, but I am not exclusively tied to using him for everything I want to do with my house, either.

Similarly, the Internet market is a network of services. The trick to understanding what the business model looks like is figuring out how to open and connect services in ways that add value to the business.

In a precient viewpoint from 2002 about the Internet platform business, Tim O’Reilly explained why a company that has a large and valuable data store should open it up to the wider network:

“If they don’t ride the horse in the direction it’s going, it will run away from them. The companies that “grasp the nettle firmly” (as my English mother likes to say) will reap the benefits of greater control over their future than those who simply wait for events to overtake them.

There are a number of ways for a company to get benefits out of providing data to remote programmers:

Revenue. The brute force approach imposes costs both on the company whose data is being spidered and on the company doing the spidering. A simple API that makes the operation faster and more efficient is worth money. What’s more, it opens up whole new markets. Amazon-powered library catalogs anyone?

Branding. A company that provides data to remote programmers can request branding as a condition of the service.

Platform lock in. As Microsoft has demonstrated time and time again, a platform strategy beats an application strategy every time. Once you become part of the platform that other applications rely on, you are a key part of the computing infrastructure, and very difficult to dislodge. The companies that knowingly take their data assets and make them indispensable to developers will cement their role as a key part of the computing infrastructure.

Goodwill. Especially in the fast-moving high-tech industry, the “coolness” factor can make a huge difference both in attracting customers and in attracting the best staff.”

That doesn’t clearly translate into traditional business models necessarily, but if you look at key business breakthroughs in the past, the picture today becomes more clear.

1. The first breakthrough business model was based around page views. The domain created an Apple-like controlled container. Exposure to eyeballs was sold by the thousands per domain. All the software and content was owned and operated by the domain owner, except the user’s browser. All you needed was to get and keep eyeballs on your domain.
2. The second breakthrough business model emerged out of innovations in distribution. By building a powerful distribution center and direct connections with the user experience, advertising could be sold both where people began their online experiences and at the various independent domain stacks where they landed. Inventory beget spending beget redistribution beget inventory…it started to look a lot like network effects as it matured.
3. The third breakthrough business model seems to be a riff on its predecessors and looks less and less like an operating system. The next breakthrough is network effects.

Network effects happen when the value of the entire network increases with each node added to the network. The telephone is the classic example, where every telephone becomes more valuable with each new phone in the network.

This is in contrast to TVs which don’t care or even notice if more TVs plug in.

Recommendation engines are the ultimate network effect lubricator. The more people shop at Amazon, the better their recommendation engine gets…which, in turn, helps people buy more stuff at Amazon.

Network effects are built around unique and useful nodes with transparent and highly accessible connection points. Social networks are a good example because they use a person’s profile as a node and a person’s email address as a connection point.

Network effects can be built around other things like keyword-tagged URLs (del.icio.us), shared photos (flickr), songs played (last.fm), news items about locations (outside.in).

The contribution of each data point wherever that may happen makes the aggregate pool more valuable. And as long as there are obvious and open ways for those data points to talk to each other and other systems, then network effects are enabled.

Launching successful network effect businesses is no easy task. The value a participant can extract from the network must be higher than the cost of adding a node in the network. The network’s purpose and its output must be indespensible to the node creators.

Massively distributed network effects require some unique characteristics to form. Value not only has to build with each new node, but the value of each node needs to increase as it gets leveraged in other ways in the network.

For example, my email address has become an enabler around the Internet. Every site that requires a login is going to capture my email address. And as I build a relationship with those sites, my email address becomes increasingly important to me. Not only is having an email address adding value to the entire network of email addresses, but the value of my email address increases for me with each service that is able to leverage my investment in my email address.

Then the core services built around my email address start to increase in value, too.

For example, when I turned on my iPhone and discovered that my Yahoo! Address Book was automatically cooked right in without any manual importing, I suddenly realized that my Yahoo! Address Book has been a constant in my life ever since I got my first Yahoo! email address back in the ’90’s. I haven’t kept it current, but it has followed me from job to job in a way that Outlook has never been able to do.

My Yahoo! Address Book is becoming more and more valuable to me. And my iPhone is more compelling because of my investment in my email address and my address book.

Now, if the network was an operating system, there would be taxes to pay. Apple would have to pay a tax for accessing my address book, and I would have to pay a tax to keep my address book at Yahoo!. Nobody wins in that scenario.

User data needs to be open and accessible in meaningful ways, and revenue needs to be built as a result of the effects of having open data rather than as a margin-based cost-control business.

But Dare Obasanjo insightfully exposes the flaw in reducing openness around identity to individual control alone:

“One of the bitter truths about “Web 2.0″ is that your data isn’t all that interesting, our data on the other hand is very interesting…A lot of “Web 2.0″ websites provide value to their users via wisdom of the crowds appproaches such as tagging or recommendations which are simply not possible with a single user’s data set or with a small set of users.”

