Parasoft is showcasing its latest product innovations at embedded world Exhibition, booth 4-318, including new GenAI integration with Microsoft Visual Studio Code (VS Code) to optimize test automation of safety-critical applications while reducing development time, cost, and risk.
The significance of video in driving engagement, building brand loyalty, increasing online sales, and delivering substantial ROI is widely acknowledged. A recent survey of web developers, marketers, and business leaders revealed that a staggering 81% foresee a strong likelihood of integrating more video content across their websites and mobile apps in the future.
Similarly, 78% of respondents emphasized the importance of video in building trust and confidence, with 65% leveraging it to boost market awareness, and 54% recognizing its impact on driving purchases. It's evident that brands see value in prioritizing video in their digital strategies. However, capitalizing on video content at scale presents a significant operational challenge, particularly for technical teams.
Let's explore the primary challenges related to video and then take a look at how you can best address them.
Top 3 Reasons Brands Struggle to Scale Video
The survey found that most brands face three primary challenges to implementing a successful video strategy at scale:
1. Producing variants is harder than creating an original. Creating video variants for different channels and devices is challenging, with 58% reporting bottlenecks in this area. Additionally, 24% face prolonged delays in video publishing, impacting their ability to reach audiences in a timely manner.
2. Varying formats and asset quality. Brands working with creative partners encounter challenges such as supporting multiple file formats (45%), obtaining optimized files for web and mobile (41%), and experiencing delays in asset delivery (38%).
3. Inefficient collaboration. Effective collaboration between creative and development teams is essential for accelerating time to market and ensuring seamless video delivery. However, many brands struggle with post-production inefficiencies, particularly in managing requests and feedback (46%) and lacking knowledge of technical best practices (33%).
5 Ways to Simplify Video Workflows
To overcome these challenges and ensure a significant ROI on both the investment in video and developer time, consider automating the various important but mundane tasks your developers are currently responsible for. The following automations are some of my favorites for streamlining video workflows, from creation to delivery, so that you can free your teams up to focus on more rewarding tasks:
1. AI Video Summarizations and Previews: Creating shorter, summarized versions of longer videos is an excellent strategy to drive traffic to the full content on your website or to create engaging teasers for social media. It's also very time-consuming. Various AI tools can automatically and reliably produce summaries or previews by selecting the most engaging parts of the original video based on your requirements for length and number of segments to include.
2. Dynamic Overlays. Automating the application of overlays such as logos and text eliminates the need for manual editing. AI-powered tools can intelligently detect where overlays should be placed within the video and apply them automatically, saving time and ensuring a consistent branding experience across all videos.
3. Smart Cropping. Automation streamlines the process of cropping and resizing videos for different screen sizes. AI algorithms can intelligently identify key elements within the video and automatically adjust the frame to optimize viewing on mobile devices. This eliminates the need for manual cropping, saving time and ensuring consistency across platforms.
4. Dynamic Video Transcoding. Instead of manually converting each video to different formats and resolutions, AI-powered tools can handle this task swiftly and accurately, ensuring optimal playback across various devices. This not only improves efficiency but also reduces the risk of human error.
5. Adaptive Bitrate Streaming (ABR). By automating bitrate streaming, you can deliver videos instantly without requiring manual intervention. AI algorithms can dynamically adjust the bitrate based on network conditions and device capabilities, ensuring smooth playback and eliminating buffering issues. This automation allows for seamless video delivery, enhancing the viewing experience for users.
DAM: Time to Go Headless?
To solve the third pain point of inefficient collaboration, lots of companies turn to digital asset management (DAM) solutions to serve as a single source of truth for all assets. They provide both technical and non-technical users with the automations listed above, while offering features such as creative collaboration, review and approval and other workflow automations that streamline the production process.
For example, you might find AI-powered features such as automatic video tagging makes asset curation significantly faster and simpler. Consistent tagging empowers users, including marketers, to better search and find the perfect video for their campaigns. They can also rely on AI-powered moderation to automatically evaluate and leverage user generated videos at greater scale.
Critically, these efficiency gains require seamless integration with other business systems such as the CMS, e-commerce platform, and others — which is where "headless" DAMs prove valuable. They separate the front-end from the backend and use APIs that enable you to customize the system to your specific needs. While enabling a UI for non-technical users, they provide the flexibility for you to work with the tools and frameworks that best suit your unique project requirements. They also make it easier to scale up or adopt new technologies as your business conditions evolve, without having to overhaul the entire system.
Take Advantage of Video's Power
As the survey findings make abundantly clear, videos are incredibly valuable for engaging audiences, fostering brand loyalty and driving sales. Until now, the amount of time and resources required to manage and deliver these assets has been overwhelming and put pressure on developer teams to keep up with growing business and market demands. But with the emergence of AI, everything can be managed far more efficiently. You just need to know where to look.
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