For Stylight, a fashion and design retail search engine, uptime, performance and customer experience are key to the bottom line. With tens of thousands of new images being added to its site each week, and a very small development team, the company needed an efficient way to manage and manipulate images, so they could be viewed quickly and optimally on any device used by consumers in 16 countries. As one of the earliest users of Cloudinary, Stylight sees significant performance and financial benefits related to Cloudinary’s cutting-edge solution for image optimization and delivery on multiple content delivery networks (CDNs).
Automating the categorization of your images and videos can help democratize access to your organization's creative assets. Many teams throughout your organization have likely spent a lot of time and effort generating high-quality content, but it'd be all for naught if the content just ends up in some anonymous folder on somebody's hard drive or is randomly dropped into your cloud storage with no functional organizational strategy.
The value of categorizing all the images in your library cannot be underestimated. Besides the obvious advantage of making your image library searchable and displaying relevant content to your users based on their interests, you can also learn more about your users according to the content they upload, and find out what people care about and look for. However, when dealing with a large volume of images, manually categorizing the images would take up too much time and resources.
Due to significant growth of the web and improvements in network bandwidth, video is now a major source of information and entertainment shared over the internet. As a developer or asset manager, making corporate videos available for viewing, not to mention user-uploaded videos, means you also need a way to categorize them according to their content and make your video library searchable. Most systems end up organizing their video by metadata like the filename, or with user-generated tags (e.g., youtube). This sort of indexing method is subjective, inconsistent, time-consuming, incomplete and superficial.