What people want depends on where they are. This simple truism makes sense, but it directly contradicts how brands have been marketing themselves for the past century or so. Both brands and OOH vendors want to maximize the value of every channel, but a message can connect or fail simply because of where the consumer encounters it -- on a mobile screen, desktop, or billboard. Knowing how to vary that message, and testing the effectiveness of message placement, is one area where location data can make all the difference in the world.
Targeting a Moving Consumer
Mobility changes everything about the dynamics of brand loyalty, purchase intent, and delivery channels. OOH data analytics is only now beginning to tap into the vast amount of information on the motivational and engagement significance of location-specific messaging.
Whether consumers are on the move or not, there are multiple marketing touchpoints (mobile/desktop/laptop/TV/video/print ads) that influence their purchasing decision. Where consumers are and have been when they encounter those messages will make a big difference in how motivated they are to act on them.
That’s why advances in the science of location data have made it the single-most important changing identifier that can help a brand bridge the gap between digital and real-world behavior.
One of the biggest challenges for businesses today is that they are constantly bombarded with huge volumes of data from multiple sources. From social media to IoT sensors, this data needs to be collected efficiently, stored securely and accessed logically. This data needs to be accessed remotely by different users and applications.
Brands that can tease out audience insights derived from location data have been able to better understand consumers and create a unified view of what matters most to the consumer, enabling smarter decisions around marketing and business strategy.
Finding the Perfect Place for OOH
The intelligent analysis of location data can help you identify a series of ideal locations for specific messages, based on patterns around where the majority of your consumers live, work and commute between the two. Further, it can also help to build powerful audience profiles of on-the-go audience and audience seen in particular location/areas for the past few weeks, months or years. Detailed analysis of these profiles that determine their brand affinity, interests, preferences, income size, gender, commute patterns, home location, dwell time, etc. in the online and offline world can help to identify locations for OOH placement, which is likely to create impact and increase conversions.
Planning and Managing the OOH Inventory
Once a brand identifies an ideal location for OOH placement, the next step would be inventory planning and managing the existing campaigns. This depends on the breakdown of audience data in different areas. For example, in rural areas and along highways, you might need static or printed OOH, whereas you will grab consumer attention more effectively with digital OOHs around CBDs, shopping areas and in residential zones.
If a brand decides they want to try a digital OOH, they can analyze peak foot traffic time (broken down by afternoons vs. evenings, etc.) to decide on the best times to display the brand's message. For example, integrating location data with third-party data sources like weather and traffic patterns can help to tailor content or creatives to show a relevant set of audience. This can further be used to plan and manage in-store inventory, based on the audience profiles it was delivered to. DOOH placement in airports, subway trains, shopping areas have generated a great deal of buzz with interactive creatives that tighten engagement with the brand.
Measuring the OOH Strategy
Location data and OOH investment should also factor into media measurement for brands that are testing out omnichannel marketing. This will help them compile information on which media channel most likely had the strongest influence on consumer purchase decisions. Consider how you would assign attribution in the following common example:
Customer Alex views your ad on mobile while checking the weather as he leaves home to go to work. He does not engage with the brand after that interaction. Later that same day, he is exposed to your OOH billboard messaging near his work. When Alex arrives home from work that evening, he goes to your website to check out the product on his home desktop. The next day, he sees the OOH billboard again and is reminded of why he wanted to interact with your brand. On the weekend, he walks into your nearby brick-and-mortar store and completes a multi-item purchase.
That’s just an example, but the data backs it up. Allspark, Near’s enterprise SaaS product helped an OOH advertiser to achieve 29% increase in conversions as a result of better content customization/attribution on billboards.
Make sure you are guided by data in planning and executing your OOH campaigns. Reach out to us to maximize the value of Allspark for your OOH planning and measurement.