As an “open world” medium, OOH and DOOH presents a challenge when it comes to assessing impact.
Unlike other digital options with tagging, or other traditional options with measurement in place like print, TV, or radio, OOH has no lock-tight way to track exposure. As average daily traffic miles continue to rise back up near post-COVID levels, it’s important to understand the measurement options at work. For example:
- Through the use of mobile location data, we can provide insights into consumer mobility and behaviors that can provide understanding of exposed OOH audiences. Anonymous, aggregated data is used to identify those consumers who were exposed to OOH. Exposed consumers take action and are matched to customer data via a DMP or other platform. This provides the means to evaluate performance alongside other media types, allowing brands to gauge the medium’s influence on brand campaign metrics such as awareness, recall, purchase intent, app downloads, TV viewership, offline sales and site visitation, comparing exposed vs. unexposed audience behaviors.
- Regression modeling can also measure OOH using the same approach applied to other channels. The major difference compared to using location data is that you’re not using individuals to explore the difference between control and exposed groups; rather, you’re looking at aggregate media weight by channel to determine impact. Using variation in media weight over time lets the model determine the impact individual channels have on a dependent variable set. All that is needed for this approach is impression delivery over time from OOH, post buys.
- Match Market Tests can also track the lift from OOH. However, in order to properly execute this strategy, you have to tightly control for the other independent variables across markets. This not only means that setup is more intensive (than regression modeling for example), but also that you ideally have multiple test and control markets to normalize the data and calculate the lift attributable to OOH. Furthermore, setting up market tests can mean altering plans in ways that are not ideal in favor of controlling for valuables. For example, establishing control markets by not placing OOH as a part of the mix in places where there are indications it would be successful.
- In direct response campaigns, you can track/employ e.g. unique phone numbers, or track site traffic lifts via custom URLs, but this approach is generally not the goal.
- Beyond our tracking, reporting and performance solution, KSM has constructed a database of OOH locations that have been screened for visibility obstructions and viewable approach times. The database includes the latest traffic counts and pricing for bulletins, 30-sheets, 8-sheets, wall spectaculars, transit, and digital OOH and place-based options. Additionally, KSM uses GeoPath to plan OOH campaigns to develop market-by-market scenarios against specific audiences that establish projected reach and frequency.
There is no one-size-fits-all approach to OOH marketing, but as OOH and DOOH continue to evolve we expect these approaches to become more refined as well.