The details of what happens with the information we share is often hidden behind long, complicated legal agreements that almost no one reads. If we’re lucky, they are explained in Terms of Service and Privacy Policy documents, sometimes buried out of view, other times forced on us like ransom notes forcing us to state our compliance or leave the site.

It doesn’t have to be that way.

Today, at the Internet Identity Workshop, we officially launch the Standard Information Sharing Label, which makes it easy for websites to say in simple, consistent language what they do with our information, making it easier for individuals to make better decisions about the information we share online.

The Information Sharing Work Group has published a draft specification defining the Standard Label as well as a Kickstarter project to finance its graphic design.

The Kickstarter has a brief video explaining the effort. The official press release is here.

The work is free to use and open to collaborators.

In all my years contributing to the VRM conversation, few projects have made me as proud as I am of the work behind the Standard Label.

Check it out. If you like it, please spread the word and consider chipping into help take this work to the next level.

Normally, I wouldn’t nitpick about this, but there are two key domains where this is vital and I’m knee deep in both: contracts and platforms.

Doc said:

Like, is the customer always the first party and the vendor the second party?

Well, no. So, some clarification.

First and second parties are like the first and second person voices in speech. The person speaking is the first person, and uses the first person voice (I, me, mine, myself). The person being addressed is the second person, and is addressed in the second person voice (you, your, yourself).

And

To sum it up, third parties mostly assist vendors. That is, they show up as helpers to vendors.

The first point is great, and if you continue this further (and make the leap from parties to data providers), you get something like this:

The ownership of “your” and “my” data is usually clear. However, ownership of the different types of “our” data is a challenge at best.  To complicate matters further, every instance of “my data” is somebody else’s “your data”. In every case, there is this mutually reciprocal relationship between us and them. In the VRM case, we usually think of the individual as owning “my data” and the vendor as owning “your data”, but for the vendor, the reverse is true: to them their data is “my data” and the individual’s data is “your data”. Similar dynamics occur when the other party is an individual. I bring my data, you bring your data, and together we’ll engage with “our” data. We need an approach that respects and applies to everyone’s data, you, me, them, everybody..

Which is from my post on data ownership. The trick is that 1st party and 2nd party perspectives are symmetrical.  We are their 2nd party and they are their 1st party. Whatever solution we come up with in the VRM world needs to work for everyone as their own 1st party. Everyone. Including “them”. Including Vendors.

In fact, that’s the only way we can get out of the client-server, subservient mentality of the web. It’s also the only way to make sure that our solutions work even when the “vendor” is our neighbor, our friend, or our family.

This is particularly clear in the work we are doing at the Kantara Initiative’s Information Sharing Work Group. We are creating a legal framework for protecting information individuals share with service providers. As such, it’s vital that the potential ambiguities of language are anchored in rigorous definitions. And what has emerged is that every transaction is covered by a contract between two parties. Not three. Not four. Not one. Two. And to the extent that third (or fourth) parties are mentioned, they are outsiders and not party to the contract. Since we are building a Trust Framework, there is a suite of contracts covering the different relationships in the system, but the legal obligations assumed in each contract have clear and unambiguous commitments between the first and second parties only.

Platforms

But where I think where Doc’s framing most needs a bit of correction is that, in fact, historically, third parties are never presumed to be working for second party. Not in the vernacular and not in any legal context. This presumption only emerges once you add a Fourth Party claiming that it works on behalf of the user. That is, 3rd-party-as-ally-of-the-2nd-Party is a corollary to Fourth Party concept, not a foundation for explaining it.

Take Skype, which I have on my Verizon cell phone. In the contract with Verizon, Skype is a third party application and Skype, Inc. is the third party.  But Skype isn’t working on Verizon’s behalf.

This is not only true in the sense of 3rd party applications whose value proposition is clearly at odds with the 2nd party, it is even more true when it comes to platforms. And especially when you consider the relevance of VRM as a platform for innovation.

In every platform, there are third parties who create apps that run on the platform. Microsoft built Windows, but Adobe built Photoshop. Apple built the iPhone, but Skype built Skype.  For platforms to be successful, they necessarily bring in 3rd party developers to build on top of the platform. These developers aren’t necessarily working on behalf of the platform provider, and it would be a miscarriage of alignment to claim that they are. They are out for themselves, usually by providing unique value to the end user. Some new widget that makes live better.

This becomes even more true when you are dealing with open platforms, or what I called Level 4 Platforms (building on Marc Andreeson’s The 3 Platforms You Meet on the Internet). In open platforms, you actually have 3rd parties helping contribute to the code base of the platform itself.  Netscape adds tables to HTML. Microsoft adds the <marquee> tag.  But here, it is even crazier to imagine that these 3rd parties are acting on behalf of the platform party… because there really isn’t a platform party. Nobody owns the Internet.

I think the right way to think about 4th Parties is that they have a fiduciary responsibility to the 1st party and 3rd parties may or may not.

Fourth Parties answer to the 1st party.

3rd Parties may not answer to anyone.

Personal Data Stores

Personal data stores allow individuals to share online data with service providers. Facebook Connect users can give third-party web sites like Digg, Amazon, and YouTube access to information stored at Facebook, turning Facebook into a personal data store for over 500 million people.

What makes personal data stores special is the seamless sharing with websites for real-time personalization of the web. It’s more than just file back-up or synchronization.  It’s not just publishing “content” to our friends or the public. Personal data stores allow us to bring our information to websites when we want to. It’s a way to treat the user as the point of integration.

