Speed and growth. Two themes that publishers leveraging video really care about. In 2017, so far, publishers are using more sophisticated tools to measure, automate, and improve processes. In fact, using data and automation for video to drive larger, more engaged audiences and more effective monetization, is more important than ever.

However, buzzwords don’t push the needle. Driving video business in the real world comes with a host of challenges, and fragmented efforts often tamp down any real growth.

Consider this: Advertisers are spending on average more than $9 million annually for their brand’s digital video advertising, representing a 67% increase from 2 years ago, according to a recent study from the Interactive Advertising Bureau. Video also represents more than 50% of their digital/mobile ad spending.


Obviously, there’s a lot of money on the table. Here are a few important considerations when developing a holistic video strategy.


Optimizing Your Video Destination

Fast, mobile-responsive video sites are a must to maximize ad revenue. According to a recent Cisco study, 75% of all mobile traffic will be video. Many publishers’ video web pages are overloaded with display ads, social beacons, and other elements that slow page load times and responsiveness. The pages are often also not well optimized for mobile browsers. These problems create a frustrating user experience, which ultimately leads to high user abandonment rates and therefore lower ad revenue for the publisher.


It's All About Speed

Speed. Performance. The key to speed is understanding how to setup a video player for maximum performance, by building in things like HLS streaming, video preloading, chromeless players, and mobile UI. In fact, an Akamai Technologies study showed that beyond 2 seconds load time, every second increases user abandonment rate by 6%. Using a single HTML5 video player that renders quickly across devices can consistently deliver the best viewing experience, helping to reduce churn.

Machine Learning With Video Recommendations


Machine learning in video is driven by a neural network that understands, digests and learns intuitively through video images and metadata. A recommendations engine powered by auto-generating high-quality video encodes, previews, and metadata, can improve content discovery and ultimately lift. This keeps users watching longer, leading to increased engagement and revenue.

Analytics for Actionable Insights


Compelling insights into the video activity on any sized network, can help publishers make critical business decisions. Whether it’s quickly identifying trending content or friction points in media that are causing churn in viewer engagement, leveraging real time analytics will allow users to understand how content is performing across devices.

In 2017, the ability to measure, automate, and improve video processes will continue to improve as publishers and brands develop more results oriented approach to delivering high quality video. With a focus on optimization, machine learning, and analytics, expect video to represent an even greater percentage of advertisers digital/mobile ad spending.

Learn about on these subjects and many more at JW Insights 2017 in New York City on May 18. Register for the free event here. Network with your peers and meet JW product experts and developers at this lively annual event.