How A Smart Billboard Is Changing How Consumers Interact With Products

The holiday shopping season is in full swing. It’s the time of year when many children write letters to Santa Claus listing all the cool stuff they want to receive for being good all year.

But jolly old men in the North Pole aren’t the only ones with insights into what shoppers are most interested in buying. In the world of IoT, a new connected billboard may be able to tell what products shoppers are most likely to be interested in buying and pinpoint the best time to display a relevant ad for them.

Earlier this year, Clear Channel Outdoor America (CCOA) launched a new out-of-home marketing platform called RADAR in 11 major metropolitan areas. RADAR uses data analytics to review mobile data and more effectively target consumers based on their digital data and movements.

Since its debut, the program has since expanded to over 30 U.S. markets. PYMNTS recently spoke with Dan Levi, chief marketing officer for CCOA, about RADAR’s rollout. Levi explained how the program uses probabilistic data to reach consumers and how the program is changing consumers’ attitudes and behaviors.

It sees you when you’re walking; it knows what you like.

The RADAR program works by collecting data that analyzes people’s movements and uses an algorithm to determine when is the best time to target the right audience. Levi said it reviews the mobile data to gain understanding of how people move and share behaviors in the real world.

While the idea of walking past a digital billboard in Times Square or an airport that can read data from your cell phone might make some people uncomfortable, Levi emphasized that RADAR does not collect personal data from individuals. The RADAR system can only pull data from consumers who have agreed to allow their data to be read and does not read individual users’ data but broader patterns of behavior.

“Out-of-home is a one-to-many medium,” said Levi. “When an ad is on an out-of-home display, you’re reaching multiple people. And so, what we’re doing is saying, ‘Let’s look at how mobile data helps us understand the movement of multiple people in the real world. What do they do? Where do they go? What behaviors do they share?’”

For example, the system can analyze a device’s GPS location to determine if a user visited a Starbucks and infer that the device owner is a Starbucks patron. Based on this movement, the system can determine what other devices exhibit similar behavior and aggregate the data into an audience of consumers with shared behaviors. From there, it can analyze the group’s daily movement patterns and determine the likelihood of these users passing a Clear Channel billboard.

In a nutshell, Levi said the program looks at the movement patterns of mobile data users and overlays that against Clear Channel’s physical inventory to determine which billboards have the highest probabilities of reaching them during their daily routine.

“What it is [doing] is bringing efficiency,” said Levi. “Just like so many other media, you look at the composition of the audience and the behavior exhibited by that audience and make a decision if that advertising opportunity is the best way to reach people who exhibit that behavior.”

Impact of exposure

In addition to targeting the right consumers at the right time, RADAR traces the behaviors of consumers after they have been exposed to the ads. According to Levi, further analysis by CCOA revealed how consumer behaviors changed after exposure to RADAR’s targeted advertising.

For example, a review run for Burger King that analyzed user data after exposure to one of CCOA’s billboards found that users were 25 percent more likely to visit the fast-food chain. Another review for a domestic car company found exposure to the billboards led to a 15 percent increase in visitations to a dealership.

The data collected also allowed CCOA to push surveys to mobile device users who showed up at the dealerships. The surveys found that those users who were exposed to the billboard and visited the dealership had a greater likelihood of purchasing or leasing a vehicle.

“We’re able to provide more data to the clients for them to understand and unlock that value of out-of-home [advertising],” said Levi.

Improving the mobile ad experience

Levi also sees an opportunity for the RADAR program to improve the mobile retargeting experience and improve engagement.

“What we do is operate under a premise here of retargeting with mobile after someone has been exposed to an out-of-home ad drives a greater likelihood of engagement with the consumer than just pushing the mobile ad,” said Levi.

Bundling out-of-home ads with mobile ads is paying off, he said. Retargeting people who are exposed to an out-of-home ad with a mobile ad is leading to much higher click-through rates on the mobile ad.

“We think that makes logical sense,” he added. “If you see some random ad show up on your phone, it’s invading your phone; it’s getting in the way, and it’s an annoyance.”

However, Levi believes that consumers are more likely to respond positively to an ad on their mobile device if they have just been exposed to an effective out-of-home advertisement because it amplifies something they recently noticed.

“Seeing that same message show up on your device, it has a greater likelihood of resonating because it’s not the first time you’ve been exposed to it,” said Levi.

Building a better shopping experience through data

While RADAR is still in its early stages, Levi sees programs like it as an opportunity to improve connectivity and communication between devices by offering businesses the chance to realize the opportunity that can be found in a “data ecosystem.”

“Where we are today is [using] some very interesting experiments and applications of data and connected devices and beacons and other parts of this IoT ecosystem that are starting to create use cases and proof that there is value here,” said Levi.

As the data ecosystem evolves, Levi anticipates datasets will expand and connectivity will improve, which will ultimately offer greater insights into consumer behavior and improve their mobile device experience. This model is based on data that relies on his behavior and preferences, instead of pushing a random ad.

“If I can eventually get to the point where Starbucks knows that I buy my drink every morning at 7:30 a.m. and it’s typically an iced coffee with almond milk and I’m walking by my typical Starbucks and they can push me a message that says, ‘Today, it’s free’ or ‘Today, it’s $1 off,’ that’s kind of cool for me,” said Levi. “That’s where I’d like to see things get to.”

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Click here to download the December 2016 PYMNTS.com Internet of Things Tracker.

About The Tracker

The PYMNTS.com Internet of Things Tracker showcases companies that are leading the way in all aspects of the Internet of Things. Every month, the Tracker looks at what these companies are doing across the ecosystem and in several categories, including Personal, Home, Retail, Transportation, Wearable, Mobile, Infrastructure, Data and more.