Photo Agencies and The Stock Industry: a Matter of Proportion

In my blog post, "There are Lies, Damn Lies, and Statistics", a series of email replies inspired me to post a follow-up. I'll get to them at the end, but first, a recap:

In that article, I mentioned how a Shutterstock survey focused on a small, select group of traditional image buyers to gauge their purchase expectations over the next year. I went on to say that it is the result of surveys like this (and others) that most stock photo analysts draw the wrong conclusions about the nature of the broader stock photo marketplace, which itself leads to a trickle-down effect of misinformation throughout the industry. In this case, the Shutterstock survey lead many to conclude that the industry is growing. And this perpetuates another misperception that agencies represent the lion's share of sales and revenue, which itself leads to the misperception that making money in stock requires joining an agency.

Each misperception leads to another, and another, and another, until finally, the industry is full of chaos and confusion, myth, and suspicion.

For now, I want to clarify that, just because it's easy to see how most analysts misinterpret information, it doesn't necessarily mean that it's easy to know how to do it right.

A primary example of this can be found in a July 18 article in the New York Times business section, titled, A Matter of Opinion?. The issue is how credit rating agencies were giving high marks to the very companies that were ultimately responsible for the credit crisis that lead to our current economic meltdown. After facts were uncovered, many feel these credit agencies should have known all along that banks and other institutions were engaged in speculative and complex financial instruments that would lead to this.

And that's how I feel about those who cover the photography industry. The evidence is so overwhelming that the predominant view of the stock photo industry is so wrong, that it is flatly irresponsible of the press and analysts to perpetuate that view. It's also important to point out that this is not the company's fault. Their survey and their data is just fine -- their goal was to illustrate other points more german to their businesses. The problem rests entirely within the press and blogosophere who are inappropriately using that survey to support (and perpetuate) incorrect conclusions about the industry at large.

First and foremost: The stock photo industry does not revolve around stock photo agencies. Though there are no scientifically viable surveys that show the total size of the market -- and therefore, the proportion that agencies may represent -- there is a great deal of asymmetric information (indirect data gathered from independent sources) to support the premise that agencies' role is minimal.

I've written many articles that cite multiple data sources that suggest that most stock imagery is licensed on a peer-to-peer basis--directly from photographers. Even though many of these individuals do tiny amounts of licensing annually for themselves, it's their collective economic activity that has far more gravitational pull on the industry than the entirety of stock photo agencies combined. (They are what my books call the "dark matter" of the photo industry: you don't see them, but they are there, and they account for over 80% of the stock photo universe.)

Once taken into account in discussing and analyzing the nature of the stock photo industry, a great many assumptions and other factors are instantly called into question. For one, the effects of pricing and other actions taken by agencies. If, even for the sake of argument, one assumes they are not the center of the universe, but rather, involuntarily pulled by everyone else, how they are presented and covered would not just change industry perceptions, but it could have a trickle-up effect, putting more pressure on industry executives to make better, more economically viable decisions that lead to industry growth.

As for the stock agencies themselves, I have no qualms about how they conduct their businesses, per se. True, I think they leave a lot of money on the table with their pricing, and I think they miss out on a great deal of consumer opportunities, but I don't think this harms the market at all--again, they do not "set trends", they are inadvertent followers of larger forces. I also understand well that running a profitable business is difficult, and growth is often fraught with risk. The graveyard of companies that tried to migrate to a consumer-oriented business is crowded.

Nor do I have an issue with how they market themselves. There was absolutely nothing wrong with the Shutterstock survey that I alluded to in my prior article. Shutterstock's business is to sell stock imagery, and their survey happened to focus on a particular market segment that they felt was their primary buyer base. That this segment of buyers (narrow, though it may have been) happened to show certain behaviors that also happens to underscore Shutterstock's future prospects shows that Shutterstock has a bright future (at least for the short term).

Also, the PR agency that helped promote the message, Morton PR, was particularly honest, insightful and articulate, not just about the survey itself, but in its own recognition that the survey was not (and did not intend to be) reflective of the industry at large. Not every survey is designed for that purpose, and Morton was uncharacteristically open about this, as compared to other PR firms that have contacted me as representatives of other stock agencies.

I also happened to point out that iStockphoto also had a banner year, and is showing signs of improvement for next year as well. This fact being anecdotally supported by a comment from Lee Torrens at microstockdiaries.com on his own bump in sales, despite the fact that he hasn't increased his submissions to any stock agencies.

So, if that data isn't representative of the entire market, what kind of conclusions can we learn about industry trends? And what data do we use to learn this information?

In the spirit of setting expectations correctly, I can address these questions by proxy: my replies to the emails I get on this subject.

First, there's the most common question: "How does a photographer succeed at selling stock if not through agencies?"

Begin by dispensing of the premise that agencies are the de facto channel for stock photo purchases. You can (and should) sell directly yourself, irrespective if whether you also sell through agencies.

As an added note: I strongly discourage anyone from signing an "exclusive" arrangement with an agency that did not reciprocate by prepaying minimum royalties. After all, this is standard boilerplate contract language for book publishing. Why allow a stock photo agency better rights than a book publisher?

Once you take out the exclusivity clause, you can and should sell your images through any and all channels you can. Including--and especially--your own website.

Selling your own stock is easier now than it ever has. Many applications allow you to build your own stock site, that even the most technically squeamish can produce. It's beyond the scope of discussion to address that; I talk about it more in length in this article, which also happens to be in my book on building a photo career.

The barrier to success in stock photography is less technology as it is psychology. Most don't think it's possible (the "agency" fallacy), or they just don't want to put the time and resources into it. There's also a misperception of time: that sales should come right away. Or that they'd come sooner with an agency. No -- It takes time for your stock images to derive revenue, regardless of where they are for sale. Yes, the revenue curves are different between a personal site and an agency site, but "different" isn't necessarily better. After one year, you may get more revenue from an agency site than yours, but over five years, you're sure to get more from your own site. This is usually because you will charge more on your site (because buyers are more willing to pay higher prices--a factor that most agencies don't really understand yet), you will keep more of the revenues (in fact, all of your own revenues), and your own site will likely get more traffic to your pictures than the agency's site will.

The assumption that the agency is going to do better for you and every other contributor is naive. There's going to be an uneven distribution of traffic to contributors on agency sites, and there's a 90% chance you're going to be on the short-end of that stick.

Which leads to next question I get: "It just doesn't seem to me to be that smart to be in a situation where you give away 80 to 90% of your profit. I want to create something where I keep 80 to 90% of the profit."

Stock agencies get 90% of the profit because they're doing 90% of the work. If all you do is take pictures and upload them, then all you deserve is 10% (IMHO). The value of stock photography is not the photo. It's getting it sold. If you go to the effort of creating your own website, generating traffic, building a buyer base, then you too can earn 90% of the profit (the 10% you don't get goes into your cost of setting it all up). I talk about that in my two articles on stock agencies, here and here.

This next email question represents another misimpression about stock sales: "...discussions among a number of us who primarily do landscape, scenic, wildlife photography [...] lead us to think that there is no significant stock market for this type of work. What are your thoughts?"

Most stock photo sales are done in vast, wide, disparate and unstructured transactions around the world. There actually is a very big market for landscapes and scenics and wildlife photos, but there are also billions of such images from millions of photographers too. Even bad photos sell. The problem isn't that there isn't a market--it's getting noticed among the crowd. This leads to two points, one of which I've already made: getting noticed and ranked is a function of building your own personal site and personal presence on the internet.

The second point is that stock photography should not be regarded as a vehicle for generating lots of money with little work.

Stock photography touches many people as either a buyer or seller of a photo. So much so that it is so thinly distributed among people around the world, it's fool-hearty for an individual to approach it with high expectations.

So, what does all this say about selling stock photography as a form of personal income?

For so long as the industry remains chaotic and unmanaged by any central body, stock photography will also be unstructured. There will be little innovation that helps sort, rank and distribute photos based on merit--it'll remain as it is now: arbitrary. And just as you should not rely on buying lottery tickets to sustain an income, neither should you rely on on stock imagery when it is so highly subject to sales channels that are diffuse and arbitrary.

In this day and age, stock falls into Truism #4 of my list of The Five Truism about having a Photography Business, which I originally wrote in 1998. Truism #4 says Diversify Your Business. Only a very few who truly know and perfect the stock photo marketplace should do nothing but stock. For everyone else, you don't "succeed" at stock so much as you use your existing imagery from other sources to augment your income.

Most who sell stock -- even well -- do it as fun way to earn a bit more from their hobby or as a lifestyle business. That's how it was for me for well over ten years of my photo career. And as I am more into consulting now, it's that way for me again.

In closing, I will summarize by quoting my last blog:

Turning a blind eye to the rest of the stock photo universe affects decisions about where to put marketing dollars, where to do research into buyer behaviors, pricing, and business development. If it were generally accepted that the market were larger, agencies could form partnerships with other media licensing agents, social groups and legal networks that reach that larger market.

