Buzzword Breakdown: Cross-Device Targeting
The mainstream adoption of the smartphone and tablet hit its stride around 2010, but the targeting technology is still very much in its infancy. Until recently, cookie-based targeting has been the standard way to follow consumers as they browse online. However, with a number of critical flaws, the industry has turned to new methods: probabilistic identification and deterministic identification. Here’s a breakdown of these three options for identification and targeting.
Cookie-based targeting is the oldest, most scalable, and yet least accurate method of targeting cross-device. Cookies are still the go-to for desktop display, but they are very limited for mobile and can’t connect the data across devices. So, as consumers increasingly use their mobile devices through the purchase funnel, cookies are becoming less and less useful.
Targeting using probabilistic identification uses publically available ad-serving data, such as device, browsing behavior, location, OS, etc. Using a mix of algorithms, these data points are pieced together to predictively identify individuals. With match accuracy between 50-90%, probabilistic identification is much more accurate than cookies. That may reduce wasted budget spend on the audiences marketers are not trying to reach, but experts have also remarked that probabilistic targeting methods are unclear, lack standardization, and are not scalable to large audiences.
Targeting based on deterministic data uses known user information such as login detail, email address, and customer ID. The amount of information gathered creates the potential to capture individual user profiles. But so far only email providers and communication and social networks have access to a substantial set of this data, and not all are scalable for mobile. While the scalability of the deterministic data approach is limited, logins and persistent IDs are certainly more scalable than past targeting methods, as they hold a much deeper level of audience knowledge.
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