Out-of-Home (OOH) Advertising
Advertisers expect quantified and audited opportunities-to-see, but also want much more, including reach-and-frequency and drive-to-store analytics. Accurate, privacy-friendly measurement is essential for OOH operations, whether data are real time or historical.
Accurate Attribution for Out-of-Home Advertising
The expectations of advertisers vis-a-vis their OOH media providers have continued to rise since the advent of online advertising. Today, advertisers expect quantified and audited opportunities-to-see, but also want much more, including reach-and-frequency and drive-to-store analytics. Accurate, privacy-friendly measurement is essential for OOH operations, whether data are real time or historical.
BlueFox is deployed in four primary use cases for OOH advertising:
Counts of opportunities-to-see
Counts of opportunities-to-see is the original and simplest application of the BlueFox product. BlueFox is ideal for measuring the number of persons that approach advertising media. The number of persons detected at any moment is the “visitor count”. The number of distinct visitors during a period of time (e.g. quarter hour) is the “visit count”. How long each visitor is in proximity to the advertising during their visits is captured by the BlueFox dwell-time measurement.
Generally, advertisers are most interested in the number of visits: how many people have come to the location of the advertising media. This measurement of opportunities-to-see is typically the basis of advertising pricing. A basic reporting of visits to advertising media can be shows as a simple bar chart.
Counting of visits may count the same visitor more than once. A visitor could pass by in the morning on the way to work, and then pass by again in the evening on the way home during the same day. To distinguish between multiple visits by multiple visitors, and multiple visits by one person requires the introduction of the concept of unique visitors.
Unique Visitor and Visitor Recurrence Counts
BlueFox was the first (and maybe the only) foot traffic analytics provider to measure unique visitors in a manner that is GDPR-compliant. Unique visitor measurement delivers separate values for reach and frequency, rather than just aggregate opportunities-to-see. “Reach” is the number of unique visitors that have had an opportunity to see. Frequency is the number of times that visitors have seen a specific advertisement.
Unique visitor measurement allows advertisers to change campaigns on the basis of recurrence, rather than simply some aggregate number of opportunities to see. If 40% of passers-by have seen the advertisement four or more times, then it might be time to change the advertisement. While this measure is imperative for print advertising, it is also valuable to digital advertising because it offers a measurement of penetration.
A simple bar chart can summarize the reach and frequency of a campaign. Over time, the median number of views of media will grow and the average recurrence value to move to the right on this chart.
Real Time Visitor Counts
Programmatic digital out-of-home advertising introduced the need for real time visitor measurement. The financial value of media at any moment in time is proportional to the number of viewers of that media. Knowing the real time count is fundamental to monetizing the media.
While BlueFox can report the number of persons in proximity to the media on the BlueFox web dashboard, this use case generally employs the BlueFox application programming interface (API) to deliver this number, generally every few seconds. The BlueFox APIs are RESTful and easy to integrate into any marketplace system.
Drive-to-store reporting is a special case of unique visitor counting that measures the share of unique visitors to a store that have previously passed by an advertising site. Drive-to-store analysis is an ideal mechanism to determine the impact of an advertising campaign that is intended to direct pedestrian traffic to a store.
THE SIMPLEST APPLICATION OF DRIVE-TO-STORE CONSISTS OF TWO STEPS:
1. Calculating a traffic baseline without advertising, and
2. Calculating the effect when advertising is active.
If the baseline of visitors to a store who have passed by the locations of the advertising signage is X, then we can install the advertising signage and measure X a second time. The uplift of X, from baseline to campaign, represents the effectiveness of the advertising campaign.
Drive-to-store studies are generally combined with reach and frequency studies. Review a case study of drive-to-store conducted with JCDecaux at a mall in Singapore.