From the Archive · May 2022 · Industry
Measurement in DOOH
Why measuring impressions has long been a challenge for the DOOH industry — and how Data Jam set out to solve it.
From the Archive · May 2022 · Industry
Why measuring impressions has long been a challenge for the DOOH industry — and how Data Jam set out to solve it.
Originally published May 2022 on the previous Data Jam site. Preserved here as part of our archive.
Measuring impressions, the opportunities for an audience to view media on a digital out-of-home (DOOH) screen, has long been a challenge for the DOOH industry. This issue has been further highlighted by global events over the past two years.
Planners require precise and dependable audience exposure data to craft cost-effective campaigns for their clients. In turn, clients should receive evidence from their agencies that DOOH justifies its share of their advertising budget. Media owners need timely and accurate data for their inventory, enabling them to price their digital signage accurately and demonstrate return on advertising investment to their product buyers. Lastly, the emerging programmatic buying ecosystem should be underpinned by accurate predictive figures for DOOH sites, which can only be obtained through precise historical measurement of impressions.
There is a well-established and respected solution for DOOH audience measurement, covering the majority of digital inventory and serving as the main currency for purchasing OOH advertising. However, an increasing amount of digital inventory operated independently from this service presents a significant challenge. These screens lack reliable and timely audience data, posing a problem for media owners looking to exploit advertising opportunities.
Primarily, smaller niche media owners are installing DOOH screens in targeted environments such as student accommodations, music venues, food outlets, workspaces, residential buildings, and gyms. As these environments are not accessible to the general public, obtaining accurate and reliable audience data for these screens becomes difficult.
Secondly, there is a growing number of media owners who have frames in publicly accessible areas like shopping centres but are not currently utilizing the industry standard solution. These owners would still benefit from accurate and reliable audience data.
One potential option is the utilization of third-party data. Initially, it might seem that the abundant third-party data generated by society as a whole would be more than capable of providing timely and accurate impressions figures for the DOOH industry. However, in practice, this is not the case. Companies such as Apple, Google, mobile telecommunications companies, and mobile application API providers like weather companies possess the data required for generating the necessary insights. However, there are challenges related to data availability, cost, and timely access. Furthermore, the introduction of recent privacy legislation in Europe, Asia, and other parts of the world further hinders the use of such data.
Even when considering third-party data obtained at a more localized scale, there are challenges. Data sources like till transactions, gate transactions, and car park usage, when used to estimate impressions for nearby DOOH signage, encounter issues. The primary problem is that these sources only have a tentative correlation to the desired figures. Attempting to derive comparable data for different geographical sites by utilizing disparate data sources only worsens the problem.
Instead of comparing apples with pears, these approaches often end up comparing apples with cars.
This is not to discredit the use of third-party data in DOOH, as it does have its value. It is particularly useful for providing audience segmentation data that can be combined with the required impressions figures to optimize programmatic planning. However, it is not a sufficient substitute for accurate and timely impression figures themselves.
Another alternative worth considering is the installation and utilization of remote sensing equipment. Traditional remote sensing devices include camera equipment, beam breakers, and lidar, which is a remote sensing method that employs pulsed laser light to measure distances. However, even this approach has its limitations and drawbacks.
The suitability of data obtained through these types of devices for impressions measurement is a topic open for debate. Several regions, such as the EU and certain states in the USA, prohibit the use of camera equipment in digital signage. Additionally, the significant amount of data transmission or on-device processing required to convert camera images into meaningful data can pose challenges. Beam breakers face inherent difficulties when dealing with large crowds, as does lidar. Furthermore, neither of these methods is suitable for installation in all environments.
A common challenge shared by the discussed alternative approaches is the financial burden they impose. Implementing and operating such technologies at scale can be prohibitively expensive. This presents a significant barrier to entry for smaller or startup media owners looking to install DOOH screens.
It is suggested that designing a solution from the ground up should begin with a functional specification that includes:
After nearly two years of searching for a viable approach, including exploring bid stream data, first-party API location data, and third-party aggregators of location data, Data Jam decided to develop its own solution based on these requirements.
Two years later, Data Jam has successfully created the JamBox service that meets all the specified goals. During this process, a sensing device that was not previously discussed came into play—one that can detect and measure the presence of digital devices. Nearly everyone carries a digital device, such as a mobile phone, at all times. Mobile phones regularly send out signals searching for WiFi access points to connect to, typically at least once a minute, regardless of the device manufacturer. By detecting the mobile phone signals in close proximity to digital signage, highly accurate impression measurements can be obtained. Furthermore, the signal strength can be utilized to estimate the distance of the device from the signage. An algorithmic approach is employed to filter out signals that do not originate from mobile devices, enhancing the accuracy of the collected data. Privacy is a top priority, as the signals collected are completely anonymous, and the data is securely encrypted during transfer from the JamBox device, ensuring full compliance with GDPR regulations.
The JamBox service is currently deployed at nearly 500 sites across the UK, and this number continues to grow. With access to accurate impressions data, our customers are utilizing it in various ways. They rely on a rolling four-week average of impressions figures, categorized by site, day, and hour, to establish pricing for their advertising. Reporting the actual number of impressions achieved for each campaign has become straightforward and automated.
An unexpected advantage of the JamBox service is the active monitoring of installed devices. This feature has already proven valuable in detecting WiFi and power outages at digital signage sites, enabling prompt resolution of any issues. In addition to collecting impressions data, Data Jam also records hourly weather details. This information is now being utilized to develop predictive models, enabling programmatic buying functions for the DOOH industry. This capability has long been discussed but not fully realized until now.
At Data Jam, we emphasize the importance of real data in real time. When it comes to digital signage, we believe there is no other effective solution that can match the insights provided by our service.
Data Jam has come a long way since this was written. Explore the platform, or talk to us about measuring your network.