Is offline data the dark horse of digital marketing?

By Pete LaFond, vice president of marketing, TruSignal

We are living in the era of Big Data, and the consequences for marketers are seismic. But no matter how much information there is about online behavior, and no matter how sophisticated we become at analyzing it, what consumers do online is still only a sliver of the picture.

Critical insights about consumers’ identity and their path to purchase exist in the vast swaths of profile data held offline, well beyond the cookie’s reach. Understanding consumers’ financial means, lifestyle preferences, and household information can drastically improve marketers’ ability to find more of the right ones. It can also help marketers combat fraud and effectively reach the exact same audiences across multiple devices.

Put simply, offline data is an essential part of making Big Data work for marketers.

Target more of the right people
Offline data should not replace online data, but it does help to mitigate the inherent limitations of targeting based on cookies alone. Cookies provide a means to target consumers based on real-time behaviors. But cookies capture only a disparate and limited amount of data: only about 50 data points per cookie, on average. In addition, the life of a cookie is between 7 and 14 days, which constrains scale. Targeting solely with cookie data gives a limited and fleeting picture of the consumer.

Offline data, by contrast, provides a reliable and stable data resource with a longer life span. With coverage on more than 90 percent of U.S. adults, offline data sources aggregate thousands of data points. The result is massive reach and breadth of data that, when properly analyzed, can identify great prospects that online signals may have missed.

Filter out the wrong people to improve CPAs
Offline data also contains powerful signals and attributes that give critical context to what consumers communicate through their online behavior. This data is incredibly valuable for lower-funnel campaigns focused on conversion, where filtering out bad customers is just as important as finding new ones.

Imagine, for example, a consumer who loves looking at sports cars on the web. Just because she likes to look at Porsches doesn’t mean she can afford to buy one. Household income, financial health, household data, and current car ownership (all offline data) provide a more complete understanding of who is likely to be a good customer and who is not. These insights can be applied as a filter to existing campaigns across all channels to improve CPAs.

Target people and avoid bot fraud
Ad fraud is a real concern for digital advertising today. And while the proliferation of third-party verification technologies to confirm viewability and screen for non-human traffic (NHT) are fundamentally good for the overall ecosystem, they approach the problem of NHT from only one direction.

People-based targeting attacks the issue from another direction. Offline data is the foundation for these profiles and enables marketers to verify that they are targeting actual people before ads are served. People-based advertising is a simple solution that can reduce the wasted impressions served to bots by ten to twenty percent.

Reach the same audience everywhere
Consumers are real people, not just collections of browser histories. It is well understood that people use multiple channels and touch points to engage with your brand. Marketers struggle to reach the exact same audience across mobile, display, social, video, and now programmatic TV.

People-based audiences have the ability to reach the exact same profiles everywhere. Each profile is simply matched up with the appropriate channel identifier. Thus there’s no more guessing whether the audiences in two different channels are targeting the same people.

A consumer’s fit with a brand is based on many more factors than his or her online signals can possibly represent alone. Determining the right consumers with accuracy and scale comes down to understanding them beyond what the cookies can tell you. Offline data contains powerful signals and attributes that online behavior simply doesn’t.

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