Since some agencies show the number of “views” to contributors, there regularly is a discussion about that number and it’s relevance. My usual answer is: That’s only something to keep you busy thinking but in reality doesn’t matter a lot. Okay, that was mostly a gut feeling, so I decided it’s time to have a closer look if I am right or not.
View counters at agencies
Many agencies have dropped showing too many stats and I honestly appreciate that. Stats were really important and fun when microstock was new and fresh, and people were mostly excited about how many people would look at their images. I know, many contributors still feel the same but from the few millions in revenue the agencies have grown into international companies with hundreds of millions in sales. Things got more professional, and so did (some) contributors. The longer I supply images into the market, the more I focus on the only really relevant number: How much money ends up in my bank account before the end of the month.
But in some places, those stats are still available. And as contributors are curious, they constantly argue if this or that might be important. The number of views seems to be of some relevance to many, “because only an image being viewed can also be sold eventually”. Well, in general this is obviously a true statement. However, the actual questions should be “will views automatically lead to downloads” and/or “can an image be successful in downloads without getting many views”.
Let’s have a look at three images I have at Fotolia/Adobe Stock:
Those are just three samples somewhere in my list of images sold through Fotolia/Adobe Stock. Can you make a guess how many downloads each of these three images had? Well, I’ll show you the answer at the end of the article.
But first, let’s look somewhere else: Dreamstime also shows the number of views. Looking at those, you will already find that different agencies have different ways of counting views. And we have no idea which of them counts what. Only that on Dreamstime “Views” tend to be much higher than on Fotolia.
Also, as you can already see, the images with the most views have almost no downloads at all. Honestly, I have no idea how exactly that happens but I somewhat assume that those images can be found easily through Google Images, people click on them only to find out they would have to pay to use them and go back to Google to find free ones.
The numbers on Fotolia at least look a bit more consistent but are much lower in general. So my assumption is that Fotolia only counts views on their website. And maybe even views of people who are logged in while not counting the random clicks coming in from search engines.
Statistical Correlation of views and sales
For a more scientific approach, I have decided to take a sample number of my images at Fotolia and put them into a spread sheet to find out the “correlation” between views and sales. Correlation is a statistical term that says “if event X happens, how likely is it that event Y also happens”.
An example: The hotter a day is, the more ice cream is being sold. In this case the correlation would be close to 1 because those two factors are clearly connected. On the other end, the hotter the days are, the fewer hot chocolates are being sold; this would be a negative correlation of close to -1 because also those numbers are closely related. Makes sense?
So the number for correlation can be between 1 (two events closely related) and -1 (strongly related but reverse). In between there is the 0. If two events have a correlation of 0, that means they are not related at all. A typical non-sense statement some of you might have heard from your parents: “If you don’t eat up, it will rain tomorrow.” I’d say it is save to assume that those two events are not related to each other at all, so their correlation would be very close to 0.
Now let’s have a look at this chart I have made from my Fotolia stats. Each dot represents one image, placed on the horizontal scale further to the right by the number of views and on the vertical scale by the number of downloads:
The straight line indicates the average, that statement would be “the more views an image has, the more downloads it gets”. But as you can easily see in the graph, the dots are spread out very far from that line. I have images with hundreds of view but almost no sales on the bottom right of that line, and other images with quite a lot of downloads with rather view sales on the upper left.
I calculated the correlation for these images and the result was: 0.47
Okay, this number basically says “there is some correlation between views and sales but it’s not very strong”. It would be similar to saying “in May day temperature in Berlin is mostly above 20°C” – yes, it does happen on a regular basis but often enough it does not.
How many downloads had those images at Fotolia/Adobe Stock?
So, now let’s go back to those three images I showed at the start. As you might already have guessed, I picked three images that have had the exact same number of downloads. Only that one of them had nine times more views than the other:
As you can also see, even considering the upload date there is no real connection between those number. One could argue that a “not so good image” gets seen more often over time (probably true) with people deciding against using it after having a close like. But even “time” is a not a huge factor apparently as you can see that even between the two images uploaded with two weeks of each other, the view number varies by a factor of five with the same number of downloads.
This might be an indication that one of the two images is being shown more often on the Fotolia websites with their localized search results while the other image might show (and sell) more often through Adobe Stock and over there the views are not counted.
But this is pure speculation. And that’s what this whole article basically is about: Drop the idea that counting the views will help you in any way to determine the success of an image. It isn’t something strongly related to sales and your earnings.