Chief Marketing Technologist by Scott Brinker

Business models for linked data and web 3.0

2010-03-06T13:48:53-05:00

In January, I wrote a post on 7 business models for linked data (with an 8th model added shortly thereafter). Although far from comprehensive, it attempted to illustrate the range of direct revenue vs. indirect revenue models that could justify development of linked data initiatives.

A number of people from the linked data community contributed feedback and suggestions of additional models, including Leigh Dodds (Thoughts on Linked Data Business Models), Paul Groth (Another 5 Linked Data Business Models), Eric Hellman (8 One-Way Business Models for Linked Data), and John S. Erickson (The Evolution of Linked Data Business Models).

However, some of the best feedback came offline from Rachel Lovinger at Razorfish (and author of the blog Meaningful Data). Over a series of discussions, we developed an expanded model:

There are three dimensions in this model, which we phrased as questions:

1. How direct is our revenue? This is the Y axis of the chart. At the top are ways of directly being paid for data, such as licensing and subscriptions. Toward the bottom are more indirect revenue sources, such as using data to drive traffic to a web site or build one's brand and reputation.

2. Who do we provide our service to? Along the X axis are three categories that identify, from left to right, the openness and accessibility of the service.

On the far left are private partner relationships, where data is provided in closed relationships with partners who use it internally or incorporate it into other offerings downstream. In the middle, data is provided via APIs to a more open developer community, who in turn leverage the data in more public facing applications. And on the far right are web sites that regular users visit or subscribe to, without requiring any technical expertise on their part.

3. Who do we get revenue from? For any given model, the direct user of the service and the source of revenue are not necessarily the same. For instance, with a subscription model the users and the revenue source are the same; with an advertising model, they're usually two different constituencies.

We used colors to distinguish four classes of revenue sources: blue from direct customers, purple from partner relationships, green from advertisers, and red from "subsidized" sources such as government or non-profit mandates.

In this landscape, we identified 15 business models that offer a good representation of the different ways in which organizations can monetize — directly or indirectly — data publishing initiatives:

Subsidized/public service: funded by a government, an NGO, or a regulatory mandate — revenue = funding.
Licensing: charge fees to let developers use data in other environments.
Microtransactions: on-demand payments for individual queries or data sets.
Subscriptions: charge for access to data for a period of time (may have tiers for different levels of access).
Freemium: free but limited access to data to sample, but charge for extended premium access.
Paid inclusion: charge to be included in the data set or attributed valuable meta-data (what I formerly called an "authority" business model).
Sponsorships: charge a small number of advertisers for brand visibility of sponsoring the data.
Advertising: charge for ads placed around data on web pages (may also tap into ad networks).
Marketplace: provide data to a partner service in exchange for an opportunistic royalty.
Affiliate program: provide data streams to affiliates who distribute them in other applications in exchange for commissions on related sales.
Affiliate participation: as an affiliate of other companies, combine affiliate product links with data to earn commissions on related sales.
Value-add/loss leader: incorporate free or bonus data as an enhanced feature to win customers for another product or service.
Traffic generation/SEO: publish data to earn favorable positions in search engines and other directories to generate more traffic.
Branding: provide data free of charge on a friendly web site to build brand (i.e., self-sponsorship).
Data branding: provide data free of charge to build brand, but it's the data itself — not the visible manifestation of it — that is the vehicle for meme distribution.

To be certain, this isn't an exhaustive list. I'm sure there are plenty of innovative business models that are more unique, and that many real organizations will adopt hybrid approaches. However, we do hope this helps people better visualize the landscape of data delivery business models, and that it helps move the discussion forward.

Let us know what you think!

If you're interested in this topic, I also suggest that you visit the Business Of Linked Data (BOLD) Google group organized by Kingsley Idehen, read the book The Power of Pull by David Siegel, and consider attending this year's Semantic Technology Conference in San Francisco in late June.

Creative technology != marketing technology

2010-02-16T22:41:34-05:00

Just read an article posted on Adweek yesterday, The New Tech Heads, profiling four "digital technologists" — that label seems a tad redundant, doesn't it? — from top agencies:

Scott Prindle, executive creative technology director, Crispin Porter + Bogusky
Chris Kief, creative technology director, TBWA\Chiat\Day
Richard Schatzberger, director of creative technology, Bartle Bogle Hegarty
Gareth Kay, director of digital strategy, Goodby, Silverstein & Partners

I'm thrilled to see this coverage. The integration of technology into the marketing world has been largely ad hoc to date, usually without consistent executive leadership. Establishing senior management roles for creative technologists is an important step in reconfiguring the DNA of new marketing organizations.