Clearly, one of the most successful revenue-driving opportunities in the networked economy is advertising. It makes sense that it would be since so many of the most powerful network effects are built on people’s profiles and their relationships with other people. No wonder advertisers can’t spend enough money online to reach their targets.

It will be interesting to see how some of the clever startups leveraging network effects such as Wesabe think about advertising.

Wesabe have built network effects around people’s spending behavior. As you track your finances and pull in your personal banking data, Wesabe makes loose connections between your transactions and other people who have made similar transactions. Each new person and each new transaction creates more value in the aggregate pool. You then discover other people who have advice about spending in ways that are highly relevant to you.

I’ve been a fan of Netflix for a long time now, but when Wesabe showed me that lots of Netflix customers were switching to Blockbuster, I had to investigate and before long decided to switch, too. Wesabe knew to advise me based on my purchasing behavior which is a much stronger indicator of my interests than my reading behavior.

Advertisers should be drooling at the prospects of reaching people on Wesabe. No doubt Netflix should encourage their loyal subscribers to use Wesabe, too.

The many explicit clues about my interests I leave around the Internet — my listening behavior at last.fm, my information needs I express in del.icio.us, my address book relationships, my purchasing behavior in Wesabe — are all incredibly fruitful data points that advertisers want access to.

And with managed distribution, a powerful ad platform could form around these explicit behaviors that can be loosely connected everywhere I go.

Netflix could automatically find me while I’m reading a movie review on a friend’s blog or even at The New York Times and offer me a discount to re-subscribe. I’m sure they would love to pay lots of money for an ad that was so precisely targeted.

That blogger and The New York Times would be happy share revenue back to the ad platform provider who enabled such precise targeting that resulted in higher payouts overall.

And I might actually come back to Netflix if I saw that ad. Who knows, I might even start paying more attention to ads if they started to find me rather than interrupt me.

This is why the Internet looks less and less like an operating system to me. Network effects look different to me in the way people participate in them and extract value from them, the way data and technologies connect to them, and the way markets and revenue streams build off of them.

Operating systems are about command-and-control distribution points, whereas network effects are about joining vectors to create leverage.

I know little about the mathematical nuances of chaos theory, but it offers some relevant philosophical approaches to understanding what network effects are about. Wikipedia addresses how chaos theory affects organizational development:

“Most of the focus on chaos theory is primarily rooted in the underlying patterns found in an otherwise chaotic enviornment, more specifically, concepts such as self-organization, bifurcation and self-similarity…

Self-organization, as opposed to natural or social selection, is a dynamic change within the organization where system changes are made by recalculating, re-inventing and modifying its structure in order to adapt, survive, grow and develop. Self-organization is the result of re-invention and creative adaptation due to the introduction of, or being in a constant state of, perturbed equilibrium.”

Yes, my PC is often in a state of ‘perturbed equilibrium’ but not because it wants to be.

The recent blog frenzy over hyperlocal media inspired me to have a look at Outside.in again.

It’s not just the high profile backers and the intense competitive set that make Outside.in worth a second look. There’s something very compelling in the way they are connecting data that seems like it matters.

My initial thought when it launched was that this idea had been done before too many times already. Topix.net appeared to be a dominant player in the local news space, not to mention similar but different kinds of local efforts at startups like Yelp and amongst all the big dotcoms.

And even from their strong position, Topix’s location-based news media aggregaton model was kind of, I don’t know, uninteresting. I’m not impressed with local media coverage these days, in general, so why would an aggregator of mediocre coverage be any more interesting than what I discover through my RSS reader?

But I think Outside.in starts to give some insight into how local media could be done right…how it could be more interesting and, more importantly, useful.

The light triggered for me when I read Jon Udell’s post on “the data finds the data”. He explains how data can be a vector through which otherwise unrelated people meet eachother, a theme that continues to resonate for me.

Media brands have traditionally been good at connecting the masses to eachother and to marketers. But the expectation of how directly people feel connected to other individuals by the media they share has changed.

Whereas the brand once provided a vector for connections, data has become the vehicle for people to meet people now. Zip code, for example, enables people to find people. So does marital status, date and time, school, music taste, work history. There are tons of data points that enable direct human-to-human discovery and interaction in ways that media brands could only accomplish in abstract ways in the past.

URLs can enable connections, too. Jon goes on to explain:

“On June 17 I bookmarked this item from Mike Caulfield… On June 19 I noticed that Jim Groom had responded to Mike’s post. Ten days later I noticed that Mike had become Jim’s new favorite blogger.

I don’t know whether Jim subscribes to my bookmark feed or not, but if he does, that would be the likely vector for this nice bit of manufactured serendipity. I’d been wanting to introduce Mike at KSC to Jim (and his innovative team) at UMW. It would be delightful to have accomplished that introduction by simply publishing a bookmark.”

Now, Outside.in allows me to post URLs much like one would do in Newsvine or Digg any number of other collaborative citizen media services. But Outside.in leverages the zip code data point as the topical vector rather than a set of predetermined one-size-fits-all categories. It then allows miscellaneous tagging to be the subservient navigational pivot.

