In the advertising industry, wherever you look, whoever you talk to, it’s all about data. And it makes sense because we need data to advertise more effectively and more efficiently. (D)OOH has been suffering in this area, but many organizations and companies around the world try to connect data - especially audience data to this medium. Though, there are still some challenges. And in this paper, we analyze those challenges in 4 main sections: 1- Data source 2- Data quality 3- Lack of universal tracking technology 4- Lack of real-time insight ----- 1- Data Sources Let’s start with the most important one; where are we collecting data from? Depending on the type of data, this source can change. If it’s weather data, it can come from sources like OpenWeatherMap.org. If it’s traffic data, it can come from sources like Here.com. There are many data sources out there that can provide all kinds of information needed to make the campaign more interesting. But when it comes to the audience data, especially audience-location data, things get a little more complicated. This data is mainly retrieved from 2 sources: Mobile apps (direct integration and/or bidstream) Hardware installed around a screen (camera, beacon, etc.) --- 2- Data Quality The second question we should ask is; what is the quality of the data we collect from these sources? Whether it’s weather data, traffic data, or the location data of an audience, how accurate is it? ... When it comes to audience location data, again, things are a little more complicated. The main question we try to answer is: is the person around our ad? If there is hardware like a BLE device around a screen, there may be highly accurate positioning of the person, but these technologies could drain a phone’s battery very quickly. Also, BLE devices usually don’t produce highly accurate positions, and sometimes 1 meter makes a big difference when you’re around a screen. And again, installing hardware is costly and not very scalable, also the regulations could become a problem. ----- 4- Real-time Insight While we are at it, the 4th step of the graph above (Figure 2) is about trying to understand if the user was around a screen. Well, for digital ads, it’s simple, because you show the ad when the user loads the page in real-time (i.e. most likely looking at the screen). For (D)OOH, you have to make complex (probabilistic) calculations to analyze if the user is around the screen. There is rarely real-time information available. And even if you install some sort of hardware to the billboard to get this information in real-time with higher accuracy, as the Route (UK) puts it “those exposed to the medium are constantly moving”, meaning they may not be looking at the screen.

1. May 2022
The Untold Story of Data in the
(D)OOH Advertising Industry
​​

2. Executive Summary
In the advertising industry, wherever you look, whoever you talk to, it’s all about data. And it
makes sense because we need data to advertise more effectively and more efficiently.
(D)OOH has been suffering in this area, but many organizations and companies around the
world try to connect data - especially audience data to this medium.
Though, there are still some challenges. And in this paper, we analyze those challenges in 4
main sections:
1- Data source
2- Data quality
3- Lack of universal tracking technology
4- Lack of real-time insight
Actually, these challenges may be soon (or already are) part of the digital advertising ecosystem
as well. Privacy concerns are forcing companies like Apple and Google to increase limitations
around audience data. Facebook’s admission regarding the potential loss of $10 billion in
revenue in 2022 due to the new data-related constraints is a strong signal that the industry
started to see some negative effects of this trend.
Yet, any piece of data is important, and we need to do anything possible - within the ethical and
legal boundaries of course - to innovate around this subject.
▶ More details in the upcoming pages.
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3. Introduction
(D)OOH advertising industry is hungry for data. Any data point regarding running effective
advertising campaigns is very helpful.
As Airsqreen, we’ve been talking to a lot of OOH experts and marketers in different countries -
from the US to Ecuador, from Spain to Australia. And we’ve been asked many questions about
data - especially audience data.
We wanted to prepare this document and address some of these questions and concerns, and
help the industry players understand some of the challenges and opportunities around this
concept.
And we promise; we’ll keep things simple.
Fundamental Questions
First things first, let’s start with the fundamental questions we ask ourselves regarding an
advertising campaign (see figure 1).
1- Where (on which screens) should I advertise?
2- Did I show my ad successfully?
3- When the ad was shown, was the target audience around the screen?
4- Did the audience see my ad?
5- Did the audience take any action (e.g. bought my product)?
1st and 3rd questions are about targeting, 2nd and 4th (and maybe 3rd) questions are about
ad-verification, and the 5th question is about attribution & analytics.
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4. Figure 1 - Campaign Success Hierarchy
Please note that if one of the first 4 steps fails, the success of the campaign also fails.
1- That means that if you choose the wrong screens, you’ll never show the ads to the target
audience.
2- If your ads don't appear on the selected screens, well, the target audience won’t be aware of
what you offer.
3- When you show your ad, if the target audience is not around the screen, again, the target
audience won’t be aware of what you offer.
4- If they don’t look at your ad, yet again, the target audience won’t be aware of what you offer.