Congratulations to Scott, Chris, Richard, and Gareth on leading the charge. (By the way, Gareth has a great blog, brand new, that's worth checking out.)

However, reflecting on this article — and exploring the web sites of these agencies looking to learn more — it struck me that the mission of a creative technologist may be quite different than a marketing technologist.

The role of the creative technologist — as the title implies — seems to be primarily about (a) using leading edge technology to execute creative campaigns and (b) finding inspiration for new creative campaigns from the leading edge of technology. The focus is on creative campaigns either way, which is an evolution — but not a revolution — of what agencies have provided for decades.

Now, I believe there is a genuine need for such creative productions — and always will be — and therefore there's a place for such creative technologists who can lead and enable them.

But I wonder if the emphasis on creative technology has caused a number of these agencies to overlook the larger vision of marketing technology.

Marketing technology isn't just about creative productions. It's about changing the very operational architecture by which marketers run their organizations and build relationships with customers, prospects, partners, vendors, collaborators.

Creative technology projects are a subset of this new marketing technology universe. But there's a need for a broader management vision that synthesizes such creative technology with overall social media marketing, search marketing, web site and post-click marketing, email marketing, marketing automation, cross-channel management, marketing analytics, marketing resource management, and so on.

Granted, these broader marketing technology responsibilities probably fall under the domain of the CMO of a company more than an agency. But agencies should be deft and nimble at interfacing to their clients at that level, if for no other reason than to make sure that the benefits of their brilliant creative technology productions are fully captured.

I can't help thinking that agencies have an opportunity to lead this integrative vision — and that it is a revolutionary shift in marketing. But to accomplish that, they need to integrate such marketing technology into their own operations first.

Not to pick on anyone, but...

When writing this post, I did a Google search for each of the people featured in the Adweek article. As an example, I did a search for "gareth kay goodby silverstein" — figuring I might learn more about him on a profile page on their site — only to be shocked to discover no links to Goodby, Silverstein & Partners in the first three pages of results from Google. I gave up before going to page four.

Puzzled by that, I went to the Goodby Silverstein web site, which launches a visually stunning Flash experience. There was a Staff menu option, so I clicked it and came to a beautiful mosaic of about 100 faces that you could roll over each one to see their name and title. I hunted around for Gareth, but never did find him. I can kind of link you to the page, but it's actually deep in a Flash — so you have to get routed through their official opening.

From a purely aesthetic perspective, it's a gorgeous site.

But from a functional marketing perspective, the closing off of Google as a channel — and really all link-oriented social media venues — seems like a dubious marketing technology decision.

Maybe some would argue that such sacrifices are sometimes necessary in the interest of developing the most creative production. It doesn't have to index in Google, it just has to be gorgeous. Maybe that's true.

But I'm not convinced that we're anywhere near the Pareto frontier of having to trade off creativity and functionality. I think we can have both — although it will require creative and functional forces to collaborate even more tightly, beyond the scope of any one creative project.

Web 3.0 interview on data marketing

2010-02-02T17:56:45-05:00

While I was at the Web 3.0 Conference last week, giving a talk on data marketing, I did a quick video interview on the subject with Scott Koegler of SemanticWeb.com.

Watch Web3.0 Conference Interview Scott Brinker - Ion Interactive in Tech & Gaming | View More Free Videos Online at Veoh.com

Ratings in Google search ads address trust

2010-01-31T08:42:35-05:00

I woke up this morning to read an incredibly exciting story on Search Engine Land, Yelp Ratings Appear In Google AdWords.

This may be one of the most game changing experiments in the history of advertising.

Here's why.

Last year, I did a research project on people's attitudes towards sponsored search advertising, which led to a blog post that study reveals issues with search ads — trust and usefulness. (I have since also read similar research done by Bernard Jansen, Anna Brown, and Marc Resnick in an academic paper, "Factors relating to the decision to click on a sponsored link.")

The net conclusion: people don't find advertising — even search advertising — to be particularly useful or trustworthy.

