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AWS Media Intelligence — Step 2: Monetization Insights

Published October 5, 2021

In an earlier blog post, we introduced you to Infinitive’s four-step media intelligence process and talked a little bit about the first step—gathering and tagging video assets. Once those assets are organized, companies can move on to the important second step, monetization insights. As a reminder, here are the four steps:

  • Content and Discovery: Migrates historical and new video assets the cloud, making them discoverable while laying the groundwork for your new revenue streams.
  • Monetization Insights: Utilizes AI/ML and logfile analysis to automate ad break recommendation and insertion to create monetization solutions. Our solution also identifies dollars left on the table from missed ad opportunities.
  • Content ROI Decisioning: Combines video asset analysis with monetization analysis to optimize future content and ad product decisions.
  • New Revenue Streams: Leverages the building blocks of the first three steps to increase consumer engagement, optimize ad inventory, and better personalize your content for consumers.

As a media company or content creator, your content is king. But are you making the most of that content and driving as much revenue as possible? Over years of working with large media organizations, Infinitive has seen how many companies inadvertently miss out on ad dollars, and our goal is to help you capture that revenue using AWS tools.

Ad break recommendations

Whether you’re uploading brand new content or pulling shows out of the archives to introduce them to new audiences, you now have the opportunity to insert ads. Today’s viewers are accustomed to tiered services where lower-cost levels include more ads and higher-cost levels include fewer or no ads. For content companies, however, multiple tiers means creating multiple iterations for each piece of content, some with few or no ads and some with many.

Having people sort through all pieces of content to choose ad insertion points would take a huge number of hours and increase costs. That’s where artificial intelligence and machine learning tools come in. AI/ML capabilities can identify where ads should go based on the number of ad breaks requested and make intelligent choices by looking at places where sound decreases or the screen fades to black. These choices can get accepted or modified by a person, but the time and energy necessary to complete this task is reduced multifold.

Missed ad opportunities

In 2020, viewers around the world consumed a staggering amount of content. Unfortunately, many content creators lost out on potential ad dollars during this time. In fact, one study showed that more than 40 percent of ads that could have been shown were not, which means companies missed out on that revenue. Sometimes an ad slot was identified and ready, but no ad was shown. Often, companies didn’t even know what happened.

Infinitive utilizes AWS analytics capabilities to figure out what went wrong and how to fix it. For example, log files are created every 10 minutes and provide extensive amounts of data. Using those log files and AWS QuickSight, Infinitive can help companies figure out how much ad revenue they’ve missed and why—whether it’s a sales issue, ad display error, or something else. Understanding the problem allows us to offer solutions.

Cloud storage shines here, as log files create massive amounts of data that must get analyzed quickly.

Infinitive can also act as your extended team when you don’t have the necessary personnel to work on increasing ad revenue. We build custom dashboards with AWS QuickSight to dig into your company’s specific questions, starting always with the same common question: How much money are you losing by leaving ad revenue on the table?

We’re passionate about helping companies make the most of their video content, and we’d love to talk to you about your most pressing needs. Email us today or reach out to our expert, Steve Malinchock, to get a conversation started.