Personal data stores can be anywhere, shared with websites whenever we want. Consider giving FedexKinko‘s a link to a Flickr account so they can download photos to print a new calendar. Or giving a new doctor permission to access our personal health history rather than filling out a paper form while we sit in the waiting room. Or giving a website access to our Outlook contact list on our desktop computer so they can give us birthday reminders and gift suggestions. The key is user-managed access, wherever the data lives. Facebook Connect gives this kind of access control over all the data we store at Facebook, enabling web-wide personalization built around the individual.

Mash-ups

In recent years, mash-ups and real-time APIs have made it easier and easier for companies to combine information from different services into a single user experience. Instead of building bigger and more complicated proprietary data silos, companies take advantage of services like Google Maps and IP-address geolocation, using real-time information to enhance their websites.

Some service are even built around other companies’ data: Twitter clients like Seesmic and Tweetdeck, which access our Twitter data on our behalf; Trillian, which works with various instant messaging networks; and Mint, which pulls in our financial data from hundreds of websites. The “real-time web” is constructed on the fly, using linked data and real-time APIs to dynamically customize services for each of us.

Personal data stores let us bring our own data to the mash-up party. Not only do we have better control over who sees what, we can provide more timely, higher quality data than service providers can get from other sources. Effective integration with personal data stores means no more ads for that car we’ve already bought; no more recommendations based on false assumptions. Unfortunately, data in the wild is constantly becoming outdated, miscopied, and misconstrued, because that’s the best companies can do using the billions of dollars worth of proprietary data that’s gathered about us rather than provided by us. Personal data stores easily allow individuals to give the most relevant, most up-to-date information to just those companies we want to do business with. That means not just better data, but more intimate relationships with our favorite companies and organizations.

Perhaps the most liberating aspect of personal data stores is that everyone gets to have as many as we want. We all have our favorite websites for different online activities. As those sites open up their data with a user-driven permissions mechanism, they become personal data stores. So, whether it’s YouTube for videos, Flickr for Photos, Foursquare for location updates, TripIt for travel plans, or RunKeeper for exercise data, we get to bring our best data with us wherever we go. Savvy websites pull in this high quality data to personalize our visits, while those with unique data open it up for use elsewhere to maximize value to their users, which is exactly what Facebook is doing with Facebook Connect.

Facebook Connect

Facebook Connect makes this kind of access simple for everyone, with industry changing adoption rates. Over 66% of the top 100 websites and over 1 million total websites now integrate with Facebook in some way. Nearly 1/3 of Facebook users—over 150 million people—use Facebook Connect every month. Every time we do, we give websites access to information stored in our Facebook accounts, such as our name, gender, names of our friends, and all the posts currently on our wall or posted by us. It’s an archetypal personal data store, with highly credible and timely data in the form of our friend list and our status updates. Sure, Facebook Connect is still far too limited in the amount of information we can store and we lack control over how that information gets used… but architecturally, Facebook has changed the game for a vast portion of the World Wide Web.

To find out what information Facebook is sharing, I built a website called “I Shared What?!?“, an information sharing simulator for Facebook. The site uses javascript and Facebook Connect to display everything it can get from Facebook. Visitors see in specific detail exactly what they share when hitting the “allow” button in the Facebook Connect permissions dialog.

Facebook uses open standard technology to bring mash-ups to a new level, built on information provided directly by the user, in real-time, with minimal fuss or bother. There are shortcomings, of course. A lot of them, but I’ll save those for future posts. For now, think of Facebook as the 800 pound icebreaker of a new way for companies to connect with their customers.

To this veteran VRM evangelist, Facebook has done more in 2010 to usher in the era of the personal data store than anyone, ever. In one fell swoop, Facebook launched a World Wide Web built around the individual instead of websites, introducing the personal data store to 500 million people and over one million websites.

Unexpectedly, Facebook has moved VRM from a conversation about envisioning a future to one about deployed services with real users, being adopted by real companies, today. We still have a lot of work to do to figure out how to make this all work right—legally, financially, technically—but it’s illuminating and inspiring to see the successes and failures of real, widely-deployed services. Seeing what Amazon or Rotten Tomatos or Pandora do with information from a real personal data store moves the conversation forward in ways no theoretical argument can.

There remain significant privacy issues and far too much proprietary lock-in, but for the first time, we can point to a mainstream service and say “Like that!  That’s what we’ve been talking about. But different!”

The term “ownership” simply brings too much baggage from the physical world, suggesting a win-lose, us-verses-them mentality that retards the development of rich, powerful services based on shared information.

Anyone up for sacred cow cheeseburgers?

I’m a member–and a big fan–of Steve Holcombe‘s “Data Ownership in the Cloud” LinkedIn group and I love the efforts of the Dataportability guys and am a big supporter of the Privacy and Public Policy work group at Kantara. There is a lot of good work being done by folks trying to figure out how to give people greater control over the use of data about them (privacy) and gain access to data they use or created (dataportability).

Unfortunately, sometimes the arguments behind these efforts are based on who owns–or who should own–the data. This is not just an intellectual debate or political rallying call, it often undermines our common efforts to build a better system.