The Economics of Migrating from Web 2.0 to Web 3.0

Synopsis

The Web 2.0 financial model: user-generated content attracts visitors, which boosts search rank, which attracts more visitors, which boosts advertising revenue. The traffic-to-dollars business model resulted in unintended social phenomenons: social-networks and blogs, which themselves spurred new web design goals that focus on encouraging visitor participation and contribution. The un-monetized "waste byproduct" from these websites is a stockpile of user-generated content, such as photos, videos, paintings, drawings, stories, commentary, and opinions. To make use of all that flotsam, a suite of semantic analysis tools is being developed to organize and structure them in ways that help search engines produce better results. This is called Web 3.0--or, "the semantic web." The consequence of Web 3.0 will be the unanticipated financial incentive for websites to monetize their content, rather than just host it to attract visitors. The opportunity to make money from user-generated content will give incentive to visitors to produce "better" content, and for websites to be more discerning about the content they receive, which affects both the social and economic landscape of the internet. The ways this type of transformation may evolve is the challenge for technologists and entrepreneurs, who must be both visionary in how the future may appear, but cognizant of missed opportunities of the past.

In this second installment (of three) about the consumer's role in the future of stock photography, I turn my attention to the economic effects from new developments in search technology. As I'll make clear soon, "search" is merely a spark that launches a much larger fire: the social aspects of the web. And whenever the subject of "social networks" mixes with economics, the spotlight focuses squarely on the consumer. I presented a simple example of this in part one of this series by showing that more consumers both buy and sell photos than do professional photographers or stock photo agencies, which itself has caused a dramatic shift in how licensing is done. This phenomenon is not as readily visible to the undiscerning eye, because the greatest proportion of these transactions is done on a peer-to-peer basis (directly between the photographer and the buyer). In fact, asymmetric analysis shows that approximately 80% of photo media content is acquired directly from the photographer, and images are found primarily from search engines. This mechanism creates economic incentive for those on both sides of the transaction: the buyer uses search engines to find what they want, so the seller tunes his content to conform to the kind of information that search engines look for.

The "missed opportunity" from this shift has been primarily the lack of technical infrastructure to support broad peer-to-peer licensing. Only the traditional licensing methods are available on a broad scale, which requires photos being submitted to a company (a "stock photo agency"), who then licenses them to buyers. Each individual agency operates entirely independently from others, and none of them have prominent placement in traditional search engine results, so only a small percentage of potential buyers ever end up on those sites. The majority of them go directly to the websites of the photographers themselves (because the search engines index them), but most of these photographers are unaware that they could make money licensing their content. Indeed, even social-networking sites are unaware of the financial opportunities to license the content. The net result is that few photos are actually monetized, and of those that are, the pricing is arbitrary and spurious. It's estimated the $15-20B of licensing is done on a peer-to-peer basis, and countless more dollars are simply unrealized due to this inefficiency.

I should clarify that even though my first article demonstrated this type of media growth in the photo industry, the broader market of all types of media is evolving similarly. In fact, events in online photography serves as an excellent "base case" to help forecast economic effects for other media types, such as music, video, line-art, books, and so on. What all these have in common, and which everyone has known for years, is that non-professionals create this content as well. And, people do so without necessarily intending (or expecting) make money with it. I call this class of content creators, "consumers."

By examining the photo industry, we can extrapolate what might happen with the industries of other media types. Accordingly, photography has these important characteristics:

1. Everyone does photography on a regular basis in large quantities.
2. People upload their photos the internet more frequently and in higher volumes than other media types.
3. Economically, photos are used more than any other media type in publishing of both commercial and editorial content. (Thus, economic value.)
4. More people can create "salable content" with less expertise, less effort, and greater speed than other media types.
5. The high quantity and low price per unit of licensed images equate to a lower barrier of entry for both buyers and sellers.

Forecasting the economic future of media on the internet is difficult because it isn't clear whether the same lack of awareness will plague other media types as it has with photography. There's already been a major economic shift in the photo industry as a result of the internet, and evidence suggests that similar economic changes are happening with video and music as well. As technology for creating content of any type improves, as does self-publishing of this content, the economics are likely to follow the trend set forth by the photo industry, and consumers will find themselves in a position to make money with their content.

The next phase of internet search technologies and standardized communication protocols may inadvertently help. As we've seen with the evolution of the internet to date, whose economic growth came from unintentional consequences, we can learn from how those circumstances came about, and use them to forecast how the future economics might also take shape.

The goal and challenge for media-oriented industries of all types is to build a more structured, formal, internet-wide framework that handles content licensing in general, regardless of the media type, or who the buyers and sellers are, and establish these foundations before consumers set precedents that are harder to unravel, which could deflate a content's value before it has a chance to flourish.

The good news is that some developments are already under way. But, to put them into context, we need to understand today's business model, and how it evolved into what we currently work with. What we'll find is a very tight sequence that starts with technical innovation, followed by social adaptation, which affects financial incentives, which comes full circle to innovation again. This feedback mechanism of constant reinforcement and revision is an economic truism. Since the technology is already underway, and some of the social fabric is similar taking shape, the only question that remains is how the business environment evolves with it.

Web 2.0 Business Models Setting the Stage

Most people are familiar with MySpace, FaceBook, and Flickr as common and well-known examples of social-networking sites. They are essentially places where people sign up and contribute "content" in the form of information about themselves, while also contributing photos, music, poetry, writing, and ideas of various sorts. In return, they get to socialize -- learn, teach, meet, and access.

Getting people to participate and contribute content is what is commonly called, "Web 2.0", and most sites on the internet are so enabled. You can visit most any blog, news organization, movie review site, shopping site, or cooking site, and you'll probably find a way to contribute something, whether it's as simple as voting on how much you liked a book, or as involved as contributing your own recipes, movies, photographs, short stories, or politically biased nonsense that you hope others will agree with.

While this kind of activity has always been technically possible to program into websites, these features of the web were largely ignored until there was a business incentive to use them. That incentive came in the form of Google's advertising network. If a site had good information, and it was indexed well by search engines, advertisers paid more dollars to have ads there. Consequently, for a site to get those advertising dollars (or to sell its own products or services), it needed to be indexed well, which means it needed more content. The easiest and cheapest way to get content is to encourage people to contribute their content. The incentive that sites give to consumers to contribute is the "social rewards."

By being smarter, funnier, cuter, or more ridiculous than others, people get attention, and people love that. So, websites used the "social" carrot to get people to participate, and in return, the site got its free content, and of course, traffic. These both raise the site's raking and boosts advertising revenue (or sales of their own stuff). Today, it's almost unheard of that sites don't have some way for users to contribute. Everyone wins.

What's notable about this development is that it was unintentional. Social websites had been around in earlier days of the net, but didn't really gather much attention or traffic. Even of those that did, it wasn't easy to make any money from those users. No one bought anything, and they wouldn't pay subscription fees. So, having millions of users did nothing but cost the company money in technical infrastructure (which itself was vastly more expensive than it is today). Companies that had stuff to sell typically didn't garner much traffic, except for dating sites, like match.com.

It wasn't until Google introduced its auction-based advertising model that inadvertently rewarded highly-trafficked sites with unanticipated revenue did a financial incentive exist. There was then an instant awareness that social-networks is where the money is.

Yet, it was never Google's intention to create social networks or any other kind. In fact, it didn't intend to affect the nature of the internet at all. It just wanted to create a model of analyzing the internet as it is (or was) for purposes of setting auction-based advertising rates. They did not anticipate that their very act of analyzing data actually changed the very data itself. (This is a perfect example of Heisenberg's Uncertainty Principle.) Indeed, not only has the data changed because Google observes it, they created a feedback mechanism where the more they looked at data (and thus, reported their observations by way of search rankings), the more the data itself morphed into to the kind that people thought Google wanted to see. This, in turn forced Google to change how it looked at the data, because people were manipulating the content on their sites to artificially bump their rankings higher.

And so it goes to this day: websites and search engines are in an endless cat and mouse game, where sites try to get higher search rankings, and for Google to maintain a plausible ranking system that users can trust to be objective when they search. This credibility is required for advertisers to trust it.

This underscores these basic, fundamental socio-economic principles:

1. Financial incentives promote user behaviors.
2. Examining user behaviors to calculate financial incentives causes sites to filter those behaviors that optimize financial returns.
3. The constant feedback mechanism and subtle refinement of behaviors and economics creates a state of unpredictability.
4. The unpredictability invokes the Law of Unintended Consequences, which yields a new economic model.

This begs questions: What's next after Web 2.0? And what are the potential byproducts from whatever that is? More social networks? Or something else? Our objective here is to anticipate future financial opportunities without forgetting that the feedback mechanism produces unpredictable results. Also, the Law of Unintended Consequences suggests that examining user behavior changes those very behaviors, which itself often forms the basis for new developments and incentives. (Knowing the future will affect your behavior, thereby changing the future.) But, as any good entrepreneur and venture capitalist know (er, should know), the goal isn't to predict or (worse) to control or shape the future, but rather, to anticipate the parameters that are most likely to frame that future.

