I agree with the comments that Paul Melcher, Ray Laskowitz and Leslie Hughes made on “Defining the Long Tail.” Rather than focusing on Anderson theories, that article should have focused more on the power-law distribution curve, because it has some important things to teach those involved in the stock-photo industry.
Melcher is correct when he says: “The long tail (as Anderson defines it) is about inventory, not pricing.” However, I believe the power-law distribution curve also applies to the universe of potential customers and the value each receives from the use of an image.
Anderson’s theory is based on giving away things that are abundant in order to get customers’ attention and draw them back to buy scarce, unique and relatively controlled items. That does not work in stock photography, where there is no way to determine what is abundant and what is scarce in advance.
For example, when it comes to pictures of people using cell phones, everyone would have to agree that these are in abundance. However, if a customer needs a picture of a 25-year-old Latino woman using a cell phone, facing left, and with copy space on the right, that picture may be very scarce and hard to find. Scarcity or abundance is impossible to determine until you know specifically what the customer wants to buy.
The industry has proven that the strategy of giving certain images away to everyone for free, or for low prices, and charging higher prices for others doesn’t work. The image that a specific customer values most is often the one that is free or low-cost, rather than the one arbitrarily set aside as being scarce and unique. The “right” image may be scarce or abundant for every customer and every unique sale. Customers make such decisions based on what best fulfills their needs for a specific project. Price is one—but not the only—factor, because each product is different.
The power-law distribution curve is applicable when we categorize customers based on the value they receive from the use of an image. There are relatively few customers who use images for magazines, books, major corporate brochures or advertising, but they can justify paying much more to use an image than if it were going to be used in a PowerPoint presentation for a single meeting. Microstock has demonstrated that there are a huge number of customers whose planned uses are so insignificant that they can not afford to pay very much. If we look at all customers as a group, we have a classic power-law distribution curve.
So, do stock sellers set aside a certain group of images, making them available only to that small group of customers at the narrow top end of the curve and pricing them accordingly? This ignores a huge percentage of total buyers. Or do we make images available to everyone on the curve and price them so that anyone, anywhere on the curve, can afford them? With this strategy, the few customers who would gladly pay more receive a tremendous discount, and the industry as a whole loses money.
Consider that in 2008, Getty licensed rights to about 500,000 rights-managed images and perhaps 1 million royalty-free images. (This includes the images of the over 100 image partners represented on the Getty Web site.) At the same time, iStockphoto probably had 25 million downloads. In addition, total downloads for Shutterstock, Dreamstime and Fotolia combined likely exceeded iStock’s downloads during the same time period. If so, more than 50 million microstock images were downloaded in 2008, compared to 1.5 million for Getty and whatever the rest of the traditional rights-managed and royalty-free sellers generate.
Some of the 50 million microstock images were purchased by the same people that bought 1.5 million images from Getty. In some cases, the uses they made of the microstock image have had a much greater value for them than what they are asked to pay. Is it better to offer images for only 3% of all potential uses, because these command the most money? Or is it better to make images available to everyone and structure pricing so that the 3% of customers pay close to what they had traditionally paid, based on the value they place on the image, while the rest of the buyers pay prices they can afford?
In a power-law distribution curve, all traditional sellers’ customers will fall into the high-revenue portion of the curve. Some of them will also use microstock images, and the long-tail part of the graph belongs entirely to microstock sellers. Most traditional sellers do not know these people and are not even attempting to sell to them.
If the traditional rights-managed and royalty-free space, sellers want to protect their market. To try to expand it, they must begin to address the long tail. To do this, they need to:
1. Focus on building traffic.
2. Give something away (probably free images) to get the attention of new users.
3. Build communities and encourage communication with and among customers.
4. Start by offering very low prices and then figure out how customers intend to use the images and the level of the customers’ price sensitivity for each type of use. The initial goal should be to identify future customers and get the attention of a new group of users, not make a profit. As such, this activity should be viewed as part of a stock agency’s marketing budget.
5. Develop a system for learning how buyers intend to use images. Buyers have a variety of ways in which they use images and a different price tolerance for each use. Eventually, stock sellers will be able to set different prices for different types of uses, rather than being forced to rely on across-the-board price increases.
6. Find a way to maintain traditional prices when customers seek traditional uses and thus receive greater value than with the small uses many other customers contemplate.
7. Make the same images that are available at traditional prices available for small, narrowly defined uses at very low prices.