Online ad personalization is the future. The industry recognizes it, and consumers want it. The issue is that attempts at personalization thus far have lacked both scale and accuracy.
If you approach a consumer with an ad that fits the context of their life, they won’t ignore you. Direct mail proved the benefits of directly addressing a qualified consumer decades ago. And when online advertising claimed one-to-one targeting ability with cookies, it seemed like a natural fit to mimic direct mail.
Using cookies, advertisers first tried to track a person’s online behavior and fit it to a pre-define persona. That proved inaccurate, not quite mapping out a qualified lead the way a modeled and scored direct mail address would.
The second idea was to “onboard” offline lists. That seemed better, until brands realized that an onboarded address gets pooled with 200 other cookies - making claims of one-to-one hard to defend.
The other problem is that in the last couple of years, the world has shifted to mobile. More time is spent online in mobile than on the desktop. Cookies are functionally useless on a smart phone, so you have to work with apps and device IDs. This works up to a point, but it is very tough to scale and even tougher to match to a known audience.
Ad personalization was never supposed to mean ‘chasing consumers across the Internet and trying to force a cookie on them.’ The final form of personalized advertising is using Big Data to define an audience and deliver a refined message to them at a preferred time, in a preferred location, on a preferred device.
The toolset for this level of personalization already exist. Our solution uses a combination of proprietary processes to segment audiences and optimize to their preferences. Find out more.