While this may not come as a surprise to some, I found it a tad surprising that such a negative bias existed even in sponsored search on Google, where ads are relatively subtle, clearly identified, and generally quite relevant to a user's search task.

That's an incredibly dangerous attitude to have growing in the wild, as — if unchecked — it threatens the entire ecosystem of advertising and massive ad-supported services such as Google.

Exploring ways to address this problem, I put together an experiment that (via a Firefox extension) overlaid Google ads with links for reviews and search results for each advertiser. It wasn't anywhere near as elegant as the example above with Yelp, but the preliminary results were very encouraging:

The presence of reviews about advertisers — trustworthy, independent, third-party reviews — directly tied to their ads, had a remarkable impact. The two human subjects with whom I did a "think aloud" study became deeply engaged in the ads and their reviews, using that additional information to improve their search experience and identify preferred vendors.

If you're interested in that study, I've included the Scribd report — a draft only! — at the bottom of this post.

The way Google incorporated this in the Yelp example above is beautiful. It communicates useful knowledge (the average rating and the number of reviews) from a known authority (Yelp) with a link to get more details of those reviews (presumedly why Yelp has a blue link).

That's a lot of information and a strong trust signal embedded in what is a relatively subtle visual representation. The brilliant Zen simplicity of Google ads remains intact, simply enhanced.

In my experiment, I automatically included overlays for reviews and other search results for all advertisers — there was no way to avoid your reputation. But in this trial with Google, it's conceivable that the Yelp review is something that the advertiser agreed to have included.

Such an opt-in mechanism can work though: reputable advertisers will choose to include reviews — it only helps them — while advertisers with poor performance would not. But the absence of reviews on an ad, particularly when its competitors have them, would be a sufficiently strong indicator itself.

Yelp won't be the only source of authoritative reviews, of course. I suspect that Google will offer similar hooks to Trip Advisor for travel-related reviews or CNET for high-tech product reviews. The advertiser may have a choice of selecting from approved independent, third-party review sites that are most relevant to their domain.

This is Consumer Reports for the 21st century, in a highly distributed and collective intelligence implementation.

The beauty of this virtuous cycle is this: advertisers are incentivized to do everything they can to win excellent reviews from their customers. The better your product or service, the better your reviews, the more you'd be inclined to advertise that fact. And — hopefully — the more inclined people will be to pay attention to such "ads" because they're not marketing spin but objective, useful information relevant to their search.

Advertising becomes less about the cleverness of your ad, and more about the earned reputation of your company.

Think about the implications of that.

This takes disruptive innovation in advertising to a whole new level — ads are not about their creative, but simply paid placement of their earned reputation.

And for end-users, who have been concerned about trust and usefulness, isn't this really what they want to know?

The Useful Ads Project

Data marketing for Web 3.0

2010-01-26T18:58:36-05:00

I just finished up my presentation on data marketing at the Web 3.0 Conference, and I thought I'd share it here as well.

Web 3.0 Data Marketing

View more presentations from sjbrinker.

I'll recap what I said to accompany the above slides, a kind of running commentary like they have on DVD's. I'll put slide numbers in brackets, like [4] for slide #4, so you can follow along.

Marketing with Linked Data

I want to talk to you about [1] the emerging field of data marketing.

Web 3.0 means different things to different people [2]. Without launching into a big nomenclature debate — there's something ironic in arguing the semantics of the semantic web — I'd humbly propose the following categories based on different waves of linking. After all, linking is what the web is all about:

Web 1.0 was about linking pages. The giants that emerged out of that wave included Google and Yahoo!, who took advantage of those linked pages to help us find great content.
Web 2.0 was about linking people. Social networking exploded, from sharing photos on flickr and videos on YouTube, to connecting with our friends and colleagues on Facebook, LinkedIn, and Twitter.
Web 3.0 will be about linking data. Who will be the leaders of this wave? Maybe you...

By "data," I mean the technologies of the semantic web and the linked data movement.

By "marketing" [3], I mean the broadest definition of the field. Marketing includes the 4 P's: product, pricing, placement, and promotion.

Product includes the design of your offerings and your strategy for differentiation.
Pricing covers not just "the price," but how your pricing evolves over time and how it changes for different segments and bundles.
Placement is the channels by which you deliver your product to market: distribution, retail, e-commerce, partnering.
Promotion includes advertising, branding, PR, sales promotions — online this means web sites, email, search, and social media marketing.

