2017: The Year Yield Optimization Comes of Age in Digital Out-of-Home

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Cover image for  article: 2017: The Year Yield Optimization Comes of Age in Digital Out-of-Home

We are seeing the digitization of out-of-home advertising occurring at a feverish clip. This is fomenting wider and more precise use of targeting, addressability, location data, visual detection data, video display, interactivity and attribution, programmatic and more (see our December 15, 2016 column).  And this, of course, is leading to unprecedented double digit ad revenue growth projected for 2017. But possibly the single biggest development of 2017 -- and certainly one of the most exciting -- will be the use of location-based screens to take yield optimization to a whole new level.

Yield optimization essentially refers to the use of data analysis and optimization techniques to maximize performance and revenue. Think airlines and hotels. When a plane departs with empty seats or a night passes with vacant hotel rooms, those revenue-generating opportunities are gone forever. And so airlines and hoteliers have become quite sophisticated in the discipline of yield optimization, which helps them understand how to promote and dynamically price their seats and rooms to achieve as close to 100% capacity as possible.

For digital out of home (DOOH) media sellers, yield optimization to date has primarily been in the form of inventory management. But now the big, exciting opportunity is to take yield optimization to a more targeted level by using visual recognition and location targeting.

I recently chatted with two experts in the field:  Rodolfo Saccoman, CEO and Co-Founder of AdMobilize, and Andreas Soupliotis, Founder and CEO of Ayuda. AdMobilize is a machine intelligence company that connects the physical world to the online grid by utilizing pioneering computer vision and artificial intelligence (AI) technology. Ayuda is a supply-side platform that is used by media owners worldwide to manage day-to-day operations.

Saccoman says that yield optimization "is a big opportunity that can generate more revenue" for DOOH networks and more precision for advertisers.

"Ads have historically been sold at static prices depending on daypart and location," he says. "It's been very basic. But what we can now do is to serve ads on location-based screens using mobile data and a knowledge of who is actually looking at the screen at any given time. We can determine who is viewing by demographic and their emotion while looking and how long they are viewing. Sellers can start charging premiums for different ads. Coke, for example, could target a specific demo and trigger DOOH ads to reach that group."

This example refers of course to up-close, street-level viewing engagement in places like shopping malls, health clubs, restaurants and the like. But here's the thing: The same targeting and dynamic pricing (i.e., yield optimization) can be deployed for large-format screens like those alongside highways. Saccoman says that technology can now determine the speed of passing cars, so that specific spots can be served (and dynamically priced) in real-time. So, a longer spot or one whose creative requires a bit more attention can run -- at a premium rate -- specifically when drivers are in slow-moving traffic and thus have a longer exposure time to the screen.

Ayuda's Soupliotis says that sophisticated inventory and pricing optimization algorithms, not dissimilar to yield management techniques commonly used by the airline industry, are a key element of the secret sauce that makes this all possible.

Soupliotis says, "We've incorporated such algorithms into the ad serving platform which understands, in real-time, what is the best version of a creative to play based on external factors such as traffic speed. What are the best screens to activate based on real-time availability and data from massive mobile geotemporal data sets? And finally, when are the best times of the day to activate these screens in order to optimize and pace an impression delivery goal against a custom audience? The ad server further maximizes yield for the seller by analyzing historic fill rates on screens, demand and even lease payout terms to deliver the most profitable campaign for the seller while delivering on location-based targeting criteria for the buyer."

So DOOH screens can now feel and adapt intelligently to real world events such as unpredictable consumer macro-movement pattern changes, weather, traffic speeds, etc. Think about how weather satellite imagery helps visualize a developing storm. Heat maps can visualize how a custom audience's movements evolve -- such as consumers who have visited a QSR three times in the last month and their daily commutes. Ad servers activate the best screens as animated by the heat map. They choose the screen when they are in the eye of the storm. It's all about activating location-based DOOH media along a custom audience's journey and their path to purchase, while optimizing the seller's yield.

These are not futuristic dreams. These new categories of yield-optimized campaigns backed by real-time ad serving, data and sensors are commonly executed by companies such as Ayuda and AdMobilize. The yield optimization of the Internet is now available on location-based screens.

As the Marriotts, Hiltons and United Airlines of the world have learned, yield optimization drives millions of dollars in incremental revenue right to the bottom line. In 2017, the DOOH industry will begin to see similar benefits.

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