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Friday, March 02, 2012

Market Efficiencies and Stock Photo Pricing

In my last blog post, Selling Stock: It's About Search Rank, Not Price, I argued that the price variability in the stock photo industry can be exploited by those who garner high search rankings. The rationale is that the direct and indirect cost (overhead) of finding an image so far exceeds typical license fees, that photo buyers are more indifferent to those license fees than sellers believe. Thus well-ranked photo sites would be able to command higher license fees, simply because they have first access to the buyer.

In fact, well-ranked photo websites are undermining their own profitability by lowering prices unnecessarily, mostly because they are following their perceived competitors, not because the customer is demanding lower prices. Their rationale would follow traditional economic theory under most market conditions, but therein lies the exception. The photo industry does not represent "normal economic conditions." Indeed, the photo industry represents a classic case of an "inefficient market."

Let me explain by starting with the definition of an "efficient market." It can be summarized as a market of buyers and sellers engaging under conditions where all information is available to parties on both sides of a transaction. (See this wikipedia link for extended definitions, examples, and citations.)

Examples of efficient markets are exchange-traded commodities like oil, orange juice and automobiles, among others. Here, producers of commodities make their wares generally available, and market-makers trade on this information. It is exceedingly difficult (if not impossible) to have inventory that the market is unaware of, or to purchase commodities without the broader market's awareness. These are the conditions that lead to the definition of an "efficient market."

While there will always be price volatility, it is almost entirely governed by predictions of how supply and demand might be affected by external events. The weather affects the price of Orange Juice; war and instability affects the price of oil; and a litany of factors affect the auto industry.

When it comes to image-licensing, most buyers and sellers do not have that much information about the "global" market of buyers or sellers, let alone access to conditions that can affect future supply and demand. This results in "market inefficiency," which results in price inconsistencies, precisely as predicted by economists. Therefore, prices vary from high to low across the spectrum, depending on the perception of the buyers in any given time/place. This is because they have limited and incomplete information about the global supply chain.

This also explains why people objected to my proposition from my prior article. They do not have access to "all information," and worse, they are unaware that their worldview is limited. That is, most pro photographers are under the illusion that the entire market of stock photos is monopolized by a small number of stock agencies.

Ironically, the other markets (non-agency buyers/sellers) don't see the other side either. These discrete and separate markets will, by definition, find different prices than buyers in other markets. Stock agencies will view one another as competitors and lower their prices, whereas websites that are unaware of stock agencies (or don't attempt to compete with them) will command higher prices.

To optimize prices and create an efficient market, the following would have to take place:

  • Stock agencies would have to expand to cover a larger proportion of the image-buying market. As my prior article advised, the way to do this is to partner (or merge) with photo-centric websites, whose proportion of global internet traffic is very high. This will allow "more information to be more universally available to a greater proportion of the buyers and sellers." This now leads to market efficiency.
  • Once the market became efficient, it could then be automated through predictive pricing algorithms, precisely the way Google automated online ad prices using an auction-based mechanism. No doubt this is not a simple algorithm, and it took years to evolve, requiring considerable data mining to determine optimal market pricing. But it was achieved to a point where it is now a highly viable (and mutually beneficial) economic model for buyers and sellers. The market of photo buying is similarly large, and there's enough economic activity that appropriate data-mining efforts could lead to similar algorithms for auction-based image license pricing.

The question is whether anyone is willing to invest enough into this untapped market.

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