Web 3.0

The answer to "What's next?" is easy: Web 3.0. In inner circles, this is called, "The Semantic Web." That is, the content on the web that was generated during the Web 2.0 era will be more intelligently analyzed than before. In essence, the data is not just indexed as it is today, but is being better understood for its semantic meaning. This very core nugget of change sparks a feedback mechanism on a very large scale, which will transform the economic foundations of the internet, much the same way the web itself changed the world.

For example, let's say you have a weird and embarrassing rash. Today, searching relies on brute-force matching of search terms, such as "weird rash" or "red rash". Type that into Google, and the results you get are pages that happen to contain both words. Though the pages themselves may be ranked according to popularity (the Mayo Clinic's site may rank higher in search results than some guy's blog), you still have to sift though more than just the first set of results to find what you're really looking for.

You could do an image search for "red rash," but search engines don't really know what's in the content of photos. If you were to do such a search on images.google.com, you'll get photos of red rashes, but this isn't because Google analyzed the photos. They match because the photos happen to have the words "red" and "rash" in the image's filename. E.g., red-rash.jpg. (Google also looks at the file's pathname as well as the filename.) If you try it, you'll see there are photos of every possible kind of red rash you can get, most of them having nothing in common with the others, nor are they sorted or ranked in any intelligible way. The results are merely arbitrary listings of all matches for images with properly-named files. Google relies on the fortunate-but-useful naming convention that some people happen to use when naming their photos: that they name their files according to their content. In practicality, this technique is spurious and nearly useless, but it's the only thing they can go on for the moment. As it is today, you have to examine each photo and see whether that looks like your rash, and then examine each of the pages that the came from to determine what the rash is.

That google relies on photos' filenames to match their content is not just unreliable, it's not even complete. Statistically, most people don't change the filenames of their photos; they leave them as they were from the camera, such as DSC1004.JPG. Photos with those names are never going to come up as a search result for any search, let alone those that could be potential (and valuable) matches for relevant searches, were the search engine to genuinely know what it was searching for. So, there's a lot of photos out there that may be of red rashes, but they aren't found because there's nothing about them that indicates that's what they are.

Pro photographers may be asking, "what about metadata? What about the keywords that I apply to photos? Why doesn't Google look at that?" They don't for the same reason Google no longer looks at the "keywords" tag on html web-pages themselves when compiling results for general searches: websites learned they can game the system by stuffing these attributes with unreliable data.

People can still game the system to some degree by naming their image files accordingly, but for the moment, doing so doesn't really reward the behavior very much. It would only yield sporadic results because Google doesn't sort or prioritize results according to any sensical pattern that matters to searchers. And there's currently no other benefit to naming a photo improperly. After all, why would someone name a photo, sexy-woman.jpg if it's just a red rash?

One reason to do so would be if there were financial incentive, say, advertising revenue if your site were to get more traffic. This would provide incentive to name photos sexy-woman.jpg, even if it's a photo of a rash. As you can imagine, this would completely ruin Google's current image search feature, which is why all search engines are sort of stuck in a corner with image search results: unless they can assure some degree of reliability of results that cannot be gamed once there was a financial incentive to do so, it's best to leave the system as it is -- nearly useless, but not so much so that people don't tinker with it. Yet, there's the very paradox: because it's still the only game in town, people tinker a lot, and it's the source of most image searching on the internet today.

So, unless one can actually, reliably determine the content of a photo, image searches will have to remain circumstantial, unscientific, and without reward.

We can envision what the economic effects would be in a Web 3.0 world, where there was a better semantic understanding of media content beyond just text. Using new algorithms that can determine the content of photos, for example, you may one day search for "red rash" and get a lot more relevant search results than before, simply because the existing content on the web is better understood.

Image-recognition algorithms are evolving in many ways, and look for very different aspects of images to determine characteristics, genres, attributes and, ultimately, content. A couple examples that I often cite in my blogs are tineye.com and picscout.com, which examine photos and find "similars" on the net based on pattern recognition by identifying photos (and portions of them) by assigning a unique "fingerprint ID." Another site, xcavator.net finds photos based on conceptual elements and can do so using specific keywords, like "train" or "window." Using this technique is even better than a text search for "red rash" or "weird rash" because the image recognition algorithm can do a better job of analysis and ordering results accordingly to proximity. Here, you could just take a picture of your rash, upload it to the web, and you'll get search results that are not only more relevant, but they can see similarities and differences that humans simply can't, or would overlook by an untrained eye.

And image-recognition is only one example -- there is also music-recognition technologies that do the same sort of thing. Shazam (www.shazam.com) is a site based on music-recogition technology that is evolving its own economic model by itself. Sing a portion of a song you like into the phone (connected to the company), and it'll tell you what song it is. That's just one application of its technology, and the company is partnering with many different, diverse businesses, many having nothing to do with the web or "search engines" directly, but it is nonetheless a search technology with widespread economic effects that are, so far, unanticipated by industry watchers. A similar-but-different development from Widisoft (www.widisoft.com) does more detailed analysis of music for conversion between music file formats that assist musicians and sound engineers to better compile and arrange musical components of a song.

The social (and, by extension, economic) ramifications of all these developments should be self-evident to anyone that works in an internet or media company. Economic predictions, on the other hand, would be premature without understanding how these technologies would evolve both technically and socially.

Problems with Deployment

The first question most people ask is why aren't these websites (or their technologies) more widely deployed, or even more usefully employed, especially by larger search engines? Several reasons.

First, these algorithms are still pretty young; recognizing patterns is a difficult and imprecise science. Of course, so is traditional text search, but the difference between the two is rather substantial. (Just matching a photo with another photo -- or a song with another song -- isn't yet sufficient for a "semantic" search.)

Second, pattern-recognition of content is only the beginning. Information about what those patterns are and what they mean still need to be seeded, and that information needs to start from humans. This isn't a major barrier, as the current Web 2.0 content on the internet has a great deal of that info already. But, its vast size and disorganization means that time is required to harness it properly. During this process, major search engines are left to guess at semantic meaning from the text on the same page as a photo, for example, which is similarly error-prone and unreliable as their current method of file-naming, though a notch better. The lesson we learned about examining data altering user behavior must be heeded strongly here: if there's incentive to "lie" or manipulate data, search engines will lose credibility.

Thus, the third problem: trustworthy information about content. Because there will eventually be a financial incentive to provide trusted and controlled data feeds about various content types, new methods need to be established to "search and rank" the sources of information. That sounds similar to traditional text search and rankings of websites, but in this case, it's not the site's credibility at stake; it's the credibility of the data found on the site. Or rather, the information about the content. (That is, the description of the rash in the photo may need to be ranked, which may be independent of the site that hosts the photo.) Unlike the text on a site that can be interpreted and ranked -- which is closely linked to the site -- photos and other media types on that same website can be sourced from anywhere, and the data about that media may have well come from an entirely different source. In the Web 3.0 world, it will be much more common for crowd-sourced content to be annotated by someone other than the content's creator. (Wiki-based sites are good examples of this today.)

And lastly, the three problems noted above will be difficult to do by any one entity, since the ingredients in this recipe require participation from many different organizations. Getting that participation is difficult, especially since each is intimately focused on their own small views of the world. (This is the very problem that every player in the photo licensing industry exhibited, which is the primary cause for its slow demise.) Having an entity that sits on top of the trees and sees the broader economic opportunities that it can use to direct which direction the tribe goes in hatching through the forest is not easy, and no one is currently poised to accept such a role. It will unlikely be a small organization, and larger companies tend not to have entrepreneurial spirit or vision.

Yet, these technologies continue to develop. Just as Web 2.0 evolved relatively slowly, so too are Web 3.0 capabilities, and with them will be leading industries that pave the way for the others by establishing standards and protocols that set the economic wheel in motion. The economic wheel for Web 2.0 was advertising dollars and traffic, so people looked to Google for the parameters to design sites and user experiences that lead to traffic, so money can be made. In the 3.0 world, there is currently no such leader, since it isn't yet clear where the incentives are. Nor will such a model exist without having experienced the iterative social feedback mechanisms that are part of every economic development.

What might that social environment look like? Let's consider your rash again: You take a picture of it, upload it to an image-recognition site, which matches it to a set of potential candidates, and each one checked against a medical website that has information about the rashes, which are then fed into a pharmaceutical website, which may list potential remedies. If it turns out you just went camping over the weekend, you can assume it's likely to be poison ivy and choose the appropriate remedy. If, on the other hand, you recently visited the red light district in Bangkok, then your spouse will be alerted, and your lawyer will be notified to accept the divorce papers being prepared for you.

Such possibilities would be objectionable to many, so limitations would be naturally put into place to protect privacy. And that's just one example. As technologies develop and new capabilities are evident, people react, and social acceptance or rejection alters future developments. These must take place before effective and long-standing economic models can form.