Consider this:

1. Privacy as secrecy is dead
2. Data sharing is data copying
3. Transaction data has dual ownership
4. Yours, mine, & ours: Reality is complicated
5. Taking back ownership is confrontational

Privacy as secrecy is dead

First, the data is pretty much already out there. The issue isn’t “How do we keep data from bad people,” it’s “How do we keep people from doing bad things with data?” DRM and crypto and related technology as the sole means to prevent data leakage and data abuse are failures. Sooner or later, the bad guys break the system and get the data.  Sure, there are smart things we can do to protect ourselves. Just like we wear seatbelts and lock our front doors, we should also use SSL and multi-factor authentication, but we can’t count on technology to keep our secrets. We need solutions that work even when the secret is out.

In fact, privacy isn’t about information we keep secret. It is about information we have revealed to someone else with expectation of discretion, e.g., when we tell our doctor about our sexual activities. It’s no longer a secret from the Doctor, but because it is private, we have rules that keep the information from being used inappropriately. Most of the time, with most doctors, it works. Those few who break those rules are dealt with through legal means, both civil and criminal, as well as social approbation. So, because we inherently need to release data to different parties at different times, we can’t control it through secrecy alone. Instead, we need to build a framework for preventing abuse when others do have access to sensitive information. Like in the case with our doctor, we want our service providers to have the data they need to provide the highest quality services.

Data sharing is data copying

Second, in the world of atoms, there can only be one of a thing, which is the reverse of the world of bits. With atoms, even if there are copies, each copy is itself a singular thing. Selling, transferring, or stealing a thing precludes the original owner from continuing to use it.

This isn’t true for information, which can easily be sold, transfered, and stolen without disturbing the original version. In fact, the entire Internet is basically a copy machine, copying IP packets from router to router, as we “send” images, web pages, and emails from user to user and machine to machine–each time a new copy is created whether or not the originating copy is deleted. To think of bits as if they were ownable property leads to attempted solutions like DRM that try to technologically prevent access to the information within the data, which is only good until the first hacker cracks the code and distributes it themselves. Instead, if we build social and legal controls on use, we can give information more freely, but under terms set by each individual when they share that information. Enforced by social and legal rather than purely technological means, this makes the most of the low marginal cost of distributing  online, while retaining control for contributors.

Transaction data has dual ownership

Image via Wikipedia

Third, much interesting data is actually mutually owned… which means the other guy can already do whatever the heck they want with it.  Consider web attention data, the stream of digital crumbs representing the websites we’ve visited and any interactions at each: all our purchases, all our blog posts, all our searches. Everything. Some folks argue that we own that data and therefore have the right to control the use of it. But so too do the owners of the websites we’ve been visiting. We don’t own our http log entries at Amazon. Amazon does. In fact, in every instance where two parties interact, where we engage in some transaction with someone else, both parties are co-creating that information. As such, both parties own it. So, if we tie the issue of control to ownership, then we’ve already lost the battle, because every service provider has solid claims to ownership over the information stored in their log files, just as we, as individuals, own the browsing history stored on our hard drive by Firefox, Internet Explorer and Chrome.

In the movie Fast Times at Ridgemont High, in a confrontation with Mr. Hand, Spicoli argues “If I’m here and you’re here, doesn’t that make it our time?”  Just like the time shared between Spicoli and Mr. Hand, the information created by visiting a website is co-created and co-owned by both the visitor and the website.  Every single interaction between two endpoints on the web generates at least two owners of the underlying data.

This is not a minor issue. The courts have already ruled that if an email is stored for any period of time on a server, the owner of that server has a right to read the email.  So, when “my” email is out there at Gmail or AOL or on our company’s servers, know that it is also, legally, factually, and functionally, already their data.

Yours, mine, & ours: Reality is complicated

Fourth, when two parties come together for any reason, each brings their own data to the exchange. We need a framework that can handle that. Iain Henderson breaks down this complexity in a blog post about your data, my data, and our data, talking about an individual doing business with a vendor, for example, someone buying a car.

“My data” means data that I, as an individual have that is related to the transaction. It could include the kind of car I’m looking for, my budget, and estimates of my spouse’s requirements to approve of a new purchase.

“Your data” means data that the car dealer knows, including the actual cost of the vehicle, the number of units in inventory, the pace of sales, current buzz from other dealers.

“Our Data” means information that both parties have in common. That could be Shared Information, explicitly given by one party to the other in the course of the deal, such as a social security number so the dealer could run a credit check. It could be Mutual Information, generated by the very act of the transaction, such as the final sale price of the vehicle. Or, it could be Overlapping Information, which each party happens to know independently, such as the Manufacturer Suggested Retail Price (MSRP) of a vehicle (which we found online before heading to the dealership).

The ownership of “your” and “my” data is usually clear. However, ownership of the different types of “our” data is a challenge at best.  To complicate matters further, every instance of “my data” is somebody else’s “your data”. In every case, there is this mutually reciprocal relationship between us and them. In the VRM case, we usually think of the individual as owning “my data” and the vendor as owning “your data”, but for the vendor, the reverse is true: to them their data is “my data” and the individual’s data is “your data”. Similar dynamics occur when the other party is an individual. I bring my data, you bring your data, and together we’ll engage with “our” data. We need an approach that respects and applies to everyone’s data, you, me, them, everybody.

In these complex Venn diagrams of ownership, it is more important who controls the data than who owns it.  We’ve already lost the crudest form of control–secrecy–and we are going to continue to lose more as we opt-in to seductive new services based on divulging more and more information: our purchase history, browsing activity, and real-world location data. But we still need to control how all this data is used, to protect our own interests while still enjoying the benefits of the great big copy machine that is the Internet.

