Why Artificial Intelligence is a Game Changer for Advertisers

An investment in televised ad placement and event sponsorship has always been at least somewhat risky for brands. Take the Super Bowl as an example. With over 100 million live viewers, it’s arguably one of the most powerful brand recognition opportunities available but at five million dollars per 30-second ad spot, unless ROI is proven, it’s still a risk.

The Super Bowl may be an extreme example, but the fact remains. Without access to valuable insights including impression and engagement metrics during live and on-demand viewing, there is a natural barrier to ad placement. And while A/B testing helps, it doesn’t replace the ability to see real-time metrics. Fortunately, Artificial Intelligence (AI) is changing that conversation as we adopt a radical shift in how we code.

A New Outlook on Measuring Advertising ROI

Software 2.0 is the new way to code; more abstract than executing a series of commands, it’s akin to neural networks. And this data collection method has significant advantages for aiding media outlets in predicting ROI for advertisers. For example, the ability to collect and associate speech and visual recognition data with viewer behavior is far more accurate when using Software 2.0 than anything we’ve seen to date.

“ONCE WE REACH A STAGE WHERE WE CAN MOVE PAST SAMPLE DATA TO REAL DATA (IN TERMS OF TRACKING AND TARGETING) IT WILL THROW UP HUGE OPPORTUNITIES FOR US TO GIVE PRETTY MUCH ANYTHING WE WANT TO THE ADVERTISER.”

Venkat Nettimi, Head – Strategy Insights and Data Analytics, Zee Entertainment

The Future: AI-Driven Event Advertising and Sponsorship

AI is disrupting just about every aspect of our lives including the amount and type of data that media outlets can pass along to prove ROI for advertisers. AI solutions now have the capability to quickly collect, tally, and report viewer engagement metrics for live streaming, highlight reels, and trailers. This makes AI a game changer in ROI conversations between media outlets, events, and the brands that advertise.

The Future: AI-Driven Contextual Ad Placement

Today’s contextual ads are a version of pay-per-click whereby banner ads display on web pages that are relevant to the content on the ad. For example if you advertise sandals on a travel website, ads will only show on pages or posts about beach getaways, not pages or posts pertaining to skiing – even when both topics reside on the same website. With AI, these contextual ads will be up-leveled to include the current linear platforms (websites) as well as non-linear platforms (traditional and online TV).

The potential of AI-driven contextual ad placement for non-linear applications is uncapped. Imagine the possibilities when brands pair ads to relevant characters within a show. One such example would be a shoe company targeting skateboarders by placing contextual ads only after scenes where Tony Hawk appears.

“INSTEAD OF ANTICIPATING WHAT THE CUSTOMER WANTS, AS WE DO TODAY, AI CAN HELP US DELIVER JUST THE “INGREDIENTS” OF THE CONTENT AND ALLOW CONSUMERS TO DICTATE THE NUANCES.”

Ujjyaini Mitra, Head of Data, ZEE5

AI for Impression and Engagement Tracking

Rather than simply counting and reporting each time an advertiser’s banner shows on the screen at an event, AI allows for the collection of all instances of a brand’s elements. Meaning when products, dominant colors, and logo or logo variations are viewed media outlets will know how many viewers were watching at that time as well as how many instances occurred. This information can then be delivered quickly, during events as well as when watching highlights on TV or OTT platforms.

Capabilities such as these allow AI to measure impressions and engagement in ways that was never possible before and allows media outlets and events to deliver significant metrics that help prove ROI such as:

  • Capturing visibility of brand and brand elements across different platforms; live streaming, highlight reels, and product placements
  • Measuring when the brand was significantly displayed and viewed vs. when only some brand elements or none were viewed
  • Reporting viewership metrics during significant brand visibility moments
  • Recommending the best contextual ads to place on non-linear (TV and OTT) platforms  

The ability to demonstrate ROI through customized metrics on advertising and sponsorship opportunities is a game changer for brands especially in this age where viewer experience is key. In addition, the fact that AI capabilities take much of the guesswork out of ad spends also improves as sales processes for media outlets.

For more information on how AthenasOwl leverages AI to improve viewer engagement, see what industry experts have to say: AI in Media: 6 Trends – A white paper on how AI will disrupt content creation, curation, and dissemination.

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