Personalized Search

A critical component of this social evolution of Web 3.0 is found in a very old technology that hasn't been exploited to its potential: that of "predictive preferences." That is, search results being ordered according to what might be appropriate or relevant to the searcher. While many may not be aware of it, the vast amount of raw content from the Web 2.0 world is being analyzed by "crowd-analysis algorithms", which look at data that people have voted on or expressed some kind of opinion about. This data is then examined for patterns to predict how individuals might like something, which can then be used to determine whether any given search results should rise or fall in "relevance" ranking.

In the music industry, there are two applications of this technology that you may be aware of. Amazon.com has been using predictive preferences for years, and I rely on it almost exclusively when I buy music. I let amazon choose new albums for me based on what it knows about me: the things that I've bought in the past, searched for, and/or rated my preferences for as it tracks my behaviors on its site. It even looks at preferences that aren't music related. when it offers suggestions for what I'd like, I'm always shockingly surprised at its accuracy. (Porcupine Tree is my latest miraculous find.)

Another example is Pandora (www.pandora.com). People with an iPhone were recently introduced to it this way: name a song, a band, or a genre, and the site will stream music to you in radio-station format, all comprised of songs that you are likely to enjoy.

Part of how pandora does this is by applying conceptual attributes to songs, such as "acoustic guitar solo." There are over 400 such attributes, which the site calls "the music genome project." This requires humans to assign such attributes to songs manually at the moment, but music analysis isn't that hard. It isn't a stretch to envision combining these two technologies, so that an algorithm determines attributes based on digitized sound waves, which it can then assess and assign to other songs in real-time.

Hypothetically, I could rent a car in a city I've never been to and program the radio's stations by singing a song that I happen to like. The radio can be instantly programmed to assign stations to the preset buttons. No more "scan button!"

A similar "genome sequence" of photography or video has never been done (or proposed as far as I know), but it seems as one would be inevitable, and would lead to another step in the semantic understanding of media on the web. When you combine the semantic understanding of content with predictive preferences, you have a readily monetized network of resources that, currently, no one is capitalizing on.

Web 3.0 Business Model: It's the Content, Stupid

This scenario presents the potential for a pivotal economic shift of focus for where value is: from the website to content. As my earlier research in the photography realm revealed, the less time it takes for a searcher to find a relevant photo from a search, the more likely it is that the searcher will license it. There's every reason to believe that photos are not unique to this human behavior and economic need. The semantic web will make it easier to find content of any sort, and if the searcher's results are also tuned to their particular preferences, it raises the likelihood that such content would be purchased beyond the ratio we see today. Thus, the value of content on a site goes up because it has a higher chance of being monetized.

Remember all those photos named, DSC1004.JPG? That's content that is currently next to useless because it carries no semantic meaning, and is therefore not seen or understood by current search engines. The semantic web will eventually find all those abstract media objects and make sense of them, adding them to the set of possible search results. Such data exists in all media types, not just photos, making the economic possibilities far greater than anyone has anticipated. So, once all the "useless raw content" from Web 2.0 is semantically analyzed, it is likely to emerge in the Web 3.0 world as "invaluable data assets" that contribute even more to the Long Tail of internet economics.

As the perception of content's value continues to increase, Web 3.0 sites will have more incentive to attract those who create quality content.

An example illustrating this socio-economic development can be found in this story from the New York Times. Joel Moss Levinson, "a college dropout with dozens of failed jobs on his resume," has earned more than $200,000 by creating homemade movies that major corporations are now using in their mainstream commercials. Where'd they find them? YouTube. The article goes on to mention many companies getting content directly from common consumers, rather than through traditional ad agencies, and how this trend is reshaping many aspects of the Marketing and Advertising industries.

The beneficiaries of this are obviously not just limited to individuals. While Levinson created his own content, there's quite a bit of mainstream content from traditional media companies that can be applied to the same business model that benefits them: make the content available for a fee. More and more consumers are actually paying for movies and videos over the web, which is a trend that was once predicted, but failed to materialize for years. In fact, there was doubt that it would ever happen, because users just got used to the net being "free." Many early sites that tried to charge for membership found they couldn't make the numbers work. But as users are learning that good content is harder to come by, this model is finally becoming economically stable. And, it has a twist: users are not just getting content for pay, but are also given further incentives to contribute as well, such as feedback or other information about the content they're paying for. These incentives come in the form of reduced fees, or in the reduction of advertisements the visitor otherwise has to see before getting to see the content. An example is found in this article in the New York Times, where Hulu (www.hulu.com) allows visitors to view programming with fewer ads, and encourages visitors to vote on shows with thumbs-up and thumbs-down buttons.

As new and different kinds of websites are built to respond to that economic incentive, websites will continue to reinforce this behavior by adjusting compensation and other reward systems. They'll also want "semantic information" about that content, not just raw data, which changes the user experience, which changes the nature of how and why people go to websites in the first place.

Evidence of this is already making headlines: YouTube's recent announcement that they will now begin to enable users to purchase songs and other content found on the site -- whereas, before, such content was only used to attract more visitors. Similarly, Flickr's relationship with Getty Images is one where a company is cherry-picking user-generated content from a social network and selling that very same content on a professional photography site. Still another example is the growing basket of online discussion forums that are converting from "free access" to paid-for access, which is the most overt illustration where a site is changing its business model from using user-generated content to attract visitors, to one where that same content is used to generate subscription fees.

All this is part of the feedback mechanism that perpetuates unpredictable change. As users themselves are ranked and "scored" for the various content types they create and contribute, a phenomenon that already exists in many forms on social networks and discussion boards, there would be an amplification of this if there were financial incentive to raise your rankings. Or, to lower others' rankings. This type of human behavior has not yet been put to the test in a broad scale on the internet yet, so its economic effects cannot be predicted.

New Frontier for Web Design and User Participation

The economic models I described above have all been on insular sites that host content. That is, people realize that content has value, so they are using Web 2.0 world to find it. However, in the Web 3.0 world, content may very well exist on websites that don't yet have an ecommerce infrastructure. It's not just about taking credit cards or other forms of payment, it's about pricing models and legal licensing terms. This is the very inefficiency of peer-to-peer licensing that I focused on in part one of this series.

New internet-wide methods and protocols must be established to enable any website that carries licensible content. As more and better content is produced, and as search engines are better able to analyze it semantically and produce search results sorted by personalized preferences, more of the content must be licensed through a universally available infrastructure, thereby transforming the way websites are designed, further affecting the visitor behaviors and incentives.

So what about that licensing mechanism? One such development in this area is ACAP, which is found at http://www.the-acap.org/. ACAP stands for the Automated Content Access Protocol, and its main initial purpose is for communicating access and usage permissions (about the content on any given site) to web crawlers (also known as 'spiders' or 'robots'). Just as you currently accept (and need) Google and other search engines to crawl your site to index it so it will come up in search results, an ACAP search engine will do the same thing, but it looks for other details about your content besides its semantic meaning. It is used to specify license terms and conditions that the owner stipulates, should someone want to license something from your site.

Of course, this a huge and complicated effort, since mechanisms need to be put into place to track and verify content ownership. But, waving the magic wand about that for the moment, if it were to exist, this then paves the way for a content licensing protocol to sit on top of the entire stack of media and search data about it, to complete the puzzle: any content crawler could assess market conditions for any given type of media type and estimate a market value. Plug that into an existing auction-based system like Google's adwords program, and the financial models are in place for the new economic model where a series of automated analytical robots crawl the web, analyze content, rate and rank its information and its creators, and come up with a high/low range for pricing, which can be used to see a more fine-tuned auction-based mechanism.

As futuristic as this may sounds, all of the technologies that do these tasks exist today in one form or another. It's merely applying them in a generalized way to arbitrary and abstract data types that makes it an inevitable development. What's more, it's self-regulating and self-perpetuating. Taken out of the equation is the inefficiencies of peer-to-peer licensing models, where prices are arbitrary, and the transaction itself is costly and time-consuming.

Just as Web 2.0 created a feedback mechanism (where social networks yielded financial returns, which stimulated the growth of social networks), the Web 3.0 world will have a similar feedback mechanism, where content creators are given incentives to create good content, describe it well, and allow third-party, automated market-makers to handle transactions. Though the content itself may still be exchanged between creators and publishers, the transaction will more likely be officiated through market-makers.

It's also a more efficient system in that incentives to cheat are reduced. This comes in two forms. First, because everyone's search may not necessarily yield the same results, attempting to manipulate content to match what someone might think search engines are looking for may actually diminish the content's value. Searchers looking for a photo of a "woman" aren't always looking for porn -- they may genuinely be looking for a photo to be used in legitimate mainstream media. If the content creator tries to "lie" to manipulate search engine results for the photo, he may inadvertently eliminate as many buyers as he would attract if he were just honest about the content in the first place. That's not to say that all content is equally valued, but that brings up the second aspect to semantic awareness by search engines: the content itself would be ranked, not just the site it came from. If a particular set of photos were manipulated with "keyword pollution" (where the photographer adds a huge amount of keywords in the hopes of being indexed to match a large number of search parameters), then that image would be reduced in its credibility ranking, irrespective of what the photo's content actually depicted, or what site the photo came from. Being a bad actor in the economic game has penalties, and being a good actor has rewards.

