Will Artificial Intelligence out-of-home billboards change the industry?
What if billboards and banners could tell which colours, pictures and words were getting the most attention, and could adapt accordingly to ‘self-optimise’ on their own?
One thing is certain, if consumers can find a way to avoid ads they will – from downloading ad blockers to paying to avoid them (Youtube?). Brands must find new ways to getting in front of the consumer and they’re turning to old-school billboards and video displays, thanks to new technologies.
The situation today
Traditional advertising has lost a lot of ground to online advertising and, despite electronic displays being present almost everywhere in our cities, it can’t compete with the precision and relevance from online advertisers.
Print, television and desktop viewership are down and media inside the home is fragmented. As a society, we are spending more time outside than ever.
Out-of-home used to be the last medium on every media planner’s list because marketers had no idea if it worked. The entire strategy was around brand awareness.
With artificial intelligence, their goal is changing. Marketers will start to shift from brand awareness to actually seeing sales from their OOH ads. Digital out-of-home advertising and AI should start to generate real revenue for advertisers.
The typical audience today is more sophisticated, expect brands to care more about them and demand more mindfulness from advertisers. They want ads to be more conversive than they are with a big data approach. AI technology can solve these pain points by helping marketers personalise content and make it more engaging.
Object recognition using AI is a relatively simple task nowadays. However, determining the mood displayed on the face of a person is a little more challenging and perhaps controversial in Europe (take GDPR, for example).
By detecting facial features, such as the eyes and mouth, and determining whether they are open or closed, AI can estimate whether the subject is happy, surprised, sad or angry. Moreover, it is also able to determine the gender of the person with an accuracy of over 85%, and even estimate their age to within six years of accuracy.
Imagine a billboard, and likely you think of a static picture with a slogan, or maybe a sort of revolving picture in a dynamic version. That’s old school billboards. Billboards can now pick up on essential cues that enable them to tailor responses to the people in front of them. These are smart billboards equipped with responsive abilities.
Want to get a smoker’s attention? Try a smart billboard that coughs. That’s what a responsive billboard designed to promote smoking-cessation products from a Swedish pharmacy did.
Billboards with sensors can also collect data on nearby foot traffic and even the sort of people to be found at any given location. Giving advertisers better insight into the results is ameliorating one of the medium’s longstanding weaknesses.
This kind of digital display doesn’t just respond to a single element (distance) but uses cameras and facial recognition abilities to identify gender, age, and even the expressions of the viewer. Mindful about privacy concerns, the new billboards will be designed not to store or share any of the camera images or the anonymised data interpreted from them.
“The marketing funnel has changed because of mobile. Out-of-home is no longer just about driving traffic to brick-and-mortar but can drive a specific action.” says Dan Levi, executive vice-president and chief marketing officer at Clear Channel Outdoor.
So how does it work?
We’re seeing the beginnings of a new era in advertisement powered by the application of technologies such as facial recognition, artificial intelligence, machine learning, voice technology, location data, and augmented reality.
From a technical point of view, a camera will capture images of people using a video camera mounted on a digital billboard. As people get closer, about one metre away in front of the camera, the system will simultaneously send data over a high-speed network to the recognition system – which can determine the age, gender, and emotions of a given person.
The recognition system will then tell the billboard which content to display for the recognised person. This all took place in about one-half of a second from the time the camera detected someone to the content selection. The content will be displayed for about 10 seconds.
The smart billboards of the future will combine algorithms with sensors for the environment, and start offering content to people based on not just age and gender, but the weather and local events as well. Beyond obvious tie-ins to the environment a bookstore, for example, could offer suggestions of books for adults, and younger children that work well for a cozy escape from the cold or to read while on the beach.
The same can be said for stores using video displays. Indeed, the storefront can be similar to the online homepage. The goal is also to understand where people come from, what they’re looking for, how to raise their interest, how to increase their basket size and how to make them come back. The way to do that is to offer experiences that consumers remember in addition to convenience.
With machine learning and computer vision, it is possible to understand everything we can about what happens in front of the displays – who is there, what they’re looking for, how they behave, how they respond and how they engage with the content.
This can be done in real time so retailers are able to personalise the content. Consumers can also purchase the product they see so as a result, a window advertisement becomes another powerful e-commerce platform.
For example, many retailers today are missing a way to offer compelling experiences that differentiate them from e-commerce (only a small percentage of shopping happens online, it is mostly offline).
Even Amazon is going offline now through initiatives like Amazon Go. Brick-and-mortars shouldn’t be too alarmed, but they must try to figure out how to leverage technology to make the offline experience better.
In the future, we might see a new war concerning premium locations for billboards. For instance, Netflix recently bought outright a string of billboards in Los Angeles to ensure access.
Hyper-targeting versus mass targeting
It is exciting to see the sort of data now being captured. Strategic locations or businesses like malls, health clubs or elevators have the ability to better understand what messages are received by the consumers and then target via mobile the same message or a sequential message, a product offering and provide nearest store location.
Still, hyper-targeting might not work for every brand. Indeed, reaching someone out of your very specific target zone is not necessarily a mistake. It is also a way to create brand awareness, generate word-of-mouth and build interest around your brand.
If you want to create a national campaign (perhaps about a society topic), you can’t do that if your message can only reach your core purchase intenders. You lose all of the benefits of reaching people outside of that bucket. This is a strength of out-of-home that was thought of as a weakness.
Marketers have always wanted to target very specific audiences through precise segmentation. These are demographic segments that are often based on location histories. For example, a store might want to target shoppers that frequent one of their competitors’ stores. This strategy uses location data history as the primary basis for defining the profile of a custom audience.
With so many ads competing for people’s attention, appealing visuals or a catchy slogan that assume one-size-fits-all audiences don’t necessarily draw people in. That’s why we will likely be seeing more innovations in billboard personalisation in the future.
Ads that adapt to users reactions could represent the future for engagement with out-of-home campaigns. With an AI writing its own copy, selecting effective imagery and adapting, what might this mean for the future of the advertising industry, and specifically the creative process? Furthermore, do we really want to live in a society where ads are more and more personalised?