Taking back ownership is confrontational

© Regien Paassen | Dreamstime.com

Fifth, we don’t need to pick a fight to change the game. There is a lot of data out there that many of us believe we should have control over. I agree. A lot of people argue that we should have the right to exclude other people’s use because we own the data, because it’s ours in some legal, moral, or ethical framework. The problem is, those other people already have it, and they also believe that they are legitimate owners. In fact, many of them paid for that data, buying it from data aggregators who compile all sorts of things about people, from both public and private sources. This entire ecosystem of customer data is a multi-billion dollar business and every single player “owns” the data they are working with. So if we focus our energy in claiming ownership over that same data in order to take control, we are framing the conversation as a fight, a fight against a powerful, well-healed, well-funded, entrenched bunch of opponents.

Most of these “opponents” are the very people we are trying to win over to our way of thinking. These are the vendors we want to embrace a new way to do business. These are the technologists we want to transform their proven, value-generating CRM systems to work with our data on our terms, instead of their data on their terms. Arguing over ownership puts these potential allies on the defensive, when what we really want is their collaboration.

From Ownership to Authority, Rights, and Responsibilities

Rather than building a regime based on data ownership, I believe we would be better served by building one based on authority, rights, and responsibilities. That is, based on Information Sharing.

• Who has the authority to control access and use of particular information?
• What rights does a party have in using and distributing a piece of information?
• What responsibilities does an information user have to others with respect to that information?

Let’s stop arguing about who owns what and start figuring out how we can share information in ways that allow everyone to win.

When we collect all of our information into a single conceptual repository, and then share access to it with service providers on our own terms, we create a high quality, highly relevant, curated personal data store. This allows us to bootstrap a control regime over all of our data in a way that creates new value for us and for our service providers. Now, instead of iTunes Genius or a Last.FM scrobbler only having access to our media use with their service, they can provide recommendations based on all the information stored in our personal audio data store. We get better recommendations and they get better data to drive their services. This personal data store is entirely under the authority of the user, sharing information with service providers according to specific rights and responsibilities.

The Information Sharing approach neatly sidesteps the complexities involved in privacy and dataportability issues of the information already known by service providers. These remain serious issues, worth addressing. Resolving them will require long term investment in the legal, regulatory, moral, and political systems that govern our society. Fortunately, sharing the information in our personal data store can begin almost immediately once we have working specifications.

This controlled sharing of information will dramatically increase our comfort level when revealing our intentions and interests. We would have control over the use–and would be able to prevent abuse–of that information, while making it easy for service providers to improve our lives in countless ways.

At the Information Sharing Work Group at the Kantara Initiative, Iain Henderson and I are leading a conversation to create a framework for sharing information with service providers, online and off. We are coordinating with folks involved in privacy and dataportability and distinguish our effort by focusing on new information, information created for the purposes of sharing with others to enable a better service experience. Our goal is to create the technical and legal framework for Information Sharing that both protects the individual and enables new services built on previously unshared and unsharable information. In short, we are setting aside the questions of data ownership and focusing on the means for individuals to control that magical, digital pixie dust we sprinkle across every website we visit.

Image by hegarty_david via Flickr

Because the fact is, we want to share information. We want Google to know what we are searching for. We want Orbitz to know where we want to fly. We want Cars.com to know the kind of car we are looking for.

We just don’t want that information to be abused. We don’t want to be spammed, telemarketed, and adverblasted to death. We don’t want companies stockpiling vast data warehouses of personal information outside of our control. We don’t want to be exploited by corporations leveraging asymmetric power to force us to divulge and relinquish control over our addresses, dates of birth, and the names of our friends and family.

What we want is to share our information, on our terms. We want to protect our interests and enable service providers to do truly amazing things for us and on our behalf. This is the promise of the digital age: fabulous new services, under the guidance and control of each of us, individually.

And that is precisely what Information Sharing work group at Kantara is enabling.

The work is a continuation of several years of collaboration with Doc Searls and others at ProjectVRM. We’re building on the principles and conversations of Vendor Relationship Management and User Driven Services to create an industry standard for a legal and technical solution to individually-driven Information Sharing.

Our work group, like all Kantara work groups, is open to all contributors–and non-contributing participants–at no cost.  I invite everyone interested in helping create a user-driven world to join us.

It should be an exciting future.

This material is based upon work supported by the National Science Foundation under Award Number IIP-08488990. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author and do not necessarily reflect the views of the National Science Foundation.

I’m looking forward to writing a bit more this year, opening the conversation up about portable contexts and user driven services. My work with Project VRM and the Kantara Initiative‘s Information Sharing and User-Managed Access Work Groups will continue to be a big part of that.

I’m also looking forward to some interesting new product and service releases, from SwitchBook, MyDex, The Mine!, and others in the VRM community, as well as updates and innovations from Scanaroo, Kynetx and Azigo and others. Also, Doc Searls‘ upcoming book on the Intention Economy promises to be an intriguing read. It should be a good year for VRM.

Best of luck to you and for your own plans for 2010. May it be a stand-out year for all of us.

From cable TV to YouTube, from newspapers to blogs, from Wal-Mart to eBay, from Ma Bell to the Internet, the shift from centralized, structured systems of authority to emergent, collaborations between individuals has been reshaping our political, social, and economic world for generations. This is a trend that has driven—and been driven by—the massive success of the Internet, email, the World Wide Web, eBay, Google, RSS, FaceBook, YouTube, and Twitter. Each of these examples took an existing model and made it more user driven: networking, messaging, electronic publishing, buying & selling, content discovery & advertising, news aggregation/syndication, online video, status updates.