The Spoiler

So, what can disrupt this potential future? The elephant in the middle of the room that I haven't mentioned is Copyright. That is, user-generated content is copyrighted material, owned by the creators of content, and that creator has rights. The ability for a website to sell content that visitors submit is restricted in ways that aren't entirely easy for everyone to quickly understand, and navigating around this restriction involves an exercise in skills in three disciplines: political, legal and socio-economic. I'll tackle all that and more in part three of this series. Stay Tuned.

Stock Photography, the Consumer, and the Future

Preface

I apologize in advance for the extreme length of this article. I hardly expect anyone to read it in one sitting, or to even finish it. Those who do read it may be eligible to win a free pizza. Or better yet, to improve their understanding of the photo industry.

This article was pieced together from the results of several consulting contracts I've done for particular clients looking at various investment options in the photo licensing space, most of it written in the last six months. I've removed the specific citations of particular companies that I was asked to research, but in the end, I've manage to maintain cohesion in the overall message.

Synopsis

In this article, I will be addressing: Stock Photo Price Erosion Historical Trends of Stock Photography Is the Stock Photo Industry Growing or Shrinking? The Consumer and The Long Tail Market Efficiencies and Effects on Pricing Long-term Industry Prospects (expand, contract, or remain flat) Market-Maker Model for Optimizing Prices How and Why Pros Benefit from Consumer Involvement

This coming October, I'll be presenting a talk at the Photo Expo Plus conference in New York City, called, "Stock Photography and the Consumer". You can find a link to the list of sessions here. Search for my name to get the specifics on the talk.

The abstract of the session presents the premise for this article:

Licensing stock has yielded lower financial returns in recent years, mostly because the target audience are the companies familiar to photo industry veterans. While this audience tends to buy in larger volumes, they represent a small fraction of overall purchasing for photos online. The largest growth curve for photo buyers is the consumer.

This article is a sort of primer for the session I'll be presenting at the conference, but it gets into depth on auxiliary information that may not be covered due to the two-hour time constraint. This article wasn't written just for those attending my session, but rather, for anyone interested in understanding the broader economic impact that consumers have on the stock photo industry.

Current Business Strategies

With a few exceptions, most pro photographers would agree that their incomes from licensing stock photography has dropped over past ten years. Finding a way to reverse this trend has been a top goal for photo trade associations and de facto industry leaders. They have come up with a variety of proposed strategies, but the one that continually remains at the top of everyone's list is characterized by the following populist quote from a discussion forum frequented by stock photographers:

Stock photo industry is on the decline. And the reason is because microstock agencies are driving prices downwards, and pros and semi-pros are not being consistent or cohesive in their pricing structures. The solution is to create a standardized pricing system that everyone adopts.

NOTE: A prior edit of this article mentioned that the Stock Artist's Alliance (SAA) and the PLUS coalition supported a pricing standard. This was erroneous -- they advocate standardizing certain terminology to be used in licensing agreements, an aspect of this article that I had originally included, but later removed.

The rationale for believing this approach will reverse price declines stems almost entirely on the premise that pro photographers see themselves as the primary (if not sole) suppliers of images to buyers. In other words, industry groups believe that, while the consumer's role in stock sales has been destructive in pricing, they actually contribute very little in the overall supply of licensed images. Therefore, if at least the pros cooperate on a price structure, buyers have no choice but to pay them, because pros really are the market-makers of their own products.

Believing that this strategy will work is rooted from a historical and cultural bias that dates back to the pre-internet era, when it was true that the supply of images was controlled by stock agencies and a smaller, limited set of pro photographers. Indeed, pricing stability was not only achieved, but optimized. Cohesiveness among agencies and photographers was not difficult because very few controlled the entire photo channel, allowing them to regulate how much supply entered the market. The thinking today is that such a model can be brought back.

Why cooperating on price doesn't work.

The "Nash Equilibrium" states that no matter how much competitors agree to maintain price stability, the ones who benefit the least will betray the others in order to win business. And this act will force others to follow suit just to stay competitive, thereby bringing equilibrium to the group. In other words, "market rates" will ultimately prevail. While there were few enough players in the industry in the pre-internet days to control the channel, there are just too many people involved right now to sustain compliance, as dictated by the Nash Equilibrium. For more information and discussion on this topic, see my article, The Photographer's Dilemma: to cooperate or not?.

But today, with the internet and digital photography, a huge amount of inventory has entered the supply chain from a variety of sources, mostly consumers. Therefore, adopting "price structures" will fail simply due to supply and demand. Worse, it could actually cause more harm to pros who vow to adhere to these prices charts because they would price themselves out of the market, as dictated by the Nash Equilibrium (above).

So, if photographers don't accept that consumers photos are not disrupting the natural balance of "supply and demand", nor do they accept the principles of the Nash Equilibrium that voluntary price adherence won't work, what do they need to see that will help them change their fundamental business strategies to be more in line with current economic realities?

Perhaps we should start looking at a global picture of what's going on in the stock photo industry.

Is the Stock Photo Industry Growing or Shrinking?

It's a simple question, one that you wouldn't expect to be asked seriously. Rather, you more often see it as a rhetorical question used to underscore a different point, as illustrated by the quote at the top of this article: The stock photo industry is on the decline. And the reason is because microstock agencies are driving prices downwards..."

Yet, I seriously ask, Is the stock photo industry on the decline?

Here are the pivotal questions that can help address that problem:

1. Do most published images come from pro photographers?
2. Are most photo buyers consumers or traditional media companies?

As I'll illustrate in the following sections, the data I've been collecting over the years (in particular, the last six months) shows that even though per-image pricing has dropped, it has been more than offset by volume, resulting in a net increase in dollars spent industry-wide on photography. The bulk of that extra money is being spread thinly and broadly to millions upon millions of suppliers that are not traditional players in stock. Who are those non-traditional players?

Do Most Images Come From Pros?

To find out, I examine two data points: the rate of growth of the publishing industry, and that of the stock licensing industry. For publishing, we examine the rate of growth for print and online mediums that use photos, where growth is estimated to be between 20-50% per year since 2000, depending on various metrics used to determine the size of the internet. (Google ad rates along with other agencies that sell online advertising that use photos are example reference points.) Even using a conservative growth estimate of 10% per year, the past 8 years would yield a compounded increase of more than double the size it was in the year 2000.

This kind of information is consistent with other data I've found in prior analysis I've done on the size of the photo licensing industry. I've estimated the size to be between $15-20B, which I've published (along with my analysis) here, here and here.

When more photographers try to stuff into a VW Bug and things get tight, it doesn't mean the car has shrunk.

By contrast, reports generated by stock photo industry trade associations and financial analysts who follow publicly traded companies, such as Getty and Jupitermedia, do not show any growth at all since 2000. It was a $2-3B industry then and remains so today. Also consider that there are also 10-20x more "traditional pros" as there were 10 years ago, as measured by the increased number of photo organizations and their aggregate membership numbers. Distributing the same $2-3B revenue to 20 times more photographers than before means that pro photographers are not just earning less per sale from falling image prices, but they have to share their piece of the pie with more people.

If traditional pros and agencies are only getting $2-3B of a $15-20B market, are consumers somehow earning and spending the remainder? To a degree, yes. But not entirely. There is a great deal of money that is also lost due to "economic evaporation", due to pricing and distribution inefficiencies discussed later. First, I'm going to address the portion of the sales pie represented by consumers.

The Long Tail

In a phenomenon coined in 2002 called, "The Long Tail," a reporter for Wired magazine noted that the huge revenues generated by amazon.com came from the sales of millions of little-known books to millions of consumers, who, prior to the internet, were never even aware of such books, nor had they the means or incentives to find them. In quantities of one's and two's, these unknown books were sold to random people on the web in a manner that added up to billions more dollars of unexpected market potential than industry analysts and economists had anticipated. Though all eyes tend to look at the mega-blockbuster hits, the real money is in the really small sales of one's and two's to inconsequential buyers. The top 100 books that sold in the millions only represented a tiny proportion of amazon's revenues in comparison to the millions of these tiny sales of little known books.

Is it the same story with photography? Is the vast proportion of sales between consumers, not directly with stock agencies and established pros? If the estimate of the market size is $15-20B, and pros only account for $2-3B, then the gap must be accounted for. Unfortunately, showing where those sales are coming from using precise numbers (as can be done with amazon.com sales) is not as simple; amazon is a monitored sales channel because it is a public company, so we can examine their financial results. Ad-hoc sales by consumers is not.

Deriving information about the broader market from a monitored sales channel like amazon.com is possible using symmetric analysis because sales figures correlate with the information we seek. That is, we can look at amazon's reported earnings and derive that most products sold are not the "big hits" of best-selling books, but rather, millions of smaller sales in one's and two's. If you were to graph this, these small sales would represent a very long tail of bumps along the bottom of the X axis.

