Deep Meta

As working wildlife photographers, we are always on the hunt for tools to make our lives easier. Sometimes this looks like equipment we will put to use in the field such as waders, snowshoes, new backpacks, and floating blinds (more on this in a future article). Other times, it’s workflow related - such as new features found in Lightroom like the game changing “select subject” option in the masking tool. And every once in a while, it has something to do with how we sell and license our photography.

Actually, this last statement is a little misleading. We are ALWAYS looking for new and improved ways to go about making money with our photographs. It’s just that things are, in many ways, still plodding along in the business of selling photographs much the way that have been for the last 15 years.

One of the biggest hurtles to making money with stock photography today is the time and tedium it takes to prepare a photograph for sale on stock agencies like Getty. You need a title, you need a detailed caption, you need not just relevant keywords, but keywords that Getty actually recognizes and accepts.

All of this can be done in a program like Lightroom, of course. Annalise and I talk quite a bit about the importance of flushing out all your important metadata in Lightroom for this reason. Doing a lot of the heavy lifting up front makes selling photographs easier down the road. But not all stock photography companies are the same when it comes to the metadata they prioritize.

Alamy and Getty and unquestionably the two largest stock photography agencies in the world. Getty is based in the US. Alamy is based in Europe. And I have written extensively about both these companies and why wildlife photographers need to be working with them in other articles here.

But what you must understand is that both companies handle and prioritize metadata differently.

Alamy gives photographers carte blanche to come up with and get exceedingly creative when it comes to keywords. Their captions / descriptions, on the other hand, is a completely different matter. This European stock photography giant puts very little emphasis on captions. Sure, captions are still important here. But they cap you at exactly 150 characters in your caption. In other words, with Alamy, you write a tweet about your photograph.

For those of us who are used to both the searchability and success of a photograph being predicated on the completeness and creativity of our captions, 150 characters is a tough pill to swallow. However, once you understand that you can recreate all the information you would have in your captions in the form of long-tailed keywords – or what is better understood as key phrases – then you can get down to the business of describing your photographs and helping buyers find your work.

Getty is completely different.

Getty puts a lot of priority on the caption, giving us photographers the freedom to add paragraphs of information to our photos if we so choose. Keywords, on the other hand, are a completely different matter.

Getty operates under a very selective library of keywords that it recognizes. This is so strict that at times I find myself having to submit formal requests to have species name added to the list so I can properly tag the photograph. All of this means that when you sit down and start writing out a logical list of keywords for your photographs, chances are Getty will not recognize 95% of them.

Traditionally, to learn what is and is not excepted by Getty for a given photograph, you had to go through the entire process of uploading and submitting photographs to their system. This was a tremendous bottleneck for many photographers. It was painstakingly slow and tedious. And in all honesty, if given the choice between a colonoscopy and submitting 100 images to Getty, I probably would have chosen the colonoscopy.

But now things are different thanks to the roll out of a new program called Deep Meta.

To be fair, this has been around for a while now. I was just late to the party!

No, this has nothing to do with the company formally known as Facebook.

Deep Meta is a standalone software program that Getty released to make the entire process of submitting images to them significantly easier. And after several weeks of doing a deep dive into Deep Meta, I can assure you that this is game changing.

When you first pull up the program, the whole thing can be as intuitive as sitting down to Adobe Photoshop or Premier Pro for the first time. But have no fear. Getty realized this and put together a proper website to help us creative types navigate this software that feels like it was designed for accountants at first.

In a nutshell, Deep Meta allows us to create batches of images to upload, fill in all the metadata based upon Getty’s specs, and then upload directly to the contributor portal. Yes, all this still takes time to do. But the layout, the functionality of it, and the fact that I can do all of this on my own terms anytime I want without having to login to Getty, makes a big difference.

Deep Meta still requires us to do all the things: title, captions, copyright notice, and keywords. But I don’t have to be online to do this AND the whole platform is infinitely easier to use, AND the program suggests keywords for your images like never before.

In the past, I would struggle to pull together 10 relevant keywords that Getty would actually recognize.

It’s important to understand what this means though. When us wildlife photographers sit down to Lightroom or Photo Mechanic, we tend to think logically about our keywords. The problem though is that logical and descriptive keywords only go so far when it comes to people finding our photographs.

Me, I come from a natural history photography background. Working with the BBC Natural History Unit, National Geographic, Wyoming Wildlife, Ranger Rick, etc., this set me up for thinking very directly about my photographs. Is it a photo of a brown bear on the edge of Cook Inlet, Alaska, with a coho salmon in her mouth? My keywords are going to look like: brown bear, Alaska, Cook Inlet, coho salmon.