The conclusion: companies which find ways to be more user driven are more valuable, more profitable, and more successful.

What does it mean to be “user driven”? At its most basic, it means putting the user in charge, in some way. Fully realized, it means putting the user at the center of the system, as a point of integration, origination, and control. We call these fully realized systems “User Driven Services”.

User Driven Services put users in charge. Users start each interaction, manage the flow of the experience, and control what and how data is captured, used and propagated.  Users are the cause and the controller, working with service providers to co-create collaborations that create value for all parties.

From self-serve gas stations and soda fountains to ATMs and self-checkout grocery stores, companies have been putting users in charge of different aspects of their services for years. With GetSatisfaction—which allows users to self-organize for cooperative customer support—and Facebook—which provides social context for user-generated content—users are not just self-servicing, they provide the core content behind the user experience. Now, through user-centric Identity and API access to most popular online services (Flickr, Twitter, Facebook, etc.), users can direct which parts of their experience are serviced by which providers, allowing unprecedented realtime flexibility in service creation.

User Driven Services are redefining how we interact, how we manage our businesses, and how we engage in both public and personal conversations. Businesses and organizations that want to thrive in this new reality would do well to help co-create a new mutually beneficial marketplace for products, services, and ideas. Individuals, participating in this rising tide of personal power, have an opportunity to coordinate with each other and with service providers to craft a future that meets all of our needs, as individuals, entrepreneurs and business people.

Terminology

A few key terms:

System: a group of independent but interrelated elements engineered to operate as a unified whole.

(The systems to which we refer are not natural or conceptual systems, but rather, operating mechanisms designed and implemented to perform intended functions.)

User: any individual interacting with a system.

Service: a value generating experience available to users through interactions with a system; also the system providing such experiences.

User Driven Services: services that maximize value creation by maximizing user control and authority.

Characteristics

User Driven Services have the following characteristics:

1. Impulse from the User
2. Control
3. Transparency
4. Data Portability
5. Service Endpoint Portability
6. Self Hosting
7. User Generativity
8. Improvability
9. Self-managed Identity
10. Duty of Care

We will explore each of these characteristics in a series of articles over the next few weeks.

No longer is it sufficient for companies to package a value proposition on their website and then drive traffic to it through ads, search engine optimization, and reciprocal links. Today companies must find ways to provide a value proposition wherever the user might be: on Facebook and Twitter, on their iPhones, and even through 3rd party applications accessing deep into the company’s datasphere through APIs and webhooks.

The Internet is reconfiguring around the user, wherever people happen to be.

I’ve been talking with folks in the VRM community about this topic over the last few years. VRM is, at its core, about starting with the user, re-engineering systems to maximize user freedom and control, and placing the user at the point of integration.  Or, as Doc Searls puts it, creating tools for “both independence and engagement”.

For example, I’ve led several discussions at various VRM workshops on what I call “user driven search“: what would happen if the user were truly in control of all the data related to their search and could engage any Search provider they like with the full scope of that information and under the user’s terms?

In the last several months, I have been advocating a new term has that captures the core direction of both VRM and User Driven Search: “User Driven Services”.

When you configure your services around the user as the primary point of origination, integration, and control, you are building User Driven Services.

Over the next few weeks, I’ll dive into what we mean by User Driven Services; consider it a warm up for both the VRM West Coast Workshop 2009 and the Internet Identity Workshop.

More …

• Teleconference 2008 06 18
• Teleconference 2008 07 02
• Teleconference 2008 08 13
• Teleconference 2008 09 24
• Teleconference 2008 10 08
• Face to Face 2008 October

The premise is simple: if users know they are safe giving personal data, they will give it more freely. Limits on long term data mining (and its attendant offensive behavior of junk mail, spam, and telemarketing) paradoxically increase data sharing and enhance the ability of vendors to provide more meaningful engagement at the moment of the transaction. Less long term data retention leads to more real-time data provided by users, resulting in better customer experiences, and more profit for vendors.

Until recently, this was a theoretical argument, a belief by those of us promoting VRM. As Doc Searls puts it, “A free customer is more valuable than a captive one.”

Now we have evidence of just how valuable that can be.

Jared Spool shares with us the real-world example of a redesign in the direction of the “One Night Stand” that created $300 million in value in the first year: [excerpt edited for brevity. see full article for details]

Now that’s real money.

Hat tip to Abhijit Nadgouda of iface thoughts.

I had heard a bit about this before and it sounded great… but there’s always such a drive to just start coding! Before I reach Carolyn Snyder’s excellent Paper Prototyping, I hadn’t realized what I was missing.

The key difference from what you might be thinking–and definitely what I was thinking–is that paper prototyping isn’t just about doing mockups of the UI and asking users for feedback. It means recreating the a subset of the core user experience using a paper-based model, with a human “computer” and the user interacting not with the facilitators or testers, but directly with the pieces of paper, by pointing for hovering, touching for clicking and writing for typing.

The results were amazing.

We took two weeks to develop & construct a paper prototype for our upcoming Search Map software, which is the first implementation of the SwitchBook approach to User-driven Search (which is the focus of our work with the VRM community). That was followed by one week doing the actual testing.

