The biggest goal of an out-of-home campaign is almost always to influence consumer behavior or make an impression on a consumer. First and foremost, out-of-home media is always striving to drive people to visit an actual store or buy a product.
That being said, measuring the effectiveness of an out-of-home campaign’s ability to actually influence a consumer’s behavior is a different story. It’s not as easy as assuming that a person who passed your billboard was influenced to visit your store because they saw said billboard. The factors are nuanced and the technology that is most commonly used to do so, while effective, is by no means cutting edge.
The ubiquitous use of mobile phones has changed all that, providing new opportunities to source data and update outdated technology. These changes have made huge impacts on the world of data science and technology, revolutionizing the way we track consumers. At the forefront of this technology, our data science team at Billups has been working to catalog consumer behavior patterns and construct a baseline of behavior that can be used to provide insight into what might influence consumers to purchase a product or visit a store.
We’ve attached a link to a paper written by our data science team which explores this causal modeling of consumer behaviors based on out-of-home campaigns. Using as their source a massive data set that includes info on purchases, visit history, demographics, and psychographic insights, they are able to paint a thorough picture of consumer patterns that allows for accurate insights into their behaviors.
Read More: Causal Modeling of the Impact of OOH Media