Suddenly, I feel like I can have a real impact on the site if I submit something. If there’s anything near a critical mass of people in the 94107 zip code on Outside.in then it’s likely my neighbors will be influenced by my posts.

Fred Wilson of Union Square Ventures explains:

“They’ve built a platform that placebloggers can submit their content to. Their platform “tags” that content with a geocode — an address, zip code, or city — and that renders a new page for every location that has tagged content. If you visit outside.in/10010, you’ll find out what’s going on in the neigborhood around Union Square Ventures. If you visit outside.in/back_bay, you’ll see what’s going on in Boston’s Back Bay neighborhood.”

Again, the local online media model isn’t new. In fact, it’s old. CitySearch in the US and UpMyStreet in the UK proved years ago that a market does in fact exist in local media somehwere somehow, but the market always feels fragile and susceptible to ghost town syndrome.

Umair Haque explains why local is so hard:

“Why doesn’t Craigslist choose small towns? Because there isn’t enough liquidity in the market. Let me put that another way. In cities, there are enough buyers and sellers to make markets work - whether of used stuff, new stuff, events, etc, etc.

In smaller towns, there just isn’t enough supply or demand.”

If they commit to building essentially micro media brands based exclusively on location I suspect Outside.in will run itself into the ground spending money to establish critical mass in every neighborhood around the world.

Now that they have a nice micro media approach that seems to work they may need to start thinking about macro media. In order to reach the deep dark corners of the physical grid, they should connect people in larger contexts, too. Here’s an example of what I mean…

I’m remodeling the Potrero Hill shack we call a house right now. It’s all I talk about outside of work, actually. And I need to understand things like how to design a kitchen, ways to work through building permits, and who can supply materials and services locally for this job.

There must be kitchen design experts around the world I can learn from. Equally, I’m sure there is a guy around the corner from me who can give me some tips on local services. Will Architectural Digest or Home & Garden connect me to these different people? No. Will The San Francisco Chronicle connect us? No.

Craigslist won’t even connect us, because that site is so much about the transaction.

I need help both from people who can connect on my interest vector in addition to the more local geographic vector. Without fluid connections on both vectors, I’m no better off than I was with my handy RSS reader and my favorite search engine.

Looking at how they’ve decided to structure their data, it seems Outside.in could pull this off and connect my global affinities with my local activities pretty easily.

This post is way too long already (sorry), but it’s worth pointing out some of the other interesting things they’re doing if you care to read on.

Outside.in is also building automatic semantic links with the contributors’ own blogs. By including my zip code in a blog post, Outside.in automatically drinks up that post and adds it into the pool. They even re-tag my post with the correct geodata and offer GeoRSS feeds back out to the world.

Here are the instructions:

“Any piece of content that is tagged with a zip code will be assigned to the corresponding area within outside.in’s system. You can include the zip code as either a tag or a category, depending on your blogging platform.”

I love this.

30Boxes does something similar where I can tell it to collect my Upcoming data, and it automatically imports events as I tag them in Upcoming.

They are also recognizing local contributors and shining light on them with prominant links. I can see who the key bloggers are in my area and perhaps even get a sense of which ones matter, not just who posts the most. I’m guessing they will apply the “people who like this contributor also like this contributor” type of logic to personalize the experience for visitors at some point.

Now what gets me really excited is to think about the ad model that could happen in this environment of machine-driven semantic relationships.

If they can identify relevant blog posts from local contributors, then I’m sure they could identify local coupons from good sources of coupon feeds.

Let’s say I’m the national Ace Hardware marketing guy, and I publish a feed of coupons. I might be able to empower all my local Ace franchises and affiliates to publish their own coupons for their own areas and get highly relevant distribution on Outside.in. Or I could also run a national coupon feed with zip code tags cooked into each item.

To Umair’s point, that kind of marketing will only pay off in major metros where the markets are stronger.

To help address the inventory problem, Outside.in could then offer to sell ad inventory on their contributors’ web sites. As an Outside.in contributor, I would happily run Center Hardware coupons, my local Ace affiliate, on my blog posts that talk about my remodelling project if someone gave them to me in some automated way.

If they do something like this then they will be able to serve both the major metros and the smaller hot spots that you can never predict will grow. Plus, the incentives for the individuals in the smaller communities start feeding the wider ecosystem that lives on the Outside.in platform.

Outside.in would be pushing leverage out to the edge both in terms of participation as they already do and in terms of revenue generation, a fantastic combination of forces that few media companies have figured out, yet.

I realize there are lots of ‘what ifs’ in this assessment. The company has a lot of work to do before they breakthrough, and none of it is easy. The good news for them is that they have something pretty solid that works today despite a crowded market.

Regardless, knowing Fred Wilson, Esther Dyson, John Seely Brown and Steven Berlin Johnson are behind it, among others, no doubt they are going to be one to watch.