To build out a paper prototype like this you have to have a critically specific definition of what it is you are building. Depending on how early you are in the gestation of your software idea, this might be impossible. But if you have a pretty good idea of the basics, the paper prototype will force you to actually write down both

• a subset of tasks in sufficient detail for the user and the prototype to do with paper assets, and
• create the pieces of paper that represent every window, every menu, every dialog box, every state in the interface.

It felt like we went through three revisions of our core UI before we actually had any users. We found there were so many assumptions hidden in our initial requirements documentation that we were missing key parts of the user experience. And then, by mapping out those parts of the experience, we made significant leaps in simplifying and unifying the overall design.

Prior to the actual testing, we first did a dry run with a fellow associate as a user. This was eye opening. Not only did we identify a few assets we were missing, we realized we had several key assumptions that we had overlooked in our design. These assumptions led us to revise the paper prototype significantly, leading to an even better run through with the live testers.

This pattern repeated itself for everyuser. Snyder strongly suggested doing just a handful of tests, no more than two per day. So, 4-6 testers over two-three days. After two weeks building the prototype, I was thinking we should have more testers to really get the value out of this thing. But after the trial run, I realized that there is so much opportunity to update & improve between tests, that you want to immediately assimilate each session and update the prototype.

That is the real beauty of the paper prototype.  Because it is just paper… and in particular just sketches on paper–not a beautifully designed custom UI–it is trivial to change. We were evolving in leaps and bounds between every test, taking out portions of the interface, creating new icons, adding buttons here and removing them there, even updating dialog boxes in mid-test.

It would be hard to overstate how powerful it was to engage in such rapid evolution based on real user feedback. With ~3 revs in the construction phase, 1 with our trial run, and 4 more revisions from each test, I estimate a good 8 substantial revisions to our design in just three weeks.

Our timing for this exercise was just about perfect. We just started a 6 month dev cycle in January, after over a year of internal development (largely on the server side with a basic architectural prototype on the client). The core experiential basics had been fairly stable, and we were ready to integrate a lot of conceptual learning into a new rev. So, we had a lot of detail about what we wanted to do, and were in a good point to take a moment, document our requirements rigorously, and sit down with users to see what really works. For the record, we spent about three weeks in requirements engineering prior to working on the paper prototype (which was another three weeks of effort). I don’t know if I’ve ever spent a more useful 6 weeks in any programming project.

We also quickly saw the limitations of this approach. Of course, it was slow. We joked that the McKinney 5000 was operating at about 110hz. (Sam McKinney acted as our “human” computer for the testing–and did a great job I must say.) A good portion of our user experience depends on finding “flow” during advanced searches across many different websites and different search providers. Just keeping track of the user’s behavior was a breakneck task… simultaneously updating the screen to indicate the real-time feedback and recommendations from our server was even harder. The result is that although we got to test our core workspace, the technique was too slow to really test the work flow.

So, Carolyn Snyder, thanks so much for the easy and thorough guide to paper prototyping. It was an amazing exercise for our whole team. And for those of you who are working through the details with disruptively innovative software, I encourage you to try it. I think you too will be amazed at your results.

p.s.

My apologies that we didn’t get any pictures of the experience. We were so busy doing it, nobody stopped to capture the look & feel of the interactions.

Problem Domain

The distributed nature of the web is a big part of its power–nobody needs to ask permission from a central authority to use it or create with it. However, that disaggregation limits the cohesion for sophisticated uses, leaving users to hobble together ad-hoc mash-ups of value from multiple, diverse service providers.

For example, the average travel planner spends 29 days from their first query to their first purchase. No tool I know of facilitates that entire process effectively.

Solving this problem in a general way—while retaining the authority of the individual and the flexibility of open systems—is perhaps the greatest opportunity for VRM. The personal data store and VRM relationship services are two prongs of an architectural shift for enabling this kind of aggregation while remaining open. Once you put the user in the driver’s seat, with coherent controls over the flow and the data, the experience can integrate around the user, even as they drive anywhere on the Internet.

Solution

Kynetx’s solution is built on one primary capability:

A rules engine (and language) for contextual customization based on strong identity-based claims, using the user-centric Identity of Information Cards.

This puts Kynetx squarely in the web augmentation service business. Adaptive Blue (and their Glue product) is perhaps the most sophisticated approach to this space, but Yahoo’s Toolbar also augments web pages, as does Skype (putting its SkypOut button on any phone # it recognizes), and the granddaddies of all web-augmentation services are the ad blocker plug-ins that remove banner ads on websites.

I distinguish web augmentation from web media enhancements, like PDF and Flash and Java, in that the latter are embeddable or downloadable extensions to the core HTML/http architecture of the web, while augmentation services provide third-party manipulation of website presentation on behalf of the user. They actually tweak the web page as the user sees it, rather than offering websites a new way to package content or functionality.

Web augmentation isn’t new, but it is gaining adoption and breadth. There is a low-grade market war going on in this space. While browsers define the official battleground of the World Wide Web; augmentation services are the guerilla warriors of next generation browsing. The approach that reaches ubiquity first will create significant value throughout the architecture: for users, software vendors, and service providers.

So, the question that comes to my mind is where does Kynetx fit into all of this?

The value proposition of a rules-engine for customization is powerful, if that engine makes it easy to leverage strong identity. Every website will, imo, want to take advantage of the unique value of user-centric identity and  Information Cards in particular. However, rewriting your customization to do that will take resources and that will slow adoption. If Kynetx can simplify how websites plug- in to the Identity meta-layer that sounds like a real value.