Linked data will impact all of these [4].

Web 1.0 brought us web marketing and search engine marketing. Web 2.0 brought us social media marketing. Web 3.0 will enable a whole new marketing paradigm, data marketing.

Data for customers

I'll touch on 4 data marketing topics in this presentation [5]. Let's begin with the big picture, thinking of data for customers.

Data helps us make decisions [6].

Data helps us impress our boss [7].

Data helps us persuade people [8].

Data is the fuel of the 21st century [9].

Yet despite its ubiquity in our lives — particularly our professional lives — finding the data we want in any given circumstance is hard work [10].

And then once we find it, we tend to stow it away in silos [11]. Spreadsheets. Documents. Databases. We end up with data that is dispersed, duplicated, out-of-date, and difficult to relate from one application to the next. To paraphrase the children's rhyme: data, data, everywhere, but not a drop to drink.

But a new generation of Web 3.0 companies is working to make data "open" [12] — linkable and shareable. Freebase, Infochimps, Factual, Calais, Flowing Data, Wolfram Alpha. These companies are making it easier for us to find and use the data we want.

But they won't have a monopoly on linked data [13]. The beauty of semantic web standards, such as RDF and OWL, are that they will enable any web site to publish structured data and link it to other sets of related data, anywhere on the web. Just like we all did with HTML. Linked data is the great wave of Web 3.0.

Now, marketers love data [14]. We may not be database architects — at least not yet — but we appreciate information: market research, web analytics, CRM records, social media monitoring. We know the value of good data.

As Sting said [15], "If you love something, set it free." (This may be the first — and last — time someone cites Sting for explaining the semantic web.)

Set data free.

The essence of Web 3.0 for marketers is to think about data for customers, not just data about customers [16]. Shift from data stalking to data talking. What data could you share with your prospects, customers, and partners to strengthen your relationships, build your brand, and win more business?

Data + search = SEO++

One of the first places data can help is with search marketing [17].

The web's a big place [18]. Carl Sagan would say, "billions and billions" of pages. Just doing a search for a specific restaurant by name in a specific city can return 80,000 hits. It can be hard for us — or our customers — to find answers.

Yahoo! was one of the first major search engines to start leveraging structured data from web sites in their search results with SearchMonkey [19]. When you do a search for a restaurant — such as "slanted door san francisco" — you might see a particularly useful summary from Yelp, right in the results. Aggregate rating, number of reviews, address, phone number, a photo of the interior.

That's a heck of a lot more useful than a random line or two of text.

Google does something similar with their Rich Snippets feature [20]. As does Bing [21].

As a marketer, the benefit of adding search engine friendly structured data to your web site is simple: more traffic [22]. Yahoo! reported that search results that embedded these useful snippets of structured data received 15% more click-throughs than the competition.

Although the search engines claim adding structured data to your web site won't directly improve your ranking [23], to prevent spammers from gaming the system with bogus data, there is a virtuous cycle here. A better listing gets you more clicks, more visitors — some percentage of whom will link back to your site, thereby improving your ranking, which in turn wins you even more clicks.

To clarify, the data bubbling up in these search results was published by Yelp [24]. Yelp is a classic example of a company that has a value proposition rooted in data. They offer extensive data about restaurants — featuring the collective intelligence of over 9 million user reviews — that makes them a data authority in the subject.

The value of that authoritative brand position was estimated at over $500 million in recent M&A rumors.

Adding structured data to your web site is pretty straightforward, using microformats and RDFa [25]. If you're not technical, just think of this as extended HTML.

Embedding this kind of data in your web site is a natural extension of search engine optimization (SEO) [26]. Whoever is doing your SEO now should be able to help with this. But since structured data takes SEO a little further, I call this SEO++ — a mix of SEO and data objects. It's reminiscent of the paradigm shift to object-oriented programming, from C to C++.

As semantic search technology advances, this will be a big deal.

You can certainly take this kind of structured data further than restaurant reviews. Last year, Best Buy launched a large-scale semantic web site with their products [27].

They used a more advanced vocabulary called GoodRelations [28] to more fully describe their products. GoodRelations can describe components of products, accessories, delivery options, payment options, warranties — just about anything you could want for defining e-commerce offerings in a structured format.

The payoff, according to Best Buy, was a 30% increase in site traffic from organic search [29].

