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Although OOH (Out-of-Home) media presents advertisers with a dynamic, effective mass reaching medium –it remains a challenge to measure compared to other channels. This is largely the result of a lack of standards around outdoor advertising.
Just like in the digital world, a few major players dominate globally and provide their own measurement methods. On the other hand, brands remain largely unaware of how to measure OOH advertising options and rely on age-old billboard ratings. Here’s a quick analysis of some of the more common OOH measurement practices.
Traffic information provides advertisers with estimated ad exposure metrics.
A rough analysis of the data can easily be obtained from government census and
surveys. This is usually looked at during the planning stage but is commonly used for post-campaign reports as well.
Traffic data is fairly easy to attain for both the asset owner and the advertiser. If not freely available on open data resources, traffic reports can be bought for a fee from survey companies
While it provides some base, much of this is survey-based and historical in nature. For example, it doesn’t make sense to measure 2019 campaigns with 2014 traffic data? At the same time, the data cannot be used to measure digital OOH sites, which accommodate multiple advertisers at different times.
Digital brands can also add coupon codes to their OOH campaigns. This makes measurement easier in terms of conversions – how many people saw the ad and used the coupon code.
Measurement is fairly straightforward and the advertiser does not incur any additional costs. It also enables the brand to understand which billboards are performing better if different coupon codes are used across multiple billboards.
Digital coupons can only go as far as measuring conversions. However, it won’t help an advertiser understand the audience being reached by the billboard but did not redeem the coupon.
Creating custom landing pages has become a standard practice for digital marketers. Today, each campaign is tagged to a specific landing page to improve the user experience and also make measurement more efficient.
The same concept can be used for billboard campaigns. Similar to using coupon codes, custom landing pages enable brands to understand where users are coming from. This is popularly done using QR codes and NFC tags for indoor media in malls, stores, and even train stations
Just like coupon codes, this form of measurement helps brands measure conversions in the form of web visits. It also helps them segment the audiences who specifically visit because they saw the billboard ad.
Again – while conversion numbers are easily measured, it’s hard to benchmark billboards based on conversion rates.
Although it may require a more sophisticated approach, tracking metrics on social media are also being used to measure out-of-home (OOH) campaigns. This could be done using hashtags that would be tracked on Instagram and Twitter.
Additionally, search trends could also be used to attribute uplift in keyword or brand name searched in areas where the billboard campaign is ongoing.
When a consumer connects with a hashtag or social media page because of the billboard, brands have a better understanding of who the person is because they are tagged to profiles.
This form of measurement is largely dependent on the consumer taking some form of online action. While this may be relevant for high dwell time locations like bus stops and train media, it is difficult for drivers who pass by roadside billboards to take an instant smartphone action.
By looking at the various OOH measurement metrics above, one issue becomes apparent. Each data source is usually looked at in isolation and there is no common thread to understand the relationship between them.
The major OOH players are moving towards mobile movement-based measurement, which provides an individual-level understanding of audiences passing by a screen.
However, we understand that offline consumer movement has a range of dimensions beyond online actions and cannot be pictured using a single data source.
We believe that multiple sources of location intelligence provide the most extensive mechanism for counting audiences who are exposed to OOH campaigns. This also helps us understand not just the demographic attributes of the screen viewers but also their purchase intent, product usage, and ooh performance movement patterns.