Gaps

There are however, several gaps that I see in Kynetix’s approach mapped out in the white paper.

First, who are the target developers: websites or Third party services. Or both?

It’s not clear to me if the primary authors of KRL rulesets (and hence Kynetx’s customers) will be the destination website developers or third party augmentation services. For example, . Adaptive Blue‘s Glue augments web pages so that things like movies can be recognized across domains for social commentary, ratings, and sharing. That means that Glue modifies the presentation of web pages at IMDB, Netflix, Amazon, Blockbuster, etc. In this pattern, it is the third-party, Glue, that would be running KRL rulesets, not the websites.

Is this the intended architecture for Kynetx? Is the point of the Kynetx Information Card to provide authorization by the user to allow services like Glue to augment their web experience, while the rest of the plug- in handles injection into the web page within the browser?

Or, is the main point that web services themselves would leverage Kynetx’s Information Card approach to manage third party identity for customization? For example, so Hertz could seamlessly provide AAA or AARP discounts if, and only if, the appropriate AAA or AARP information cards (KIX) are presented by the user? In this case, Hertz writes the customization, but doesn’t need to know upfront what the user’s affiliations might be.

If the first case is intended, the white paper doesn’t do a good job explaining how this fits into a larger, open ecosystem, nor does it highlight this unique architectural opportunity. If a user wants Orbitz to help augment its travel planning experience, even when it is at Expedia or Southwest airlines or Hilton.com, it would be great to do that in a secure, authorized, privacy-sensitive way. But it isn’t quite clear if this is the point of Kynetx’s approach. (Although it is a great opportunity, one that r-buttons and SwitchBook see in the not-so-far future).

If the second case is the goal, it isn’t clear to me why Kynetx is better than other customization frameworks. With a card selector and cards issued from the right authority, users can already present AAA or AARP credentials to websites, which in turn can integrate that information into their existing CMS or other presentation code (Drupal, PHP, perl, Ruby-on-Rails, etc.). If the value proposition is in speed-to-market for identity-based customization, then the white paper needs to make that case first and foremost. If that’s the goal, then it also suggests a business model, which I talk about in a bit.

It could also be that both of these are part of the approach: allowing both the website developer and third parties augment the web experience based on strong identity. This is the general idea behind r-buttons and would almost certainly speed deployment. However, the white paper doesn’t address the issues of contention when multiple providers want to augment the same page. Given the open-ended javascript functionality associated with a KIX, this could be a challenge.

Second, isn’t re-aggregation actually about creating a coherent context?

While the Kynetx approach allows users to present a particular relationship at a particular website, that doesn’t seem to solve the stated problem. I don’t see how it actually achieves a cross-web aggregated experience. In fact, it seems that the best aggregated experience should combine many relationship cards at many different services. In the 29-day travel planning scenario, won’t users need to send their AAA and AARP cards to every site they visit? (Or some large subset?) Does the card selector require a ceremony for every website every session? Or just once and then it is a permanent approval, such as confirming once with Expedia that the user is a AAA member? Managing this A x B complexity with A Information Cards and B websites scales poorly if every site has a distinct ceremony–and even worse if each card presented at each site is a distinct ceremony.

This apparent model of KIX based aggregation seems to miss an opportunity, one that is near to my heart as the core of the Search Map architecture for User-driven Search. It seems to me that for a given web-based task–such as travel planning–what you need is a user-driven personal data store that tracks the user’s progress across the Web. This data store should be 100% transparent, 100% editable, and seamlessly transferable/accessible to authorized vendors under terms controled by the user. We call our version of this a Search Map, an electronic document that provides the user a concrete way to manage and express their Search intent. It is also a seamless way to manage and express user context.

In the white paper, Phil asserts that “users are freed from managing episode context themselves” as a core benefit. But, I don’t think this is actually a benefit. Attempting to achieve that goal could end up being more patronizing than useful, following in the footsteps of “Clippy” the Microsoft Windows help agent which tried to figure out the context and help users, but failed miserably. “I see you are writing a letter. Would you like assistance?” Ack!

It’s not that users don’t want to manage their context, it’s that they haven’t been given simple, value-producing tools to do so. Consider spreadsheets: it’s not that users want to balance the budget on a computer—doing budgets on a computer isn’t inherently rewarding. It’s that spreadsheets make it easy to get value out of balancing their budget on the computer. Managing KIX across 29 days of travel planning and potentially a hundred+ websites sounds like a chore… unless we have a coherent expression of the context (in something like a Search Map, perhaps) that is easy to use and immediately useful.

Third, over-centralization limits scale.

The Kynetx model, as I understand it, doesn’t scale to the full World Wide Web, because it centralizes two core functions: resolving requests for augmentation and the validation of injection javascript as safe, private, and secure. Both of these constrain the growth opportunity for a KRL-based approach to augmenting web services. First, it places the core usage-time server demand on a single service. Given the business model of charging for ruleset evaluations, there is no obvious incentive for Kynetx to release an open source reference implementation to make it easier for alternate KRE service providers. In fact, there is every expectation that Kynetx will be motivated to “win the market share” battle and be the primary KRE service. Which, unfortunately, makes it just another silo, and will face precisely the same sort of scaling issues that plague Twitter. Second, by making Kinetx the arbiter of “quality” it places a single entity in control ofwhat constitutes “safe”. Even with good intentions, such centralized moral authority is not just dangerous, it alienates potential innovation. Nobody wants to be forced to seek permission for their new functionality. That was, IMO, the primary reason the World Wide Web dominated AOL so quickly.

