One of the biggest myths in OOH is that it is not measurable and that attribution is simply not possible. However, using data science and modeling technologies it is possible to show the impact of an OOH campaign. In this article, you’ll learn the importance of attribution, how it works in OOH, and how Billups’ attribution works to help measure the outcomes of an OOH campaign.
Attribution evaluates marketing touch-points a consumer encounters and measures the outcome as a result. For online marketing campaigns, this might be the number of clicks, form fills, or conversions. However, OOH is considered an offline channel. Offline channels such as OOH, TV, and radio cannot take advantage of the direct 1:1 attribution channels as digital. As such, data science and modeling come into play to determine the results of a campaign.
Offline attribution shows how offline marketing efforts influence customer behavior and outcomes. Some offline marketing channels include television ads, radio and outdoor advertising. Basically, anything that is not online, can be considered offline.
Online attribution shows what online marketing efforts have the most impact. This can include digital advertising, email marketing or social media. One of the benefits of online attribution is that it usually has the ability to leverage digital tracking technologies to collect data on consumer interactions with marketing touchpoints.
For offline marketing and attribution channels, the scenario is a bit more complex. It might not be possible to create a direct 1:1 correlation to follow a particular customer journey from prospect to conversion. Offline attribution has to use different methods from online attribution to gather information about customer behavior. Online attribution collects data automatically, whereas offline attribution is a bit more challenging due to the difficulty in tracking customer behavior and interaction in the physical world. Surveys, focus groups and other similar methods are some of the ways that offline attribution can be done, but data science and modeling are becoming increasingly popular ways to determine the impact of offline marketing channels.
Attribution in outdoor advertising answers the question “What did my OOH campaign do?” or “What happened as a result of my OOH campaign?” It allows advertisers to prove the value of Out-of-Home.
Our patented view shed technology determines whether a mobile device location pings within the area from which the OOH advertisement can be seen. From there the mobile device is tracked to determine whether there was a subsequent outcome, such as the mobile device visiting the brand’s store, website or downloading its app. Finally, we apply algorithms to mobile data sets and evaluate what outcomes OOH was responsible for. Here is a graphic depicting the process: 
Now that you have an understanding of the attribution process at Billups, it's useful to know how data science is used in attribution.
Data science is a huge part of how we operate our attribution here at Billups. We use machine-learning to pull in millions of data points so that we can attribute outcomes to specific media activity. It allows us to draw powerful conclusions from sparse data sets to depict campaign performance. Here are some other important points about how we use machine learning and what is possible:
As mentioned earlier, the validation of results is key. The control group is one of the most important parts of an attribution study. It confirms that study results are due to exposure to an OOH unit in a campaign rather than other variables such as seasonality, other media channels or other market factors. Control groups serve as a benchmark to determine the effects of the OOH campaign versus pre-treatment or no exposure to the campaign.
We use the words “treated” and “untreated” to refer to the audience exposed to the OOH and not exposed respectively. Treated audiences are those who were exposed to the campaign, whereas control audiences are those who were not exposed to the campaign. If someone slated for the control audience is somehow exposed to the OOH campaign, then they must be removed from the control group. The groups must be mutually exclusive.
To learn more about our control group methodology, read this article. Now let's get into exactly what Billups attribution can and cannot do:
Here at Billups, we currently have five attribution studies available to measure the results of your campaign. Choosing which study is right for you depends upon your campaign goals.
At Billups, we leverage both the art of strategy and the science of data to help brands create effective and memorable campaigns. Depending on your particular campaign goals we can recommend an attribution study that will help determine whether your campaigns had the intended impact on brand awareness, sales, online traffic and more. Contact us to get started planning and measuring your next campaign.
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