OpenText™ | Blogs
OpenText™ "OpenText Media Management uses intelligence to improve the marketer’s life one task at a time"
Marketers who use video grow revenue 49% faster than non-video users, according to Wordstream. But in today’s digital world, it’s not enough to simply use video – video must be easily searchable, discoverable, and embedded with video analytics to meet the needs of current day marketers. In this second post in a four-part series, I will be covering the strategic innovations for intelligence in OpenText™ Media Management (OTMM).
If you missed it, you can read about the importance of user experience in the enterprise in part one of my four-part series.
Intelligence in Media Management
In Media Management 16.3, we introduced the Rich Media Analysis service, which was the beginning of the powerful conduit to automate tagging and processing all that opaque content to make it searchable and useful for your users. Our interim releases added additional AI enhancements for OCR for text on images in 26 languages and identifying faces in images. We’ve continued that momentum in the OpenText Release 16 Enhancement Pack 5 (EP5) release with additional support for video.<
Video marketers get 66% more qualified leads per year
Processing Video Assets
Dealing with video is time-consuming and complex. Considering how effective video has proven to be for driving sales, marketing organizations are including more and more video in their mix increasing the need for that video to be quickly located, easily managed, prepared and distributed.
The new video insights will allow for rapid discovery of your videos. Think about what most marketers endure trying to find that perfect moment in a video that captures the essence of their product, service, or membership. Instead of watching endless amounts of video to find a scene where a specific person is speaking about the desired topic or an advertisement with a particular segment to reuse, marketers can use the new video insights tab to discover speech-to-text, visual text recognition (on-screen OCR), speakers, and extracted keywords, all based on a rolling timeline that can be played back in lock-step with the video. Users can now filter to find specific text spoken from the audio track.
do you want to know more?