The problem with this, however, is that such keywords will only get you as far as natural history magazines.

That photo of a bear might be purchased by Alaska Magazine, or maybe the Journal Nature to illustrate a new scientific finding about brown bears. But other sales to other media outlets will be harder to come by this way.

When we keyword our images, we need to think beyond such straightforward descriptions. Although all of us want magazines like National Geographic to pick up our images – and yes, they do absolutely buy my work through a variety of channels including Getty – it’s the 100,000 other ways in which wildlife photographs get purchased that make up the bulk of the income one can make through selling stock photography. This means that in addition to logical keywords like bear and salmon, we also have to think broader and more conceptual. It’s these types of keywords that have always been challenging for me to come up with. Sure, I have a document of compiled keywords I can plug in when needed, but I have no way of knowing if there is even any relevancy to these in the market.

This is where Deep Meta comes into play.

Now, some images have significant “stock” appeal. These photographs are MUCH easier to think conceptually about. But unless you are a seasoned stock photographer already, it takes time to learn the ropes in the market to get an idea for what sort of images make great salable stock images.

So, for the sake of this article, I decided to work through the process with an image that is decidedly not “super-stocky” so you get a feel for how this works and how this program will help you if you sell images on Getty.

I will let you do your own homework on the basic functionality of Deep Meta. Things like how to create a batch and add photos to that batch are simple enough to figure out or otherwise use Deep Meta’s tutorials to handle. Once you have the files loaded however, simply click on a photograph to pull up a new window that contains all the metadata fields.

And to be clear, metadata is not the same as your EXIF data such as exposure values and pixel dimension. Instead, this is the descriptive stuff such as titles, keywords, captions, copyright information, etc.

The photograph in question here is of a species of shorebird known as a marbled godwit, flying with a few other non-descript shorebirds in the background. I photographed this at f/2.8. The depth of field is extremely shallow, and all you get here, other than the godwit, are some muted blues and tans of the background along with the out of focus birds in flight back there.

First thing’s first here, we need a title and caption for this photograph.

Title: Marbled godwit flying with flock of shorebirds

Yes, this is about as generic as it can be. However, this title is keyword rich and that’s all that matters to me here. We aren’t selling fine art here, trying to capture the hearts and minds of people with our words to sell our photographs (more on this to come in another article). Instead, when we fill out the metadata on our images, we need to think like a search engine. Keywords, keywords, keywords. But not just in the place of the keywords themselves. Every word you associate with a photograph’s metadata ultimately gets used as a keyword on Getty and Google.

So, “Marbled godwit flying with a flock of shorebirds” contains keywords such as: marbled godwit, flying, flock, and shorebirds.

Perfect.

Next comes the description / caption.

Captions should generally contain the basics of journalism: who, what, where, when, why, and how.

All of these are not always relevant, of course. But if we can add them to the caption, then we will be better off for it in the long run. So, I added the following as the caption to this photograph. . .

“A marbled godwit (Limosa fedoa), flies with a mixed flock of other shorebirds up the coast of the Gulf of Mexico during the spring migration near the Tampa Bay estuary.”

Who: marbled godwit.

What: flying with a mixed flock of shorebirds

Where: coast of Gulf of Mexico near Tampa Bay

When: during spring migration

These are the basics.

Keywords gleamed from this area: Limosa fedoa, mixed flock, coast, Gulf of Mexico, spring, migration, Tampa Bay, estuary.

I can go further, of course. In a recent article about captions, I suggested that you flush out a full paragraph of details with your captions because it helps to increase the salability of your photos. For this reason, when captioning for Getty or my own PhotoShelter stock library, I would then add something like this:

“Although these birds are typically seen along the coastline from the Gulf of Mexico to the Outer Banks, marbled godwits are only using these coastal areas during the winter and migration. Instead, marbled godwits nest in the short grass prairie near wetlands across the prairie potholes region of North America that was created at the end of the ice age in places like Alberta, Saskatchewan, Manitoba, the Dakotas, and Montana.”

While the first sentence gave us the who, what, where, and when of the situation, this second part becomes a gold mine of keywords. Looking over the additional couple sentences, we find the following keywords to help with searchability: Outer Banks, coastal, winter, migration, short grass prairie, prairie potholes, wetlands, North America, ice age, Alberta, Saskatchewan, Manitoba, the Dakotas, Montana.