Photos by consumers, on the other hand, are not sold through monitored sales channels, making such "peer-to-peer" sales difficult to track. We don't have direct numbers we can analyze from public companies or trade groups (because consumers don't join trade groups).

Therefore, to find the information we seek, we need to examine asymmetric information, or rather, data that doesn't directly correlate to the information we want. Because of the indirect nature of this data, we need to find more data sources than just one, and then extrapolate information from the aggregate. This is similar to how GPS systems locate you: they get data from a number of satellites, and derive your position from that aggregate. The more satellites there are, the more accurate the estimate. So, the more data we collect from "indirect" data sources that hint at consumer sales potential, the more accurate our estimates will be.

One such satellite in our search for data is the historical sales trends of pro-level cameras. Up till the year 2000, there was a direct correlation between pro-level camera sales and those of stock photo sales, as compiled by industry trade associations for both cameras and stock photo trade groups. After 2000, the trends went out of parity: pro-level camera sales spiked, but official (industry-provided) stock photo sales figures remained flat.

What caused this breakdown of symmetry? Either one of the data sets is wrong, or there is another element in the equation that hasn't been factored in. Since the "official industry figures" on the size of the stock photo industry does not include peer-to-peer sales, there's a strong chance that this is the missing data. The traditional industry analysis failed to recognize non-traditional contributors to stock licensing.

A strong contributor to this is the proliferation of pro-level digital cameras after 2000, which made pro-quality photos more easily available online, and for sale in general. In other words, if consumers were buying pro level cameras prior to 2000, they were mostly film-based cameras, and consumers never went to the bother of scanning their images. Digital images, on the other hand, are easily and instantly made available for distribution, which is the beginning of when consumer's role in photography licensing began.

Another satellite providing data is the rate of growth for photo-centric media, such as magazines, web sites, general advertising, to name a few. According to data mined from those industry trade associations and trade magazines (such as "Advertising Age"), growth to the year 2000 also remained symmetric with official industry data for stock photo sales, just like with data for pro-level camera sales. After 2000, the graphs go out of parity; media growth continued, but the stock industry numbers remain flat. Again, this asymmetry suggests that the industry data is erroneous. When you factor back in the peer-to-peer sales, again, the symmetry between the graphs returns.

The more data you collect from this asymmetric information, the more it supports the notion that the size of the stock photo industry is much larger than what most people had thought. Thus, the unaccounted for sales must be coming from non-pro photo photographers. The question is, who?

What is a "Pro Photographer?"

Is it the consumer? Perhaps, but we may have to step back a second to define our terms. What's a consumer? How do you define a "pro photographer?" What's the difference?

For example, Lifetouch Inc is a private company with over 22,000 employees, and they do one thing: portraits (in many forms). They have an annual revenue of over $1B. The company provides model releases for subjects to sign, permitting the company to license the photos to others. This is classic "stock photography licensing." Whatever revenue the company may generate from these sales is not calculated into the "size of the stock photo market" by industry trade organizations. And Lifetouch (and their competitors) represent a very small niche in the overall photography business segment.

Are the photographers that work for LifeTouch "pros"? For that matter, what about others who also shoot portraits? For example, in this article from The New York Times (April 2007) looks at stay-at-home moms generating extra income by shooting portraits of their neighbors' kids. Are they consumers? Or pro photographers? And they aren't the only "consumer/photographers" doing the same thing. How do we categorize these people? Some are part time; many happen to be hobbyists or enthusiasts who don't really earn that much money with photography. But, the pictures they shoot are ending up in the stock photo supply chain as potentially licensable pictures.

Imagine if we expanded this research to include photo-based business units from all possible sectors, not just portraits, like LifeTouch is. We'd see a great deal of additional photos (and money) going into the "stock photography pie" that has traditionally been dismissed as irrelevant numbers by the stock photo industry. To them, they were consumers. But now?

You can't have it both ways -- if you call them pros, you have to factor in their contribution to the stock photo industry. And since photo trade organizations don't, nor do people who calculate financial data (such as "the overall size of the stock photo industry"), then we have no choice but to call them "consumers."

No matter what you call them in the end, the size of the stock licensing market is enormous, and the suppliers of images clearly include millions more people than had been counted before. And those new members represent a much larger percentage of the economic activity than the traditionally-defined "pro photographers" and stock agencies. By failing to recognize this group, photo industry trade groups and companies that profit from stock photo sales are mis-managing their businesses and missing out on a great deal of opportunity.

Do Consumers Buy Stock Photography?

To answer this, we're faced with a similar question just posed above: How do you define a "consumer?" When someone licenses an image, how do we characterize the sale? By the use of the licensed image? That is, whether it is used for business purposes or personal use? Are the two so easily separated? The IRS reports that 80% of employed people work for a "small business." If you sell an image to a handyman making a small brochure where he advertises fixing people's plumbing and light fixtures, is this a consumer-sale? Or a traditional stock license that would be included by photo industry trade groups in their analysis?

For purposes of the data we seek in this article, I consider a buyer to be a consumer if he is not familiar with the stock photo industry, does not go through normal channels, and most importantly, makes purchasing decisions as a consumer would, not as a business typically does. Consumer purchasing decisions differ from businesses in stock photography because they don't understand traditional license rates, are unfamiliar with license terms, don't know what model releases are for (or how they apply), or even that photos need to be "licensed" in the first place. In fact, many who license photos from me usually start the process with an email that says, "I'd like to use a photo of yours, but I can't download the high-res version (because it's not there to download). How can I get it?"

I then have to explain what photo licensing is, and why they need to pay for it.

Example uses of recent photo licenses I've sold to consumers:

1. Self-employed handyman's business card
2. Wallpaper for a bedroom
3. Wedding invitation
4. Set of place mats for a large family reunion
5. Cover image for a local musician's self-produced CD

Most of these uses are clearly for non-commercial, personal uses. Others could be considered in the middle. Either way, the people buying the images are not part of what most photo industry trade associations consider the traditional photo buyer. Thus, they do not consider this demographic a group with strong purchasing power. Hence, it's not a viable market.

I disagree with this. Given that I'm one person, and I license photos almost entirely to consumers on a regular basis, it's clear that there's a market out there. Furthermore, I do not consider my experiences to be merely anecdotal. They represent viable market conditions for these reasons: First, my traffic statistics are not insignificant, ranging from 12,000 to 28,000 visitors a day (summer and winter traffic on my site varies in parallel with industry averages). This in itself is considered to be a viable sampling of the general population at large. And since my web traffic runs in parity with my sales figures, it's fair to say that the general population acts consistently over time, given the same conditions. I've spoken to other independent photographers who sell on their own websites in the same manner, and they report similar patterns as well, though their ratios of traffic-to-sales differ from mine. (See here for my web traffic stats.)

Speaking of traffic-to-sales ratios, most people "stumble" onto my site, rather than go there specifically for the purpose of acquiring images. My ratios would be much higher if I were a more commonly known resource. (I do no advertising of any sort.)

Yet, even with my statistics, if the same traffic-to-sales ratios were to scale up to the broader market, sites like Flickr.com could be generating revenues in the $3-6B range annually. I would venture to say they'd earn even more because the site is a destination for people to look for photos. Flickr would also attract more of the traditional media buyers as well, a target audience I don't attract (because I'm not a known entity for traditional media buyers). People who license my photos never heard of me before they landed on my site--they got there by happenstance, the result of search engine results (for which I tend to rank highly). That wouldn't be the case for Flickr.

And therein lies the magic hen for laying the golden eggs: search engines. That's how most consumers find photos, whether it was their intention to license them or not. Traffic to google's image search far exceeds the traffic on every other photo-related website (by huge orders of magnitude), that even if only .1% of those searches results in a sale of any kind, this would generate revenues that far exceed the combined revenue of all stock agencies combined. And the use of search engines for photos is growing as the need for those them increases, while the photo industry continues to ignore the consumer by not promoting themselves in the mainstream as a consumer-oriented resource.

So, now we get to the most obvious of questions: If Flickr "could" get that revenue, but isn't (because they don't offer users the option to license photos), nor are there many other sources where consumers are aware of licensing, how does that affect the total dollars consumers spend on stock photography? That is, if they never heard of stock licensing, and if there aren't enough sites that service the consumer's need to license images, how do we know consumers are generating economic activity?

Inefficiency and Evaporating Money

This brings me to a critical component of the stock photo industry: unrealized revenue. That is, much of the money spent on acquiring images is actually not going to anyone at all due to inefficiencies in the system itself. Think of it as energy lost when you're driving with one foot on the brake. You waste a lot of gas because the brake is siphoning potential speed from the car. You've spent the money to buy the gas, but that investment isn't being used.

