Have Your Stock Images Disappeared Into The Abyss?

Hundreds of thousands of images in major stock distributor collections are never viewed by any customer. If customers can’t see them they certainly can’t buy them. Is there a solution to this problem?

Tens of thousands of images are being added to stock photo databases every day. A very high percentage of them will quickly fall into an abyss never to be seen again.

Image creators are producing more images than anyone has time to look at. Take Shutterstock for example. Search for “woman computer office” and you get 81,943 returns. Or if you search on gettyimages.com for “couple walking beach” you’ll be given 4,778 returns (and the couple is standing still, not walking, in the first image shown).



We know that most customers never look beyond the first two or three pages (100 images per page that’s 300 images) of search returns before they either change their search parameters or go to another site. Nobody looks at the pictures that are at the bottom of the search return order. In most cases they don’t even look at the pictures that are in the middle of the pack. So what happens to them? They just sit there and take up space.

In effect, much of the imagery in image collections is never shown to a single customer. As collections grow the situation will get much worse.

Is There A Better Way

Distributors can track the images that are delivered for viewing by a customer. And in at least some cases they record and report the number of times an image is viewed. I would think it would also be possible to record the date when each viewing occurred.

Some images may get viewed a few times after initial uploading to a site, but depending on how quickly images with similar keywords are added to the database the image uploaded first falls into the category of those that never get viewed again. In some cases the image may have been licensed a few times and it may stay up higher longer, but as it gets older it tends to drop into obscurity unless it has been a dramatic best seller.



Agencies might want to take the images that haven’t been viewed, or viewed a very few times in a two or three year period and put them into a separate “B” database that could be offered to customers at a discount price. Customers looking to save money could search this database first. If they can’t find what they want then maybe they will have to go to the “A” database and pay a little higher price.

In this way at least some customers might have a chance to see image that are otherwise hidden from view. The agency might even sell a few or these and earn itself and image creator some money.

Is Discounting Everything A Better Solution?

The problem with the way things work now is that agencies tend to discount everything rather than just offering discounts on the images that haven’t been seen at all, or haven’t been seen for a long time.

Consider what’s happening at iStock when searching for “woman computer office.” If you search the discount collection (images produced by non-exclusive creators) the most downloaded image (6476620) has been downloaded >8400 times and had 84,335 views. The one-hundredth image (9596618) in this discounted collection has been downloaded >300 times with 4110 views. You can purchase either of these image for between 1 and 7 credits (each credit is about $1.50). Other images on the site, many of which have exhibited anywhere near the sales history of these images, can be purchased for between 10 and 160 credits.

But if you do a default Best Match search of the entire collection image 6476620 doesn’t even show up in the first 300 images and image 9596618 shows up in the 213th slot.  And, by the way, 9596618 is not in an office. Also, many of the pictures on the first page of Best Match have been downloaded fewer than 50 times.

I’m not saying they shouldn’t be showing new pictures that haven’t been licensed very often on the first pages of the search. But there shouldn’t be a need to dramatically discount very popular pictures that customers obviously want to use.

Discounts should be for images you have trouble selling, not for your best selling images.
By creating “discount stores” where an image not normally seen at the high-end store can be presented, there is a chance to make some money off that image. It may not be what the creator hoped he would get when the image was first uploaded, but it is better than nothing.

This strategy would also help to hold the line on the pricing of the images that are in good demand. The premium collection holds new image and images that have proven demand. That would make it possible to offer discounts to customers with budget issues without discounting the agency’s most sought-after images.

If an image is moved to the discount store and it starts selling well there is no reason why it shouldn’t be moved back up to a higher price level store.

For a company like iStock it might make sense to have two or three levels of discounts based on how new and popular certain images are rather than randomly slotting every image into a collection (and a price point) where it stays forever regardless of how well it sells.

It may make sense to initially slot images to a variety of price points. But moving them based on how well they sell, or don’t sell, makes more sense than leaving them in one collection forever. It also provides a better justification for why some images should cost more than others than the current arguments the industry makes for its pricing.