5- And only after all the successful completion of the previous steps (probably more than once,
so that the audience is exposed to your ads more than once) you can expect action from the
audience.
Challenges with Data in (D)OOH
There are multiple challenges with data in the (D)OOH advertising industry. We’ll discuss some
of them below.
1- Data Sources
Let’s start with the most important one; where are we collecting data from?
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5. Depending on the type of data, this source can change. If it’s weather data, it can come from
sources like OpenWeatherMap.org. If it’s traffic data, it can come from sources like Here.com.
There are many data sources out there that can provide all kinds of information needed to make
the campaign more interesting.
But when it comes to the audience data, especially audience-location data, things get a little
more complicated. This data is mainly retrieved from 2 sources:
- Mobile apps (direct integration and/or bidstream)
- Hardware installed around a screen (camera, beacon, etc.)
Some mobile apps share users' locations with data aggregators by integrating data aggregators’
software (a.k.a. SDKs) into their apps. Then this software gets the location of the user from time
to time.
Some other apps just pass this information through programmatic advertising channels. When a
user loads a page, the app (through its advertising technology called SSP) sends his/her
location to the advertisers, and some data aggregators collect these location data to resell to
their clients.
In both cases, there may be problems with the quality of the data, which will be discussed in the
next section.
Another approach is to install hardware like cameras or BLE devices. It could increase the
accuracy of the user’s location, yet this approach is not very scalable as it’s costly to deploy
these devices and then maintain them. And of course, there are regulations like GDPR that make
things more challenging.
2- Data Quality
The second question we should ask is; what is the quality of the data we collect from these
sources? Whether it’s weather data, traffic data, or the location data of an audience, how
accurate is it?
Depending on the type of data and the data source, it can be very accurate. If we have a camera
installed on a billboard and we analyze how many people are looking at the billboard, the
accuracy rate can go very high. If we have a sensor deployed on a billboard analyzing the
humidity level, the accuracy rate can be very high.
When it comes to audience location data, again, things are a little more complicated. The main
question we try to answer is: is the person around our ad?
If there is hardware like a BLE device around a screen, there may be highly accurate positioning
of the person, but these technologies could drain a phone’s battery very quickly. Also, BLE
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6. devices usually don’t produce highly accurate positions, and sometimes 1 meter makes a big
difference when you’re around a screen. And again, installing hardware is costly and not very
scalable, also the regulations could become a problem.
A more popular approach is a software-based approach, where the data-aggregators ask some
popular app-owners to install their software (a.k.a. SDK) to collect location data from the users.
Through this software, they apply some algorithms taking into account signals from Wifi, GPS,
cellular, etc. sources and try to locate the position of the user.
This may also provide a highly accurate position of the user (though mostly it doesn’t), but the
issue is we can’t keep track of the user very frequently, as it would drain his/her battery very
quickly. So data aggregators limit this tracking signal to every few minutes (or longer). And even
a few seconds makes a big difference when you’re walking.
Plus, regulations (again) and data-collection limitations of companies like Apple and Google
certainly don’t help. In fact, Facebook said they’d lose $10 billion in 2022 due to the new
data-related limitations introduced by Apple on iPhone devices . If Facebook is suffering from
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this, imagine the rest.
That’s not it. Let’s say data points are perfectly accurate and there are no regulations and there
are no limitations from Apple and Google or anyone else (a marketer’s heaven). The issue is
that data aggregators usually sell this data with some delay (a few hours or daily), meaning all
you can do is apply some algorithms for the probability of the user being around your ad next
time.
1
https://www.cnbc.com/2022/02/02/facebook-says-apple-ios-privacy-change-will-cost-10-billion-this-year.ht
ml
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7. And all of the above efforts, installing hardware or software, collecting data points, applying
algorithms, data science, and so on, are just to understand if a person is around our ad.
Now, compare this to digital advertising where the person is looking at his/her phone or laptop.
Life is too easy for digital advertisers.
3- Lack of “Cookies”
If you’ve ever run digital advertising campaigns, you'll probably agree that it’s been relatively
easy to target an audience (in the future it may not be so, as 3rd party cookies are about to
disappear ).
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The beauty of digital advertising is that it is easy to collect data, connect this data to the person
while s/he is navigating through different websites, and use it for targeting the person at the
right time at the right place.
This has been mostly possible thanks to a great (and underrated) technology called cookies .
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The problem with the (D)OOH industry is that we don’t have a universal technology like cookies.
We actually put a massive amount of effort just to match what a simple cookie does.
