Keywording is a critical part of the stock photography upload process. It enables your images to be found when customers use the search capabilities of the microstock site.
The key to keywording is thinking like a designer. What types of keywords would a designer use to search for an image? What elements are part of the image that a designer would identify using keywords?
A designer may want an image with clouds or blue sky. The designer may want an image that is portrait rather than landscape. The designer may want an image with women vs men, old vs young, etc.
Effective keywords can help launch your image to the top of the results list if you are thorough in your keywording efforts.
Yuri Arcurs one of the top grossing microstock photographers in the industry has created a stock photography keyword tool that he makes available for free on his website.
The tool allows you as the submitter to type in keywords into the tool and then choose images that are similar to yours. By selecting similar images, you will be able to access a list of keywords that people are using in their searching process. The cool thing is that the keyword tool allows you to consider the popularity of the keywords in the list that is returned.
Selecting a mix of highly successful keywords along with a relatively large mix of not so popular keywords can help you significantly increase the income you can make from the sales of your stock photography images.
I think it’s a good idea, and what would be helpful would be the high-level, aoprppriate keywords for classification.As I’m working with my own pictures, I find I’m using words like: grasshopper, fair, flea market, Africa, Abstract, bird, bee, cat, dog, flowers, butterfly, dragonfly, spider, bug, forest, tree, leafs, waterfall, spring, street (for street shots), people, snow, ice, …These may or may not be the best choices, but they’re the first words that come to mind when I look at the picture. It’s all ad-hoc, though.Standards are wonderful: there are so many of them! Too bad they’re all different.I would need it to work in LightRoom 3 on a Mac (Lion); and it would be nice if I could realize (and retrofit with application to all images) that cat and dog were both members of the superset pets. It would be even better if, when I specified Cat, Pet was also added.I leave the implementation as an exercise for the student.