Predyctive Programmatic Marketing: How Offline Data is The Joker In The Pack Of Digital Marketing
Offline Data In Programmatic Marketing Helps Target The Perfect Audience Based on Real Time Searches & Behaviors
Is it possible that offline data could wind up being the dark horse of programmatic marketing? It certainly is the age of Big Data, and the repercussions for marketers are nothing short of substantial. No matter how much data there is about online behavior, and definitely irrespective of the sophistication of analysis surrounding it, what consumers are doing online is just the tip of the iceberg. Crucial insights into the identity of consumers and the paths they take to purchase things exist in the seemingly endless volumes of offline profile data, which cookies just can’t usually reach. Understanding the lifestyle choices, financial means, and information of consumers and households can dramatically improve the ability of marketers to learn more about what can work out right for them. It can even help marketers to fight fraud and reach out to identical audiences across multiple platforms. In short, offline data is a crucial part of getting Big Data to work out for marketers.
Focusing more on the best consumers
Predyctive uses offline data which is something that should not ever replace online data, but it can help manage the existing limitations of doing targeting just based on what cookies provide. Cookies can be a useful way of targeting consumers just on their real-time activity. However, cookies capture only so much data, roughly 50 data points for each average cookie. Also, cookies have a lifespan of only a week or two, which seriously restricts their scale. When you do cookie targeting, you only get limited data providing a fleeting glimpse of your customers. On the other hand, offline data proves to be a stable and reliable stream of data with much more lifespan. Covering more than 9 in 10 American consumers, offline data source are aggregated into thousands of individual data points. The consequence of all this is a massive spread of data, then when analyzed properly, can help you find potential prospects which were missed by online signals.
Improve CPAs by filtering out the wrong consumers.
Offline data is also advantageous in how it incorporates powerful attributes and signals that give you essential context about what consumers are communicating through their behaviors and actions when online. That data proves tremendously beneficial for any lower-funnel campaigns that are emphasizing conversion, where filtering out bad customers is just as crucial as discovering new ones. Consider for instance a consumer that loves looking up sports cars online. Even if she likes looking at Porsches, it doesn’t actually mean that she has the money to actually buy one. Household data like income, current car ownership, and financial health are all offline data, and they provide you a more comprehensive view of who might be a good consumer and who isn’t worth your time or trouble. You can apply such insights as a filter to your current campaigns in all channels so that you can improve your CPAs.
Target individuals to avoid bot fraud
Ad fraud is sadly a real worry in modern digital advertising. The total ecosystem has benefited from the proliferation of verification technology that confirms viewability, even screening for non-human traffic or NHT. However, they only come at this issue from one point of view. Another possible angle is targeting attacks based by people. Offline data proves to be the basis for such profiles which empowers marketers to verify that they are targeting real people prior to any ads getting served. Programmatic marketing that is people-based proves to be a simple answer that reduces impressions wasted on bots by as much as 20 percent.
Reach out to a similar audience everywhere
Consumers are actually people and not just accumulations of browser histories. It’s well-known that consumers use many channels and various touch points when they engage with a brand. As such, marketers often struggle to reach out to the exact same audience across video, social, display, mobile, and programmatic television. An audience based on people has the power to reach out to identical profiles in all places. Every profile just gets aligned with the proper channel identifier. You no longer have to guess about audiences from distinct channels since you’re targeting the very same people. How a consumer fits within a particular brand is going to be based on multiple factors, and more than can be represented by their online signals. Figuring out who the right consumers are with scale and accuracy really boils down to learning far more than just what their cookies can tell you. Offline data has robust attributes and signals which online behavior just doesn’t, but programmatic marketing needs all the help it can get.
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