The way to reach web scale is to make it absolutely trivial for /anyone/ to play the game. Several open source implementations and open standards enabled anyone who wanted to, to set up their own web server and try out the World Wide Web as a service provider. And, despite that lack of central control, lots of companies made lots of money providing enhanced software to manage those systems. So don’t fall for the illusion that central control is required or desirable for a big financial win.

Signing software is understood technology; we can enable signed KIX functionality with a validated identity as a first step towards quality control. Then, by opening up the validation service–and separating it from the distribution/matching of those KIX functions, we can allow software developers and service providers the freedom to innovate and provide their own approaches to what is valid and what isn’t. Some providers will choose to accept ANY signed KIX and simply track reputation. Others will charge a fee for developers, but run through a quality control check and review. By opening it up, you allow users and developers the freedom to manage KIX quality however they like, without building a presumptive “download at your own risk” ecosystem.

With Kynetx the sole authority on “quality” for KIX functionality, we would have both a technical and a political bottleneck that would retard the adoption of a generalized approach to the disaggregated web experience.

[Btw, it would be great if there were a name for the javascript injected into the browser when a KRL rule fires after evaluating the context and the user identity. This is currently just the "associated KIX functionality", which is a bit wordy.]

Fourth, what about privacy and data rights management?

On the whole, it isn’t clear to me what data might be sent around in the claims of various Information Cards, but there is no discussion in the white paper about the data rights associated with that information. If I’m telling Hertz that I’m an AARP member, can they use that data to start sending me junk mail or SPAM targeting AARP members? Frankly, this is a hole in the entire user-centric Identity framework. OpenID Attribute Exchange and Information Cards allow users to use a third party service for the management and presentment of minimally sophisticated facets of identity (much better than username & password), but neither inherently enables users to specify a data rights regime for the claims or attributes so provisioned. In effect, we’ve made it easy for users to provide additional data about themselves, but missed the opportunity for users to easily control the use of that data.

Since Kynetx has a goal of seamlessly augmenting users’ web experience, isn’t it incumbant on them to assure that seamlessness both protects users’ right to privacy and prevents unintended over-customization based on supposedly private data? This is another manifestation of the “Tivo thinks I’m gay” problem, where Tivo analyzes viewing behavior and assumes things about the user, with no way for the user to manage their profile. The data rights problem happens because there is nothing to keep Tivo from telling Hertz, GE, or NBC they think the user is gay. The problem in the Kynetx approach happens when service providers start passing presumably private data to third parties—and users lack the means to control that leakage once the service provider knows certain data. This level of data rights control needs to be built in from the start for VRM and user-driven applications.

Business Model

At the core, I think the business model needs rethinking. Although a CPM-based pricing for KRL evaluations seems to align the value proposition directly with costs, it actually presents more risk and less control to potential customers than other models. It also presents greater risk and less stability for Kynetx itself.

What service providers and developers want to see in a technology platform is one with a free entry point (so you can get testing and trying it ASAP, even if a production system would need a for-fee license), a constrained, predictable cost structure, and economies of scale. Charging per evaluation offers none of these.

This model instead creates an artificial scarcity and then charges by the drop. What you want is to create abundance and sell buckets and hoses and pumps. Doc calls this the “because of” effect. Constraining KRL evaluation to support a pay-by-drink business model will artificially constrain adoption. Instead, run to ubiquity and sell the best tools for leveraging the system you’ve helped create.

At the same time, the evaluation of rulesets will have highly variable demand, with great spikes and drops far outside of Kynetx’s control. Tying revenue to that demand volatility means an unpredictable, wild revenue profile, flattening out only with insanely large numbers of users. This works for mega services like Amazon Web Services, but for a start up moving from initial revenue to predictable cash flow, it can be unsettling. In contrast, an IDE sales model or subscription based service with monthly fees bounds developer expenses and stabilizes the revenue curve.

I like the idea of KRL rulesets. Currently, SwitchBook is planning on using Javascript, RegEx, and XPath, for similar evaluations. That approach not only feels ad-hoc, it is. I’d like to see a unified approach that is flexible, cross-platform, and supported by a good development and test environment.

I think Kynetx could go far by creating an open source platform for KRL rulesets, then providing a robust IDE and testing framework for those who want to manage KRL rules to meet business needs. I think this is nicely pointed to in the mention in the White Paper of A/B testing with different KRLs. This is precisely the kind of sophistication that businesses will need to make the most of KRLs and which can easily be separated from the core infrastructure that enables KRLs in an open way for everybody. Also, the consulting opportunities to analyze, customize, and manage KRL rulesets is a huge business opportunity. Doing that well is likely to remain a black art for a long time to come; helping Fortune 1000 companies do it well should be lucrative.

As Dale Olds put it referring to Novel’s Bandit Project: First, enable an open identity-metasystem, then sell tools to companies to help them manage it.

Collaborations

I like the value proposition of platform-independent identity-based customization. It fits well with VRM’s r-buttons, MyDex’s Personal Data Store service, and SwitchBook’s Search Maps. I think there’s still some brain work to be done figuring out how we can all support each other and simultaneously build sustainable business models, but I’ve no doubt there’s a way if we all invest in exploring those opportunities. Although I focused on questions and concerns about Kynetx in this post, I have great respect for Phil and hope to work with him as both our companies–and the entire VRM community–build out viable solutions to these kinds of problems.