With high-quality cameras becoming more accessible than ever, it’s harder than ever to make money out of photography. So how can photographers, image libraries, and content owners prosper in such tough times?
There’s a dilemma that’s all too common in photography and throughout the creative industries: To make money, your work needs to be popular and to be popular, it needs to be out there. But it can’t be out there if it’s not yet popular because many are not willing to pay for it.
So what’s the answer? How do you make money out of your images online?
Distribute them for free.
Sounds crazy, right? But bear with us.
The case of #FreeHawaiiPhoto
Canadian-born photographer Cath Simard took the below photo of a Hawaiian road in 2017, which subsequently went viral across social media and the wider web. The image was shared countless times around the world, largely without permission or attribution.
Simard spent a great deal of time and effort trying to track down every illegal usage of the image and retrospectively gain fair compensation. But with no way of knowing just how many copies of the file were out there, it was impossible for her to keep up.
Exasperated at how the current method of online image display creates an ecosystem that does little to protect the intellectual property of creators, she decided to take a different approach. She began the #FreeHawaiiPhoto campaign. Simard sold the image as a non-fungible token (NFT) and then immediately released it for commercial and non-commercial use, with no fee attached.
Read more: What is copyfraud? And what do NFTs have to do with it?
The theory was that by encouraging usage of the image, the resulting fame would add value to an authenticated original. You could think of it like a record sleeve that has been signed by the band that recorded it, a football shirt signed by the player who wore it, or indeed, a printed image signed by the photographer who took it.
And it worked; the NFT, released as a 1/1 edition, ended up being sold to a collector for the equivalent of $303,481.
How it challenges the current image-monetization model
While this case is very specific and completely unique in many ways, it raises broader questions about the way in which we have historically made money out of digital images.
With the democratization of photography and mainstream access to high-quality scanning hardware, countless images are either freely available online (both legally and illegally) or relatively easy to create with the average smartphone camera.
With photography facing such devaluation, and the prospect of tracking down and being paid for every online use extremely difficult, it begs the question: is the traditional restrictive image-licensing model obsolete? We believe it is. It’s time to be free from the threat of image theft and give your images the exposure they deserve.
This isn’t to say that you should send a high-resolution JPEG of your image to everyone on the internet and hope it gets popular. Rather, by using image-streaming technology to distribute it freely but securely, you can provide widespread access at maximum quality, while retaining complete control over where it appears.
This means that, as with the #FreeHawaiiPhoto case, the more your image is shared and the more times it is viewed, the more value could be added through its subsequent fame. However, the difference with image streaming is that shares do not mean duplications; all views are securely streamed from just one original online copy.
The money, of course, still has to come from somewhere – and that’s where in-image advertising comes into play.
The new image-monetization model
Image streaming works for images much like YouTube works for videos. As an image owner, you store all your high-resolution original files on one secure server and each of those images can then be published across the web using embed codes.
Once displayed, they are protected from theft through right-clicks and screenshots and they can appear with uneditable captions and dynamic watermarks. Users can also zoom in to view all the finest details without affecting page loading times, and it’s even possible to include call-to-action buttons that direct a viewer to your online shop.
This highly engaging user experience is perfectly complemented by in-image advertising, whereby contextually targeted ads are served within the image frames as they are streamed.
Using artificial intelligence (AI), the content of the image and the page on which it appears can be evaluated, and this can then be combined with the geolocation of the user. Using this data, ads that are completely relevant to the content a user is viewing can be served within the frames of these images. This avoids wasted impressions through poor ad placement and flawed retargeting.
Read more: The fascinating ways in which the biggest brands are using AI today
Revenue from advertising is, of course, paid to the content owner, but a proportion is also paid to the publisher. This means that publishers not only get to use an image for free, but they also get paid every time it is viewed, providing an incentive for them to share it as widely as possible.
The result is the best of all worlds: Maximum exposure with no loss of revenue, while maintaining complete control.
Image streaming is the future of digital publishing
This article began with a moneymaking dilemma and has ended with what we believe is the ideal monetization model for creators, owners, and publishers of digital images.
With 1bn hours of YouTube content being watched every day, it’s clear that streaming works – and with YouTube’s 2020 ad revenue totaling $19.77bn, the potential earnings are undeniable.
The idea of speculating to accumulate can be a hard one to justify for photographers, image libraries and other content owners in the current landscape. However, by using image streaming and in-image advertising, it’s possible to offer the incentive of payment for the publication of your images, without putting your hand in your pocket – and crucially, without making a single copy of the original image file.
Image streaming and in-image advertising make it possible to incentivize viral popularity with minimal security risks, while all the time getting paid. What’s not to like about that?
To learn more about SmartFrame’s innovative image-streaming technology and in-image advertising, explore the website or contact our team today.
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