Music videos, which comprise an important part of the video-streaming industry, are consistently the most-viewed content on streaming giants, such as YouTube and Vimeo. In exchange for free viewing, those channels serve advertisements for revenue. That business model creates a clumsy user experience, however, as a result of often-repeated ads that don't relate to the content.
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.
There are great digital asset management (DAM) products out there for uploading, storing, managing, organizing, and sharing digital assets. With Cloudinary's new end-to-end DAM solution, you can also upload and manage your assets efficiently, but the journey doesn't end there. It continues on to the development and delivery stages, so that your assets can be seamlessly manipulated, optimized, and delivered to create an engaging user experience that will in turn, increase conversion and loyalty.
Lack of experience and compression knowhow can cause significant user-experience problems. For instance, on a major retail site, I recently ran into a 48 MB video-hero banner. Pulling out the video and encoding it as an H.264 MP4 reduces the size to 1.9 MB. So, despite the desire for more video content, developers have not yet caught up to best practices. How do we get the best of both worlds without creating a disaster like the one above?
Developers are always looking for new and creative ways to deliver content that resonates with the way users feel. Often using the latest technical innovations the market has to offer such as Artificial Intelligence (AI) and Machine Learning (ML). What better way to demonstrate innovative uses of these technology in a consumer market than capturing expressions from your users and then serving content based on that expression!
As the number of channels and devices continues to grow, it is becoming much more challenging to deliver an optimal visual experience. On an eCommerce site, engagement and conversions are critical. Factors such as page load time strongly influence search engine rankings, shopping experiences, conversion rates and, ultimately, your revenue. An optimized visual experience positively affects conversion rates. But it also can introduce resource bottlenecks, as every image and video needs to be delivered in the most efficient format, quality and resolution, based on the viewing device.
React Native is a popular open source software that enables you build mobile applications easily with JavaScript. Other similar and popular options out there include Ionic, Lungo, Sencha Touch and NativeScript Vue. You can use your existing knowledge of HTML5, CSS and JavaScript to develop mobile applications without having to learn a different set of skills.
When you see the term boomerang, what is the first thing that comes to mind?
A thrown tool made of wood that returns to its thrower? Another definition is reversal, logically portraying the aim of the tool itself. Based on this definition, the term boomerang videos” came into play to depict videos that loop back and forth.
When the <video> HTML tag was first introduced in 2007, Web Hypertext Application Technology Working Group (WHATWG)(https://whatwg.org/) took interactivity with the Web to a whole new level. No longer do you have to tackle unique plug-ins or insert weird markups before posting videos online. Who still remembers the Flash days?
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.