Ultimately, publishers need to follow a three-step path for cross-device success:
1. Understand where the challenges are. Publishers typically face three challenges in an increasingly cross-device world. First, they don’t know who their audience is. Many publishers have added cookies or login systems to learn about users, but even in those cases, they know very little about users’ interests and preferences, and it’s difficult to find those users outside of a single platform, not to mention across devices.
The second challenge is that publishers want to empower their sales teams to establish more direct relationships with advertisers to command more value for their audiences, versus devaluing inventory through a marketplace. However, the “do it yourself” approach is often not possible for anyone but the largest publishers.
A third common challenge: Marketers are moving ad spend to mobile and want cross-device data for targeting, given that Google reports that 90% of multiple-device owners use screens sequentially to complete online tasks. Though this trend of increasing mobile spend may not necessarily be a burden for publishers with mobile inventory, the issue is that marketers are expecting high return on their mobile spend, which publishers cannot necessarily guarantee due to limited mobile data.
2. Learn how to solve those challenges. By selecting the right partners, publishers can easily make their data work for them. Many publishers already use data management platforms (DMPs), which help profile users on silo’d platforms, either desktop or mobile. But DMPs can’t necessarily match users across screens. That’s where device matching comes into play. There are several companies that have built cross-device pairing technology utilizing either deterministic or probabilistic device-matching, the two most common ways to solve for cross-device identity.
The deterministic approach is person-based identification that involves collecting personal data, and using that data to connect users across devices, typically through a login system. The probabilistic device-pairing method uses accessible data, from ad requests, for example, to make predictions about users.
3. Leverage cross-device data to add value. The most important value-add of cross-device data is that it enables publishers to participate in audience extension. Whether using first-party audience segments, advertisers’ audience segments, or third-party DMP audience segments, the ability to leverage audience data to reach desktop users on their mobile devices makes any publisher a valued partner for advertisers.
Once publishers are able to offer cross-device data and retargeting abilities, they can offer their advertisers even deeper features, such as cross-device frequency capping, storyboarding and sequential messaging.
Ultimately, the sophisticated use of cross-device audience data leads to more value for everyone involved. Publishers can command higher prices because their inventory is more valuable, advertisers can run more effective campaigns, and users are provided with more relevant messaging.