The biggest difference between amateur photographers and professional photographers isn’t necessarily the talent and it doesn’t even have to be skill. It’s the expenses. For enthusiasts, the amounts that they spend on new lenses, on driving to locations and on buying props is the price they pay for entertainment. For professionals, those are outlays, investments that have to be recouped if they’re to continue paying out of their pocket. It’s a difference that’s been at the heart of the criticism laid against microstock photographers. The format can only pay, some have argued, if you don’t factor in the cost of production. A new statistics tool for microstock sites reminds even part-time photographers that when they’re looking to make money, costs should drive decisions and define shoots.
Created by Andrey Popov, a software engineer and semi-professional photographer, Microstock Analytics logs onto microstock sites and collects data that includes sales figures, file information and thumbnail images. Once the numbers have been crunched, users can display the results as graphs, comparing their sales across different platforms. At the moment, the system works with iStockPhoto, Dreamstime, Fotolia and Shutterstock, with more sites planned based on user demand. The service was launched at the end of May and is now being used by more than a hundred photographers. Pricing is based on usage: tracking up to 500 files is free but the price rises to $299.99 for a one-time unlimited license. The program works even with giant portfolios; during testing Popov was able to track 40,000 files and 4 million sales.
Choose Your Best Files
The ability to compare sales across multiple sites at one source is clearly one important benefit for non-exclusive contributors. Another is the ability to track trends. Microstock Analytics allows users to group together collections of images into sets in order to identify the subjects or models that are bringing in the greatest number of sales. They can then focus their efforts on the most valuable shoots and make sure that they’re only uploading the images most likely to sell, a particularly important decision when you’re producing more images than the upload limit allows you to offer.
“If you produce a lot of content every month and you’re not iStock-exclusive, you want to choose best files to upload there,” says Popov. “But that’s not easy to do because you need to analyze sales on several other sites.”
Being able to track over time as well as across platforms can also be surprisingly valuable. Popov had found that Shutterstock’s preference for new content generated more sales in the first week than the files produced later on a monthly basis. Because some of his old shoots that had sold well initially appeared to be generating little return after a year, Popov assumed that microstock images have a short shelf life and little value over the long term.
“I was afraid to invest any significant amount of money in photoshoots,” he recalls. “But when I actually got to see monthly graphs for those photoshoots I saw that they sell equally well even after one year. It would be really hard to see without software or would require enormous amount of time to calculate using spreadsheets.”
Using Microstock Analytics, he says, he was able to double his income every month for three consecutive months across each of the four sites.
That’s really the key benefit of Microstock Analytics: instead of guessing what buyers want to purchase, estimating how long a set of images will take to sell and which factors will influence sales, photographers can test different subjects and compositions, and track the results. The figures that come back, such as the longevity of a set of images, may be surprising.
Realizing that microstock images can be valuable even over the long term however, makes calculating the cost of producing them even more important. When you’re shooting like a professional and choosing shoots based on the revenues those images will produce (rather than on the kinds of images you’d enjoy creating) you need to be able to calculate the return on investment. Popov provides a simple example of choosing between two models, one of whom charges $100 and the other $200. The more expensive model is likely to generate higher sales but a professional would calculate whether the extra $100 really would be a profitable outlay.
Microstock Analytics’ most important statistics then may be its ROI number, the returns delivered for the investment in the images. The program provides two figures: the actual ROI, which is based on the total earnings earned by the files (or set of files) so far; and the estimated ROI, which is projected from Shutterstock’s first week of sales.
Estimating Costs Isn’t Easy
The problem though is that both those figures rely on the photographer’s own estimate of costs, and those expenses can be difficult to calculate. The model fee is only one aspect of the cost that goes into producing an image. Other costs are likely to include props, clothes for the models, gas, equipment and, of course, the time spent shooting the pictures as well as the additional time spent on location scouting, keywording and editing the files, and uploading them to the sites.
Producing an accurate estimate of those costs is going to be difficult. Time, in particular, is difficult to value especially for semi-professionals who are shooting at the weekend and in the evenings. But the fact that the software forces contributors to think about those figures and enter even an estimated amount to see how much their images are really worth can only be a good thing. It might not turn enthusiasts into professionals and it might not make them shoot like professional but it does make them think like professionals and that can only be a good thing for the contributor and for the industry as a whole.