Similar inefficiencies in the stock photo industry creates a condition I call economic evaporation. The money is spent, but it doesn't go to anyone. I think of the stock photo industry as being more like a gas guzzling 1975 Buick than a Toyota Prius of today. It's outdated and wasteful.

Analogies aside, what are these inefficiencies in the stock licensing system? The greatest of them all is the one I cited in the prior section: people search for images using non-licensing search mechanisms (like google). As a result, they either don't find the images they want, or they have no way to (legitimately) acquire the images from the supplier (because the site they landed on doesn't license images). This often leads to either intentional or inadvertent copyright infringement. (I say "inadvertent" because most consumers are unaware that using photos in certain ways violates copyright. A condition which I'm finding more and more frequently of my own photos.)

Some economists would call copyright infringement a form of unaccounted economic activity because it really does represent value, even though it's harder to value it, or know how to mark it on a spreadsheet. This "mark" has to have a value, and there is no "market rate" to assign it. This is called "mark-to-market", and is something like the mortgage crisis we're dealing with in the US today: there are mortgages tied to homes, but it's impossible to place a value on them because there's no market (or credit) to actually buy them. The lack of liquidity means that there is an enormous amount of dead capital that's keeping the economy from moving forward.

The difference is that with homes, the problem is lack of confidence in the market. With photos, however, the problem is more lack of knowledge. People just don't know that photos are licensable assets. Because there is no market-maker for photos in the general public, the general public doesn't participate in the economics of it. At least, not to their greater potential.

That's not to say that everyone is unaware of licensing, as evidenced by my business and website. People are made aware when they try to acquire an image from an informed source who knows that the asset has value. The fact that they are willing to buy is evidence enough that the market is viable. But the amount of "dead capital" in the form of illiquid photo assets is what's keeping the photo licensing industry from moving forward.

So, while the first problem to tackle is that of public awareness, we are still faced with the problem of sales inefficiency. Just because a buyer may now know that the photo is to be licensed and is a willing payor, it doesn't itself create efficiency. In fact, the buyer licensing directly from the seller (a "peer-to-peer" transaction) is the most inefficient of all. While one would assume that the lack of a middleman should create efficiency, the problem is that most people are not business savvy; neither the buyer nor seller do this very much, and hence, they either don't care, or price their products randomly or arbitrarily. Not to say that pricing is easy -- finding the right price points for licenses is hard for everyone. There is no pro out there today that can come up with a confident price quote for every photo usage he's presented with by a prospective client. I get email from pros all the time asking for advice on this subject. (I send them to this page.)

Imagine that if pricing is hard for pros, consumers must be entirely in the dark, as are the buyers! So, the economics of their exchange, whatever it is, will be very unlikely in realizing its potential value.

What's missing in the photography sector is an efficient sales channel like an auction-based model like EBay or the stock exchange. The photo industry needs market-makers.

To understand how this inefficient exchange can be turned around to an efficient one, consider trying to sell an old microwave oven you no longer need. Ten years ago, you'd have either thrown it away, given it away, or placed an ad in the local newspaper. Any of these choices would have resulted in an arbitrary valuation for the oven. Randomness would dictate whether you'd get more or less than its genuine worth; the mere inefficiency of the system meant that such things were grossly undervalued. People just didn't want to spend the time or money trying to optimize their oven's net worth.

Today, you'd just snap a few digital photos and put an ad up on EBay or craigslist. Regardless of the price you got, the market is efficient because such sites are well-known entry points for acquiring such things. Better still, the auction-style exchange means that the "best" price is obtained, even if it's not the one you were hoping for. The net result, however, is that the sheer efficiency of EBay and craigslist has infused more money into the economy by permitting the buying and selling of "stuff" that would otherwise not have a market at all (or, a poor one).

Similar economic observations have been made by economists who study the consumer's affect on other economic trends: trading stocks and bonds, auction websites, telephone calling rates, music, and publishing, to name a few. In each industry, the "traditional suppliers" for these commodities has been displaced by wider choices and less expensive options, largely because the consumer has gotten involved in one way or another, and their numbers are enormous. Everyone has seen per-unit prices drop in their respective industries, but companies that remained efficient have benefited from overall economic growth. Examples would be Ebay and securities trading websites. As the consumer started to trade stocks, commission rates for transaction dropped from $300 to $7. Many firms sprouted up, while the larger stalwarts suffered. Those who accepted and embraced the consumer ultimately did very well.

Industries that didn't adopt became inefficient and have since been harmed. Examples include the music industry (by resisting adopting of the internet in its early days, and trying to maintain sales of physical CDs through traditional retail stores), and the telephone companies (who tried to hold onto lucrative land-line fees rather than adopt VOIP telephony and other more efficient calling methods). In these industries, consumers choices moved in new directions. Successful industries (and companies within them) are those that moved with the consumer.

This model is precisely what is missing from the stock photo industry. Existing mechanisms for buying and selling photos are so inefficient, that prices are essentially random, therefore making the photos grossly undervalued. It's so bad that many people shoot their own photos, not necessarily because they want to, but because the "costs" (real or perceived) of acquiring images online (if such photos can even be found, let alone licensed) makes self-production a less-expensive option.

Here, the problem isn't dead capital (photos that can't sell due to consumer unawareness) so much as it is "dormant economic activity." That is, a willing buyer doesn't buy because he has neither the means nor the mechanisms to buy. He needs a mechanism to find the desired images faster and easier, and to license them as easily as purchasing a song from iTunes. Until then, this economic opportunity remains dormant, and the consumer self-produces the photos he needs.

Mining that dormant revenue requires understanding the psychology of the consumer. If that person starts doing general photo searches on the net, and within ten minutes starts thinking, "Aw, forget it; I'll just shoot it myself," the photo industry is inefficient. It's a "brake" working against the gas pedal.

Odd as it sounds, this inefficiency is costing the consumer money, too. The wasted time in fruitless internet searches, plus the having to self-produce a photo, both cost the consumer more than if he were able to easily find and acquire the desired image for a market-rate price.

The Future of the Stock Photography Universe

Can the photo industry evolve from the inefficient media and large-company focused niche market it is now, to a more streamlined consumer-oriented industry? As I'll address later, it's not a matter of technological barriers--that part's easy (and already underway). The challenge is effecting political change among industry leadership. Historical and cultural biases have prevented them from recognizing that economic truisms of an open-market system apply to the photo industry today, and they should shed the "protectionist" posturing of yesteryear.

Such change may or may not come about, leaving the future open to three potential outcomes:

1. Expansion model: They get it!
   The number of licensing agencies and other photo sources shed their inefficiencies and optimize pricing models that grease the wheels of financial growth, benefiting everyone in the supply chain.
   
   
2. Contraction model: They don' get it.
   Photographers and agencies don't change their business models, allowing the existing inefficiencies to force prices even lower still, eroding profitability, and ultimately collapsing the prospects for an economically viable licensing industry. Photos become penny commodities, further perpetuating informal peer-to-peer ad-hoc licensing. Most sales are done by consumers and hobbyists who don't depend on (or care about) minimal financial compensation. Specialized photography for news and advertising remains in the hands of a few select groups of photographers and agencies that have shielded themselves from the broader effects by the nature of their specialty niches.
   
   
3. Flat model: Some get it, but not enough.
   Higher demand is offset by market-correcting lower prices, allowing most companies to sustain only minimal life-supporting profitability. But, not enough players participate in the new model, causing a revolving door effect, where new companies enter and exit the industry, yielding no fundamental economic growth or contraction.

As will be addressed in the next section, it's impossible to predict with enough clarity which of these three outcomes will likely result. As more stock agencies find it difficult to compete, and the inefficiencies in the system prevent prices from rising, the sheer need to survive may eventually push analysts to look more closely at the consumer, thereby forcing the hand of industry leaders to change their outlook.

Another distinct possibility is that the industry is merely absorbed by other more successful industries that license creative content as a sub-component of much larger business objectives. In this case, it could be that enough business savvy consumers start their own organizations that react to economic realities more adeptly, which attract far more photographers than current organizations are able to do.

Market-Marker, Market-Maker, Make Me a Price!

If there is ever going to be evolution in the stock licensing industry, the first order of business is to shed the inefficiencies discussed here. And that can only happen when the system allows for uniform access to all buyers and sellers, and when the system is agnostic to who is buying or selling. This may seem obvious, but such a system is antithetical to the stock photo industry as we know it. There are currently stock agencies vying to be the central access point for licensing, and that model prevents industry-wide growth. If the market remained as small as it used to be prior to the internet, that would be fine. But, such a model can't possibly scale up to meet the needs of the global consumer population. Unless and until the industry recognizes the consumer's role, the systems they try to build will not work. And we're seeing it today in the form of poor price performance.

The easiest way to understand how an efficient system works is to think about the New York Stock Exchange: the exchange itself doesn't buy or sell securities; rather, it provides an open mechanism by which others trade. As such, everyone has incentive to be a part of it, because it's where the best opportunities are: buyers go because there's efficiency in pricing and safety in the process, and sellers go because that's where the buyers are. As more people join, the pricing mechanisms for the assets themselves become more efficient -- valuable products are priced higher, and less valuable ones are priced lower.

