Digital-out-of-home (DOOH) screens are an incredible marketing tool, helping advertisers tie ads to specific locations, deliver more creative campaigns, and most importantly, provide higher audience engagement in comparison to their traditional OOH counterparts.
Until recently, the weakness of DOOH has been the complexities surrounding programmatic trading of digital screen campaigns. In turn, this has limited marketers in exploring new options, in which unique ad experiences can be broadcast on large public DOOH screens alongside campaigns delivered on an individual’s personal device.
The first signs of promise are now appearing, with Asian media owners and buyers working together to explore how to quickly make it a reality.
The aim is to unify digital-out-of-home screens and private screens, so that ad campaigns—and measurement—can be truly screen-agnostic. But as with all things programmatic, there are some technicalities that the industry needs to iron out, especially with regards to measurement.
My measurement is your measurement
Measurement is relatively straightforward in the world of online advertising. Typically, one ad impression will most likely reach a single person. However, in the world of DOOH, a single screen is likely serving a single ad to a much larger pool of people at any given time. In a busy train station or shopping centre for example, it’s possible for hundreds of people to view one ad at any one time.
That’s why online advertising and the traditional out of home advertising ecosystem have always had different ways of counting impressions—and thus different units of charging. This is now being addressed with DOOH impressions being calculated by what is known as the ‘impression multiplier’, which determines the number of impressions that one ad play should count for. However, in order to get an accurate impression multiplier, accurate data must be collected on the viewing audience.
This data can be collected in many different ways, from cameras to sensors to ticket sales. Indeed, one of Rubicon Project’s partnerships with a leading out-of-home media company uses its image recognition technology to provide audience segmentation and verification measurement.
This is a great step forward, but for DOOH to scale programmatically and deliver marketers genuine multi-screen opportunities, it’s essential that as an industry, we figure out a way to count impressions in a unified and universally accepted way.
There are still hurdles. Selling DOOH programmatically is still a relatively new concept, and both media owners and buyers are continuing to explore ways to convince key decision-makers to take the leap.
Additionally, the existing DOOH tech infrastructure ecosystems of content management systems, exchanges, verification and attribution are not yet fully connected, and even getting a proof of concept trial up and running can be costly. In this environment, getting anyone to agree on a decision on long-term, industry-wide metrics can be a challenge. But it’s one we must rise together to meet.
Finding a solution
So how do we step up to solve this complex, industry-wide struggle? First of all, publishers and buyers must align on how they calculate and justify what a single effective viewer means when they’re standing in front of a DOOH screen. Clearly, it’s going to be different from an online viewer, and we need to start thinking in terms that make sense beyond the online world.
Publishers and buyers need to seek the highest quality, most measurable forms of data. Everyone from media owners to exchanges are currently working on their own version of what ‘measurable data’ looks like. In order for the entire ecosystem to run smoothly, we all need to agree what that looks like.
The ‘easy’ option would be to use real time camera capture for high-resolution face recognition in order to apply the IAB viewability standard. However, the privacy requirements and cost effectiveness mean that this may not be realistically feasible. Yet.
Another option in measuring effective viewership is to use multiple variables, including the average number of viewers in front of the screen in a given time and dwell time, to determine the probability of viewers looking at the screen. Logic suggests that the longer the dwell time, the higher the percentage of effective viewers, however, there is no consensus on the definite conversion of dwell time to effective viewer. So, at the moment, this measure is used as a rough estimation agreed between the seller and buyer, rather than as an industry-wide standard.
In Southeast Asia, DOOH pioneers have been using consistent and reliable measures, taking video at different times of the day on both weekdays and weekends to capture both the dwell time and the average number of people passing by a screen in that given time. This information then enables them to estimate the effective viewers, which is in turn is represented by an impression multiplier.
There is still work to be done on this front and of course we also need to find a digital identifier that works holistically across the entire customer journey. This means no matter where the customer is looking—be it on public or private screens, online or offline—we need to have a unified solution for how we identify them.
It’s clear that the technology to sell DOOH programmatically already exists in the Asian market, and is being successfully rolled out across many media channels. But in order to form a scalable, sustainable DOOH ecosystem, it’s time for everyone to begin to align. After all, the modern digital consumer isn’t tied down to one screen, and neither should the ways in which we display and measure ads.
Oliver Lau is APAC account director at Rubicon Project