Figure 2 - Steps between audience and OOH media (Source: Geopath)
3
https://en.wikipedia.org/wiki/HTTP_cookie
2
https://www.wired.com/story/google-floc-cookies-chrome-topics/
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8. Geopath (US), is using the above steps (see figure 2) to create a connection between the
audience and OOH media . Almost all of the 2nd and partially 3rd and 4th steps in the graph
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above are to deliver what a cookie can deliver for digital advertising. So it is really challenging
for the (D)OOH industry to match the digital industry and track users while they navigate through
streets without technology like cookies.
4- Real-time Insight
While we are at it, the 4th step of the graph above (Figure 2) is about trying to understand if the
user was around a screen. Well, for digital ads, it’s simple, because you show the ad when the
user loads the page in real-time (i.e. most likely looking at the screen).
For (D)OOH, you have to make complex (probabilistic) calculations to analyze if the user is
around the screen. There is rarely real-time information available. And even if you install some
sort of hardware to the billboard to get this information in real-time with higher accuracy, as the
Route (UK) puts it “those exposed to the medium are constantly moving” , meaning they may not
5
be looking at the screen.
Moreover, most of the budgets in DOOH are spent without any real-time ad-play information,
meaning the buyer doesn’t have the proper technology to track his/her campaign. Basically,
some advertisers out there don’t even know or verify if they could show the ad itself, let alone
analyze who was exposed to it.
On the Airsqreen advertising platform, sometimes we discover big discrepancies between the
planned and delivered amount of ad plays. Sometimes some of the screens don’t start, or they
stop in the middle of the campaign for various reasons (technical issues, power outage, etc.).
And in some cases, the media owner itself is not aware of the situation and they notice the
issue upon automated alerts from our platform.
So the advertisers who don’t use such technologies don’t even know if their ads are delivered on
a screen, they just hope that things are ok and the reports they are provided are accurate. But
hoping and knowing are different things. So we advise using modern advertising technologies
to be in full control.
Putting Pieces Together
5
https://www.route.org.uk/research
4
https://geopath.org/wp-content/uploads/2019/11/Geopath-Standards-and-Best-Practices-Document_11-7-19.p
df
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9. Remember our campaign success hierarchy graph? Let’s discuss these steps briefly after having
learned some of the data-related challenges in our industry.
Campaign Success Hierarchy
1- Where to advertise can be decided with the help of different audience data points - albeit not
perfect, or it can be decided by using contextual targeting. That means depending on the target
audience we can choose to advertise in a gym or airport. We believe the contextual approach
can be really effective, but we also recommend trying different technologies and data vendors to
see if the results are satisfactory.
2- We can track and optimize our campaigns with real-time insight using modern advertising
technologies (self-advertising here; Airsqreen is a great technology to do that). We can use data
points like weather, traffic, or any other information to make the content dynamic, meaning the
image or video can update itself with real-time data.
3- To analyze whether we showed our ad at the right time can be done again using modern
advertising technologies. For instance, at Airsqreen we provide real-time data regarding when an
ad is played on which screen, and we can feed this data into other systems for further analysis
to answer “was my target audience at that coordinate at that very moment?”.
(Sorry for all these Airsqreen ads, but seriously, it’s a great platform! 😇)
4- To analyze whether the audience actually saw the ad can be achieved by installing cameras
on the screens. There are technology companies out there that provide such services. We just
need to make sure we’re not risking anything against regulations.
5- Finally, to analyze whether the audience took any actions, we can use some old-fashioned but
relatively effective approaches like QR codes, or unique contact information that is displayed in
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10. the content (e.g. a special phone number dedicated just for this campaign), or others. Or we can
use more modern approaches, analyze the data collected from mobile devices, and use some
algorithms to make an attribution analysis.
Conclusion
As discussed, using data in (D)OOH advertising is possible, though audience data has its
limitations. Still, there are companies and organizations working in this area and constantly
coming up with new and innovative ways to solve these issues. And we definitely recommend
trying these solutions and seeing which one is a more effective solution for your needs.
On the other hand, the privacy-related trend doesn’t seem to be ending soon and our guess is it’ll
get more challenging for the advertising industry to benefit from audience data in the upcoming
years. Facebook’s admission regarding the potential loss of $10 billion in 2022 due to the new
data-related constraints is a strong signal that the industry started to see the negative effects of
this trend.
That means things are about to get more challenging for the digital advertising industry as well.
This may be great news for the DOOH industry because those budgets will have to go
somewhere.
Let’s modernize, leave old-fashioned manual steps behind, and provide real-time insights to our
clients. We believe this would be the only way for our industry to grow much faster.
We also believe that great days are ahead for our industry.
Airsqreen provides a DOOH advertising platform to automate IO-based campaigns (i.e.
programmatic direct), that helps with campaign management, ad-verification, and
real-time reporting.
For more information, please email more@airsqreen.com.
© Airsqreen, Inc.
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