To those who think this is impossible for the photo industry, think about the history of online advertising. Prior to Google, online advertising was as chaotic and inefficient as the photo industry is today. Finding highly trafficked and particularly targeted sites was not only difficult, but they would change rapidly. It didn't make sense to invest dollars in an ad campaign for a website that may not remain well-indexed for the same keywords over time. In fact, most industry followers thought the internet would never be able to support a viable online advertising infrastructure -- neither buyers or publishers of ads were happy with results, and many predicted online ads would eventually just go away.

Google's novel approach was to use the same sort of auction-based system to redefine the advertising market. The "search" technology was the vehicle necessary to quantify the value of any given internet-based property; the business model underneath is to sell advertising based on the value of that real estate. Google also made a smart decision by not setting advertising rates, as was the custom back then; they merely provide a mechanism by which participants set market rates through auction. Different websites are valued differently based on their rankings for certain keywords, which can change a moment's notice. Rather than have advertisers pay to be on a particular page, they instead paid to be on whatever page was the most popular for a given keyword. As long as google's ranking is considered useful by both visitors and advertisers, market rates set by auction are deemed uniformly acceptable. And as long as the distribution of those advertising fees are considered equitable and competitive by the publishers who host the ads on their websites, the market is "efficient" and business is done.

By contrast, Yahoo's attempt at the same thing was inefficient, thereby less profitable. The lesson here is not just to create and participate in an efficient system, but to implement its various components properly.

How does this translate to stock photography? Can the same sort of model be replicated for photo licensing? It's not unrealistic, but it will require certain technological developments that, to date, no photo-centric company is willing to tackle. This is largely because the parameters that matter for photo licensing don't correlate directly to advertising, or to trading financial instruments like stocks. New parameters need to be established, and photo assets then need to be categorized automatically into those parameters. For example, "lifestyle", "sports", "travel", "artistic", "porn", "wildlife" and thousands of other top-level categories need to be devised.

I envision a sort of genome sequence tuned to photography attributes that can be applied to any photograph. Characteristics such as "black and white" and "empty space" and "vertical/horizontal" would be another set of parameters. And then there's a matter of a universal keyword architecture, which is another technology that doesn't have enough attention. (I've addressed that in the past, and will continue to do so in future articles.)

And then once these parameters are defined, an automated auction system can take them into account, and combine existing site ranking mechanisms to produce an infrastructure capable of supporting a market-maker system.

Will the photography world get around to these? Not unless anyone realizes the financial opportunity for it. But it is possible. After all, the fact that Google, being a heavily driven technology company, would build a business around advertising, a traditionally non-technical business (in fact, a culturally anti-tech industry), suggests that anything is possible.

The good news is that the need for an auction-based licensing system can be applied to other creative assets as well. There are already developments currently underway in some of the more basic levels. The first is a set of public registries that users can sign up for to store information about themselves, for example. The "iNames" project allows people to look up information about individuals, products or services, where you can make certain information about yourself public or private, depending on who's asking, and what's the use. Facebook and MySpace both employ similar-but-proprietary servers that allow developers to build applications build new businesses and websites that draw upon these information using data feeds.

In fact, the Orphan Works Act calls for the Copyright Office to create an openly accessible registry of registered works. Once the database is live, it's easy and quick to glue together a few simple protocols that exist today to create a mini stock-photo licensing system:

1. tineye.com, picscout.com, or xcavator.com can be fed a photo, either by upload or by reference from a URL.
2. The photo is then matched against images in the copyright database registry to determine who the owner is.
3. The owner's information is accessed through an iNames registry, where the user's preferences point to a license server for photo licensing.
4. The photo is then licensed through whatever agent is authorized to sell it to the buyer.
5. Payment is made and the user's commissions are wired to his account.

This all would take place as quickly as it currently takes to download a song from iTunes. If such a system were available, anyone and everyone would want to participate because it doesn't require any additional work. The only thing missing from this becoming a reality is the copyright database coming online. But that doesn't mean that other photo databases couldn't do the same sort of thing -- Flickr, for example.

Web 3.0: crowd-sourcing intelligence, not just content

In the above example, I assumed the person who wanted to license the photo already knew which one he wanted -- it was just a matter of licensing it properly. But a more challenging problem is finding the photo in the first place. This is where the Web 3.0 will be useful. To explain how that fits into this, I need to step back and review Web 2.0.

People associated the "Web 2.0" buzzword with "crowd-sourcing." That is, sites like Flickr, Facebook and MySpace are all social networks where people generate their own content and put them online. Revenue was generated because of the existence of this content; it attracts traffic, and traffic increases online advertising revenue.

What people aren't aware of, however, is that there is information being annotated to that content. Valuable information. People are doing things like rating songs, voting their tastes for things, and providing information on wiki websites. Currently, no one is leveraging that information for financial gain; they're just relying on its existence to attract visitors, which bolsters online ad pricing.

Web 3.0 is where that information's untapped value is released. Crowd-sourced content then becomes crowd-sourced intelligence. That is, information about information can be used to quantify value for that information to be monetized. For example, photos can be keyworded, classified, annotated, modified and otherwise "prepped" for a new form of monetization. As long as these user-driven behaviors are done within open-system protocols and development platforms -- and they will be, or people won't bother to use them -- then automated web robots can crawl these websites and begin to build hierarchies of this information that can be utilized by others in countless ways.

As for the photos in this system, they too can be found, filtered, and analyzed, which makes it perfect for a system that helps people find what they need and sell it to them. This then paves the way for market-makers to create an independent platform by which buyers and sellers of photo assets (or any other kind) can trade. By combining existing technological developments with search/query protocols, one can envision a search-ranking mechanism akin to google, but specifically engineered for licensed content (such as photos and video).

This may seem far-fetched, but there are billions of images online that have already been viewed, ranked, keyworded, and otherwise "prepped" for sale, yet are lying dormant because no one is laying the last mile of wire to connect it all up to a trading system.

Why and How Does the Pro Photographer Benefit?

Most pro photographers see the consumer as a threat, partly because they are large in numbers, but more because they are "cheap" in what they are willing to accept in pay. So, how and why would the pro benefit if there was an open system that embraced the consumer, rather than kept him out?

Simply put, the more level the playing field to everyone, the more likely it is that the better players will win. This is because like search engines that find the "best" matches for peoples' search queries, a future image-search-and-license environment will also feed photos that are considered "highest ranking" by data derived from millions of sources. In that environment, pros will invariably win over consumers.

By contrast, in today's environment, stock photo agencies either pick what a few individuals think are "the best results", or provide arbitrary search results. This is inefficient, wasting visitor's time, and benefiting no one -- especially the pro. Moreover, pricing is similarly arbitrary, which is also inefficient. In short, today's online stock industry does not provide a level playing field, meaning pros have an uphill battle to fight against the consumer, whose photos are "found" more often than pro's photos are. There are billions upon billions of them and no one is automating a ranking system, so the pro's photos lose due to overpopulation, chaos and randomness.

If an intelligent market-making ranking system were in place, pros are more likely to benefit not just because they are more likely to produce better content, but because they will go to extra efforts to include more useful/appropriate metadata and keyword info, and to position their images at properly targeted websites (whose ranking affects photo placement). Sure, consumers may do this, too, and some of those who do it well will be the "pros" of the next generation. Either way, buyers will invariably find and buy images produced by those who do better in this system, and pros are currently better equipped to get that running start.

Lastly, a market-maker model for selling images would expand the buyer base to include millions of more people than it does now, allowing pros to leverage the above benefits to an even greater degree. They would sell volumes more images not only to existing markets, but to new markets that never licensed photos before.

What should pro photographers do today?

The best thing for pros to do to prepare for the emerging landscape is to establish themselves using the same "search engine optimization" (SEO) techniques everyone else uses today. Create a domain name and populate the site with photos, and follow the well-accepted guidelines I discuss in an article I originally wrote back in 1999, here.

It is also important that photographers employ efficient workflow methods for how they manage their images and their metadata. I discuss this in the article, here.

Pro photographers' futures in stock photography will be highly dependent on how well they promote themselves today, not tomorrow. This is true, even if they join other stock agencies. Agencies don't promote photographers, photographers do. So photographers need to treat their photo businesses as if they weren't in a stock agency at all. (If the agency produces any revenue, think of it as a lucky bonus, not as a primary source of income.)

Summary

As photo suppliers, pro photographers are outnumbered by consumers by many orders of magnitude. As photo buyers, traditional media companies and others who buy stock photography are outnumbered by consumers, even though these sales are harder to see because they occur in such small per-unit sales. Either way you look at it, consumers are affecting everything about the photo business, especially at the pocketbook.

The best way for pros to strategize their future is to stop fighting the trends and to start adopting business practices that reflect modern economic principles. The first step in that direction is to always have the awareness that the consumer is there, both as a buyer and as a competitor.