Are you getting the most bang for your buck when it comes to advertising?
Not surprisingly, businesses want to know that their marketing budget is well-spent. Hence, marketers and advertisers demand data to prove that their campaigns are a worthy investment. Understanding the number of consumers that viewed your ad and its impact on their purchasing decisions is crucial in every marketing campaign.
In the digital marketing world, tools for monitoring consumer behavior throughout the sales funnel have long been available. In contrast to digitally native marketing, applying similar measurement techniques within the out-of-home (OOH) industry has been a persistent challenge. However, thanks to the ubiquity of mobile devices and leaps forward in geospatial data analysis, OOH measurement and attribution has become more accessible and accountable than ever before.
So, how does data attribution work in OOH? Let’s start by defining the basics.
What is Data Attribution?
Data-driven attribution is the use of data analytics to determine the campaigns, keywords, or advertisements that lead to conversions. A simple example of attribution in an online setting is measuring the number of users that bought a new pair of headphones after seeing an ad for AirPods. Attribution in traditional advertising might include sending surveys to those who were known to have seen your ads. According to Google, 60% of leading marketers believe data-driven attribution is essential to understanding the journeys of high-value customers.
What's more, top-performing marketing organizations are five times more likely to use advanced attribution.
In short, data-driven attribution lets advertisers measure–and even predict–the impact of their campaigns in repeatable, quantifiable ways.
Data Attribution in OOH
In the context of OOH, data-driven attribution is made possible through the collection of anonymous cell phone location data. Advertisers can leverage this anonymous mobile data to estimate the number of people that saw an OOH advertisement (e.g. a billboard or bus shelter) and measure the advertisement’s impact on future behavior. Along with more in-depth measurements, OOH data attribution reports typically include the number of exposed devices, device visitations at relevant points-of-interest, and audience demographics.
In addition to delivering exposure and visitation reports, data-driven attribution allows advertisers to create innovative out-of-home campaigns that integrate with digital marketing strategies. Marketers can even re-target shoppers with messages and promotions based on their location, behavior, or purchase intent. Imagine passing by a Nike billboard and receiving a promotional message for a pair of running shoes. Conveniently, the message could also include directions for a nearby store that will accept the coupon.
Billups Methodology for OOH Data Attribution
How can you measure the impact of OOH ads?
At Billups, we know that precision matters when making OOH more accessible and accountable. Our in-house data science team has developed powerful patented technologies to meet these goals all while creating smarter OOH advertising campaigns. One of these proprietary technologies is our patented SSI Viewability score, or Opportunity to View. In the section below, we discuss how this works.
Opportunity to View
Let’s take a look at the capabilities of this state-of-the-art technology:
1. Image Processing
Choosing the location of an OOH ad is a lot harder than it looks. Along with abstract concepts such as market saturation and spatial correlation, advertisers have to consider the practical issue of how the ad will appear from a distance and what potential obstructions that may get in its way.
Fortunately, our SSI tool employs image processing techniques which can assess the readability of OOH ads. Using thousands of example images, we’ve trained our tool to identify OOH units (e.g. billboards, bus shelters, posters, wallscapes, etc.) and trace them in an image. After identifying and tracing the OOH units, our SSI tool uses an attention mapping model to objectively measure which objects within the scene might distract an observer from the advertisement. For example, a massive billboard along a desert highway in Arizona will have much less competition for attention than a news stand ad in Times Square.
2. Simulated Journey
Another advantage of our model-based approach is the ability to measure ad visibility from many different distances and vantage points. Rather than taking the traditional “market ride”—driving highways and traveling long distances to determine the ideal locations for an OOH campaign’s ads—our SSI tool can automatically determine ideal ad placements simply from analyzing street-level imagery. Along with physical obstructions such as trees or buildings, our SSI tool also accounts for changes in an observer’s dwell time, elevation, speed, and viewing angle.
After gathering all the data, our Sciences team comes up with an SSI Viewability score for every out-of-home unit within a market. Take note that this solution is distinct from a traditional geofence, which has no understanding of the viewability of units within a region–simply their locations.
OOH and the Current Media Landscape
For the past year, the COVID-19 pandemic has led many consumers to stay indoors for a prolonged period of time. The good news is that the ongoing vaccinations mean we may soon find the light at the end of the tunnel. Interestingly, the pandemic fatigue and easing of lockdowns may lead many consumers to engage in outdoor activities in the foreseeable future.
Due to the lockdown effects of COVID-19, many businesses have opted to launch digital-only marketing campaigns, fearing the out-of-home space was a poor investment. However, as more people engage in outdoor activities, consumer behavior has begun to shift back in favor of OOH advertisement. According to our research, 71% of consumers are interested in walking around town or in their neighborhood. Meanwhile, 55% of consumers want to travel greater distances than before the pandemic.
Ready to Leverage Data Attribution for your OOH Campaign?
Out-of-home advertisements are a powerful customer acquisition tool.
With Billups’ in-house data science team, media planners, buyers, and advertisers can gain data-driven insights for the entire lifecycle of an OOH campaign. From determining the visibility of individual bulletins and wallscapes to measuring market saturation and audience demographics, our proprietary techniques solve for any business outcome powered by data science.
Are you interested in launching your own OOH campaign with measurable and attributable results? Get in touch with our team today.