This is why search is a great place to dip your toe with data marketing. It provides a clear business incentive — more traffic to your web site — and there's an existing budget to invest in it [30]. This year over $2 billion will be spent on SEO; within 4 years, that will be more than $5 billion.

Data branding

Now let's look beyond search and think more broadly about data marketing and what it can mean for your brand [31].

Josh Jones-Dilworth, who handles PR for many of the leading companies in the semantic web and linked data space, wrote an excellent article on Mashable, Marketing in 2010: It's All About the Data. He starts with this brilliant insight [32]:

Data shapes conversations and markets.

That is the essence of data branding — positioning your company through the data you create and publish — and, in a linked data world, how you relate that data to others.

In data branding, you want to ask yourself three questions:

1. What data, if widely disseminated, would grow my market? [33]

For example, consider Google Insights for Search [34]. Google's "database of intent" is arguably their most valuable asset. But rather than lock it in a vault, they let anyone mine this data for trends. With their Keyword Tool you can even drill down into specific number of impressions for all related keywords. This is smart, as it helps get marketers more engaged in search. Ultimately, this data encourages more — and more successful — search advertising.

2. What data would position you as a leading authority in your field? [35]

The New York Times is struggling, like all newspapers, to find their place in the digital world. But Evan Sandhaus, the paper's resident Semantic Technologist, is forging an exciting strategy [36]: to have the "paper of record" become the authoritative data source of record — at least for the paper's areas of expertise with news, public figures, politics. They have over 150 years of original content to draw upon. Check out data.nytimes.com and developer.nytimes.com to glimpse this future.

But they'll have competition. Thomson Reuters also has claim to being a data authority, particularly with companies, law, markets, and finance [37]. And they've got a strong competitive advantage with their Open Calais technology to help web developers leverage that data quickly and easily.

CNET is a data authority with product reviews. Yelp is a data authority with restaurant reviews. Google is a data authority with search behaviors. What will your company be a data authority for?

3. What data vocabularies (ontologies) will define your market? [38]

To unlock the real power of linked data, you must do more than publish structured data [39]. You need to use vocabularies — or, more technically, ontologies — that other people will recognize and use to publish or relate their data too. The interlinked web of data is the real vision.

For example, there's a well-established vocabulary for social network data — friend of a friend (FOAF) — and a very popular vocabulary for publishing called the Dublin Core. GoodRelations, which we saw earlier, is another.

But for most areas of expertise and most domains of knowledge — probably many in your specific market — there aren't well-defined vocabularies. Yet. You have an opportunity to be the first mover, to shape the nomenclature and structure of information in your space.

Reflect for a moment on the brand potential here, defining the structure of shared data as a way of shaping the use of that data in your market — in ways that are particularly synergistic and relevant to your position.

Engaging in such data branding initiatives will involve a new ecosystem of players [40] — developers and popular data applications. Search engines are one example of a data application, but there will be hundreds, thousands as the semantic web blossoms.

Smart marketers concerned with data branding will cultivate these relationships — and start soon.

Data business models

Finally, I'd like to mention a bit about business models for data [41].

Implementing linked data doesn't happen automagically. Companies need to think about how they can get return on such investments [42]. We briefly discussed this with SEO++, but there's a wide range of possibilities.

A few weeks ago, I wrote a post on 7 business models for linked data, along with a follow-up piece on the 8th linked data business model. These triggered vibrant conversations in the semantic web community around this topic, with a number of people suggesting many additional models.

Once you realize that data has tremendous value -- and that the interoperability of linked data will only increase its usefulness and accessibility -- you can start thinking creatively of many ways to capture that value.

That's going to be one of the great adventures in marketing for this next decade.

Thank you, good luck, and let me know what you think [43].

Linked data lab at MIT was excellent

2010-01-24T20:20:23-05:00

Earlier this month, MIT ran a special Linked Data Product Development Lab during their Independent Activities Period (IAP).

The lab brought together an eclectic mix of students and alumni, engineers and entrepreneurs, for a week of lectures, hands-on workshops, and collaborative team projects — all focused on the present-day capabilities of linked data. Sir Tim Berners-Lee kicked off the event with an inspiring talk about the vision of linked data.

I had the pleasure of presenting on the "business value of linked data" panel on the second morning, along with K. Krasnow Waterman (one of the organizers behind the event) and Evan Sandhaus of The New York Times.

