Most photographers are focused on how much they can charge for their images. The higher the price the happier they are. This is true, not just of RM photographers who want to retain the ability to negotiate on every sale depending on the importance and significance of the usage. It is also true of Microstock photographers as their distributors continue to push up prices. (Check out
this story.)
But as the industry moves ahead it will become important to focus more on
Volume, and less on price. This doesn’t mean that sellers should continually lower the price in order to maximize volume. It does mean that sellers should focus on trying to find ways to determine the ideal price point where a combination of price and sales volume will
maximize revenue.
For example, it is possible to set the price for a usage at $800 as a way of showing the value the creator places on his work. The creator won’t allow anyone to use his images unless they pay his price. At this price the creator may make one, or no sales. Lets assume that the creator finds one customer willing to pay $800. But, there may have been 15 people willing to pay $80 or 40 willing to pay $40. In such cases the lower prices would generate more revenue.
Finding the right balance between volume and price is not easy. Unfortunately the right price varies for every image a photographer produces. But the balance, not just asking as much as you think someone might be willing to pay, is the key to maximizing revenue.
It has now become very common in the RM and traditional RF segment of the industry to set high list prices and then dramatically discount the prices for a large segment of the customers. See articles
here and
here.
This is the same thing that happens in many retail operations where there are list prices that nobody pays and everything is always on sale. But, in retail usually there aren’t as many variations in the product as there are in stock photography, or in the cost of producing the product.
Microstock has tried to avoid the negotiating process and constant variability by establishing fixed prices and sticking with them. Discounts are available to certain users based on volume, but the discounts are standard and transparent, not negotiated separately for each customer.
One way to make a high volume of sales is to charge almost nothing for each use. The trick is trying to find a higher price point where the higher price more than makes up for any loss in the number of sales. It is fairly easy to track sales of a collection, raise prices slightly over a period of them and determine how many sales you lose as a result of the lower price. But in any large collection there are images that certain customers would pay much more to use and others that customers might find too expensive at the new higher prices. The problem our industry faces is finding a way to identify the images that customers are willing to pay more to use, and those that can only be sold at a lower price.
Many of the microstock producers have tried to establish several different prices levels for different collections of images. That has worked to some degree, but they have tended to slot all the images of a particular creator, or a group of creators, into a single price category. Usually, while some of the images might merit the higher price, not all of them do. A few may sell well and generate good money at the higher price but because a huge percentage of the images are non-sellers the overall revenue generated from the collection may not be very impressive on a per image basis.
I recently did an analysis of a small segment of the iStockphoto’s Vetta and TAC collections that I believe illustrates the point. Using the slider that lets me sort for just Vetta and TAC images I searched for “People” and got 2772 returns which I organized by downloads. In the first 500 returns of the most licensed images there were very few photographs. Almost everything was illustration. Then I narrowed the search to just photos in the top priced group and got 1433 images. The top one had 100+ downloads. But we only have to drop to the 37th to find only 10+ downloads. The 121st had only 5 downloads, the 227th only 2, and the 565th and all below had no downloads at all. Thus, 60% of the “people” photos in TAC have never been downloaded.
In my judgment many of the photos that have never sold (and some that have only sold a few times) would have earned much more revenue if they had been available at a lower price.
In addition, many of the photos that have sold were posted on the iStock site before the Vetta and TAC collections were created. My guess is that many of the downloads recorded were actually licensed at the much lower Exclusive and Exclusive+ prices so they should not be counted as Vetta and TAC sales.
Is There A Fix?
Systems need to be developed that will enable sellers to determine the best price point for each individual image. If an image is doing well at a low price it might be moved to a slightly higher price, and over a period of time determine whether it will sell as well at the higher price. If it is not selling at a high price than after a period of time it would be wise to move it back to a lower price point.
Photographers must be willing to see their images moved in this way, particularly when they are moved to a lower price point. Such moves must be data driven and distributors must be willing to show data that would demonstrate that such moves are in the photographer’s best interest. Whether an image is exclusive or non-exclusive should have nothing to do with the price category in which it is slotted. It’s all about getting each image to the price point where it can earn the greatest revenue.
Photographers also need to also recognize that even if the ideal price point for each of their images is found, their collection may still not generate enough revenue to offset costs or show a reasonable profit. There is huge growth in the number of images available for customers to consider, and relatively flat demand. Regardless of where the price is set, sales may not generate the desired revenue.