None of this is just filler. All these words are relevant to this species, even though it may not be relevant to the photograph itself. And for this reason, the photo of the marbled godwit may in fact be relevant for anyone doing a search for any of these keywords.

Even though we have yet to enter the first keyword into Getty, Deep Meta has already begun mining our title and caption for potential keyword matches for us to add. To find these suggestions we need only look under Keywords > Refine.

Here, you will find two lists. One has all your “valid keywords” you have selected. The other has the suggestions, which are divided into three lists you can toggle between. And as you can see, despite not adding a single keyword to the photograph, Deep Meta came up with 27 relevant keywords for this photograph. All I had to do was select them.

As if this part was not exciting enough, Deep Meta goes one step further to show stars on each one of the keyword suggestions.

These stars represent how often people search for these individual keywords. No stars mean very few searches for these keywords happen. Meanwhile, 5 stars means that these keywords are in high demand based upon people’s search terms. The fact that we have this information at our fingertips is game changing. I don’t know about you, but I want my photos coming up as a relevant image for what folks are searching for.

When we look at the keyword ratings, we find that the logical and descriptive keywords have very low values. The term “marbled godwit,” while explaining exactly whats in the photograph, only contains 1 star. The keyword “animal migration,” contains only two stars. However, the term “no people” holds 5 stars.

Of course, if I know this because of using Deep Meta, that means everyone using this software knows this as well and are absolutely plugging in the key phrase “no people” with their no people photographs. All of this dilutes the pot, of course. More images coming up with the exact same terms means less of a chance for you to sell your photograph with those terms.

This is why the entire process of filling out the metadata is so important, however. The more you put into your captions and keywords, the more you will get out of this. Remember, companies like Getty are not exclusively representing the world’s best wildlife photographers. Instead, you have millions of photographers from around the world who are contributing here and the more detailed we get, the more likely our images become the cream that rises to the top.

While there may be a lot of photographs of “shorebirds” or “marbled godwits,” savvy editors and art buyers who need these photographs are going to do searches for things like: “marbled godwit flying migration no people.” To do a more generic search means that maybe they get photos of marbled godwit eggs, of researchers banding marbled godwits, of these birds standing around on the beach, and inevitably of something that has nothing to do with marbled godwits such as a ring billed gull – the term “seagull” is a “valid keyword” in Getty even though there is no such thing as a seagull for instance – marbles, religious photographs (god is in godwit), and a photograph of someone’s 3 year old with birthday cake all over their face (welcome to Getty).

Deep Meta has completely changed my workflow just within the few weeks that I have been experimenting with it.

Annalise and I just returned from a couple weeks of scouting for and photographing black bears in the boreal forest of northern Minnesota. Each morning began well before dawn. We would break for lunch. And then be back at it again until sunset.

As soon as I came in from the field in the morning, I would begin downloading / importing my photos into Lightroom. While I ate lunch, I would cull through anywhere a thousand images or so and whittle things down to a small handful of photographs. Images I wanted to keep or at least take a second look at received 1 star in Lightroom. Those images that instantly jumped out at me received a 5 star. All the other photographs were deleted.

From here, I would do a quick edit on the 5-star photographs from the morning and begin filling in basic metadata. Once done, I imported the photographs into Deep Meta and began flushing out all the important stuff there. Which, thanks to this feature rich program, I was able to do in 1/100th of the amount of time as before.

All said and done, I had images from the morning culled through, 5-star photographs edited, and a batch of photographs uploaded to Getty for sale before it was time to head out for the afternoon.

Talk about a well-oiled machine!

Until now, the biggest barrier to dealing with large stock photography agencies has been the metadata and submission process. I don’t have the luxury of fiddling around in the office with images over the course of weeks after a shoot. More often, I find myself with only a few short days downtime. In fact, after 14 days of being in the middle of nowhere, just a stone’s throw from the Canadian border, we are now held up in an Airbnb for a few days before flying out to Alaska for three weeks.

When you work in this sort of breakneck schedule at times, efficiency and ease of use become prioritized above most other things.

And it’s from this need to prioritize that my personal workflow has developed and evolved. From moving over to Lightroom from Photoshop, to keeping my library of images accessible by me and hundreds of editors in the cloud, to the implementation of programs like Deep Meta. All of these things, and there are many more, developed out of necessity.

If you are someone who is considering selling images through Getty or iStock, or have already been doing so, then this is a program you MUST check out.