By the way, if you haven't yet checked out data.nytimes.com, I'd highly encourage you to do so. Evan gave an inspiring talk about what they're up to, and it's well worth examining it from the perspective of any publisher. And in this day and age of search and social media marketing, just about every company is a publisher to some degree or another.

My topic on the panel, as frequent readers here might expect, was marketing with linked data. Here's the brief slide deck I put together for it:

Marketing with Linked Data (MIT)

View more presentations from sjbrinker.

It was an excellent event. My thanks to the organizers for inviting me to participate. (It also afforded me the opportunity to meet Kingsley Idehen, one of the leading advocates for the business opportunities enabled by the semantic web — and a frequenter commenter on this blog.)

I'll also be speaking on this topic later this week at the Web 3.0 Conference in Santa Clara on the Web of Data: Semantic Web in Marketing panel with Krista Thomas and moderator Carla Thompson.

On Her Majesty's linked data service

2010-01-21T21:42:29-05:00

Earlier today, Sir Tim Berners-Lee and Nigel Shadbolt posted a great article on The Guardian's Data Blog, Our manifesto for government data.

They announced the public availability of the U.K.'s beta data.gov.uk site, a cornucopia of over 2,500 data sets of government data — everything from agriculture statistics to workplace employment by industry — open to anyone to use. It's a great example of the 8th business model for data.

And most of it adheres to proper linked data standards.

Marketers should pay attention to this initiative. When you read the introduction to their article, it's not hard to imagine this being about business instead of government, customers instead of constituents:

Data underpins our economy and our society — data about how much is being spent and where, data about how schools, hospitals and police are performing, data about where things are and data about the weather.

Yet until recently, not many non-technical people concerned themselves with data and how it could be used better.

That's changing, and changing quickly. There are growing expectations of greater accountability and transparency of public bodies. New technologies allow data to be managed and re-used quickly and cost-effectively. A greater number of people have the innovation and the skills to use data. And organizations from government to the private sector, from voluntary groups to the media are hungry for data.

Everyone is hungry for data. And as the linked data movement advances, making data as easily shareable and interlinkable as web pages are today, businesses are going to have a tremendous opportunity to use data as a marketing channel.

Initiatives such as data.uk.gov — and its U.S. sister site across the pond, www.data.gov — will help to build critical mass for such interlinked data and demonstrate how useful it can be.

Want to be inspired? Take a look at some of the innovative applications that are leveraging such open data in the U.K., such as Planning Alerts that notifies you when construction projects are being planned in your neighborhood. Useful, eh? (Would have altered the opening plot line in The Hitchhiker's Guide to the Galaxy, that's for sure.)

What are the potential data-driven applications that your customers, partners, employees, and fans could build to promote your company's mission and add value to your ecosystem?

Appoint a marketing technology czar

2010-01-20T13:46:31-05:00

Avi Dan has a great article that was published yesterday in Advertising Age, Why Brands Should Embrace Technological Change.

It's an excellent piece talking about the rapid shifts in marketing technology and encouraging CMOs to embrace the phenomenon with all their heart (and all their organizational structure).

I was pleased to see him advocate for a chief marketing technologist role that would report to the CMO:

CMOs must lead a number of internal changes as well. The first is to recognize that technology is no less a marketing tool than, say, market research, and appoint a "marketing-technology czar" to champion it. That person's responsibility will be to act as a cross-functional facilitator and identify technology that can enhance marketing activity and brand building."

I prefer the chief marketing technologist title, but "czar" has a nice ring to it too.

I love Avi's closing remarks: "To navigate through the added complexity of the technological eruption, they have to go beyond just tolerating it to become active participants and advocates of the new marketing ecosystem."

"They ought to embrace the speed of change and view it as a brand asset."

(My enthusiastic emphasis added.)

The 8th linked data business model

2010-01-17T08:25:19-05:00

In response to my post on linked data business models, Leigh Dodds at Talis wrote a terrific piece with his thoughts on the business of linked data. Leigh presents a number of great ideas that I think really carry the conversation forward.

One of his points is that I overlooked an important model, what he calls the "sponsorship model." Under this model, a government entity or a non-profit organization has a funded mandate to deliver certain data to the public or their targeted constituency. I'd humbly suggest calling it the subsidized model though, to avoid confusion, because sponsorship is often associated with advertising and branding — very different business models.

