If the blogs are any indication more and more Shutterstock contributors seem to be complaining about declining revenue. While individual royalties may not have been as high as some would have liked, for several years they were at least going up steadily month to month to month, or compared to the same month a year earlier. Within the last year or so an increasing number of contributors are complaining about revenue stagnation or decline.
Shutterstock’s overall revenue may still be growing steadily, but it’s not hard to see why long-time individual contributors are becoming very dissatisfied and unhappy.
Consider These Numbers
At the beginning of January 2013 there were about 35,000 contributors to the collection. Skip forward to the end of March 2015 and that number of contributors had more than doubled to over 78,000.
Meanwhile the number of images and video clips in the collection had jumped from 23.5 million to 54.2 million.
Downloads in Q1 2013 were 22.4 million of a total of 26 million images in the collection. In Q1 2015 there were 54.2 million images (a 108% increase), but downloads had only risen to 33.4 million (a 49% increase) for the quarter. The number of images available are increasing much faster than customer demand for images.
(It’s important to recognize that some images are downloaded many times, Thus the actual numbers of unique images that are never downloaded would be much higher. Nevertheless, the comparisons work.)
On the contributor side Shutterstock had 35,000 at the beginning of 2013. Fifteen months later at the end of March 2014 there was a 20,000 increase to over 55,000. In the next 12 months there was an additional 23,000 increase to over 78,000.
Shutterstock had $169.2 million in gross revenue in 2012 and $352.6 in the last 4 quarters ending in Q1 2015. Image creators received about 28% of these revenue or $47.4 million in 2012 and $98.7 million in the last 4 quarters.
On average each of the 35,000 creators would have received $1,354 for all of 2012, but in the last 4 quarters the 78,000 creators would have only received, on average, $1,265. Meanwhile most of the 35,000, at least, had been spending quite a bit of time, effort and money adding to the collection they already had with Shutterstock at the end of 2012.
Another way to look at this is that despite the fact that the average price per image rose from $2.30 at the end of 2012 to $2.87 at the end of Q1 2015 it didn’t make up for the declining percentage of images in the collection that were licensed.
From the individual photographer’s point of view there are two important numbers that lead to their gross earnings – (1) how many images can I get into the collection and (2) what is the percentage of images that are licensed.?
Based on Q4 2012 figures on average 92% of the images in the collection, or 920 out of 1,000 were licensed once during the year. (Of course, some were licensed many times and a significant percentage were never licensed, but this is an average.) Compare that to Q1 2015 when only 620 out of every 1,000 images were licensed.
Thus, images from the average photographer with 1,000 images in the collection would have earned $2,116 in Q4 2012 and $1,779.40 in Q1 2015, a 16% decline. The photographer’s royalty would have been about 28% of these numbers or $592 for Q4, 2012 and $498 for Q1 2015. Thus, the rising average price per image doesn’t make up for the loss in downloads per image in the collection.
It is also important to recognize that the average prices are based on revenue generated by subscription sales as well as the higher Image-on-Demand and Enterprise prices. Over 90% of the sales are low priced subscription sales where the contributor receives $0.25 to $0.38 per download. Many contributors make very few of the higher priced sales so their average gross revenue is often lower that the overall average for the company.
Go back 2 years, or a little more, and a very high percentage of submitted photos were approved, particularly when submitted by experienced photographers.
In the last year, at least, photographers are finding it increasingly difficult to get new images into the collection. A few years ago experienced photographers who had learned the ins and outs of the reviewing process were able to get 90% to 100% of the images they submitted accepted into the collection.
Now there seems to be wide variations day to day. One day a photographer may find that virtually all of the images submitted are accepted, but the next batch of images of the same general type of subject matter, processed in the same manner are almost totally rejected. There is no consistency. Often when the photographer submits these rejected images to other distributors they are immediately accepted and customers license them for use.
The issue for the image creator is not just about the effort involved in creating a new work. It’s about the work involved in getting the images where they can be seen by customers.
Jon Oringer said that in Q1 2015 they accepted about 5 million new images into the collection, but rejected about 3 million of those submitted. That is a 62% acceptance rate. For all of 2014 the acceptance rate was 58%. On www.microstockgroup.com
there are over 700 comments - many of them very extensive - from experienced contributors that detail how erratic and unpredictable the image reviewing process has become.
Added to the above problems the photographer must also consider the useful life of images. As collections get larger and larger useful life gets shorter. Here’s why.
It seems logical that any image search algorithm would employ some combination of new images
and best selling images
Unfortunately, there are a limited number of words that can be used to describe images. This is particularly true of the best selling subject matter. Sometimes it is possible to ad words that describe minor elements of an image, but then the image creator has to hope that the customer will think to use that word when searching. Often customers are reluctant to use very specific words for fear they will narrow their search too much. In such a case they could miss a good image that was keyworded more generically.
The end result is that in a large database most searches return thousands of images. This is many more than any customer is willing to review. Most customers are unwilling to look at more than a few hundred of the images returned in any search, before they pick one, change the search or go somewhere else. If an image is the 1000th, or lower, in a search return it might as well not exist for that customer because almost no one is going review that many images.
Hundreds of people are uploading new images of the most popular subjects every day. Many may not be as good, or useful, as images already in the collection, but they are likely to be shown near the top for a brief period of time. If they are not selected, almost immediately, they will get pushed down in favor of newer images. The more images added daily the shorter useful life is likely to be. Even images that are downloaded a few times will in a short time get pushed below the point that customers will review.
It is hard to conceive of a way to solve this problem other than non-biased human editing, but such editing costs money.
Thus, as collections get larger and larger this works to the disadvantage of image creators. It is not clear that larger and larger collections are even in the best interest of customers.