Here's an updated diagram reflecting this additional model:

I put the subsidized model at the top for two reasons. First, it could be argued that it is the most direct revenue source — you're paid to produce the data before you even put it online. Second, I wanted to put a lot of distance between it and the branded model to emphasize the subtle yet significant distinction between them.

Now, you could debate that this isn't really a business model per se because it's clearly non-commercial. However, in the broader sense of the term, it does represent a major "revenue" source that can employ people to produce and maintain such data.

It also happens to be the model behind many of the largest linked data repositories on the web today, such as those from the BBC or the US Census. To ignore it would be to leave unexplained the organizational motivation behind a huge portion of the linked data graph.

I can also see how the subsidized model might apply to commercial organizations, who either have a regulatory requirement for delivering certain information — i.e., a cost of doing business — or a philanthropic arm that engages in good deeds for reasons other than corporate posturing.

But I want to emphasize the subsidized model is not the same as the branded model.

The subsidized model makes the investment in linked data because the delivery of that data is a core part of its organizational mission. It doesn't need to generate any subsequent financial return from the publication of that data.

The branded model, however, has an ulterior motive for producing linked data: shaping impressions in the minds of the audience who consumes that data — with the intention that such influencing of opinion will lead to future sales and business relationships. It's the most indirect business model, but indirect shouldn't be interpreted as inefficacious. The right branding can have tremendous value.

When The New York Times invests in their Linked Open Data initiative, it isn't altruism. It's a part of their strategy to retain their brand as the leading authority of news and editorial in the world. It's a tremendous benefit to the public. But it's also a powerful move for their business.

I personally think that data branding will become one of the most significant forces behind the widespread adoption of linked data.

7 business models for linked data

2010-01-08T22:44:40-05:00

Now that major companies are implementing linked data, and more marketing thought leaders are championing data as an outward-facing competitive advantage, the question I'm hearing more frequently is:

How do you turn data into revenue?

Creating, publishing, and maintaining data takes work. What are the economic incentives for companies to put in the effort?

Here's my take on 7 business models for data web initiatives:

I've organized these by how revenue is generated, from direct money-for-data to indirect branding programs.

Within each of these revenue models, there's also a secondary dimension of how the data is delivered, whether in raw form for others to leverage in their own applications or embedded into a pre-packaged application provided directly to end-users.

1. Subscription model. Some data will be valuable enough that you can charge people a subscription to access it. This model has been around for a while, but it will gain new life as linked data standards make it easier for people to consume and mash-up data in novel applications.

2. Advertising model. Advertising: the second oldest profession. Data-driven applications will have plenty of opportunity for contextual ads and sponsorships. One interesting twist will be advertisers who pay to include information in raw data feeds, data-layer ads if you will.

3. Authority model. If anyone can publish data on the web, how will you know what data is good? That problem will be an opportunity for third-party "authorities" to validate data — or do official reviews and certifications that are published as data — and charge for participation. Compliance services are related to this.

4. Affiliate model. Affiliate marketing programs generate over $6 billion/year in commissions and are a major source of transactions and leads for merchants such as Amazon.com. Embedding affiliate links in data, so that they are activated when surfaced into end-user applications, are a natural extension of this existing model.

5. Value-Add model. Useful data can be bundled with other services to make the overall solution more valuable. For example, think of the benchmarking data now included with Google Analytics. Access to data can also be offered earlier in the sales funnel, as a lead generation incentive.

6. Traffic model. As with Google Rich Snippets, data can be used to boost the visibility and ranking of sites in major and vertical search engines. This is data-enhanced search engine optimization (SEO++) to increase traffic. Nickname: the "data for nothing and links for free" model (apologies to Mark Knopfler).

7. Branding model. As Josh Jones-Dilworth said, "Data shapes conversations and markets." Data branding can use data — and the vocabularies that define and structure data — to position and promote a company's worldview and differentiation strategy.

Of course, there will be hybrid models that combine several of these approaches.

Particularly in the early days, most organizations will benefit from experimenting with linked data for traffic, branding, and a little value add. Their own value will be learning as much as anything. As the data web matures, and they become more experienced, they may embrace more direct revenue models.

But don't underestimate the importance of data branding. When it comes to establishing industry standard vocabularies and ontologies, there is a definite first-mover advantage.

For the entrepreneurs in this space, however, everything is fair game.

Can you think of other models? Are you willing to share?