Introduction to Data Advertising
New generation of audience targeting
For the last decade, networks have been offering different behavioral targeting solutions to advertisers to increase click through rates and overall campaign results. What we have been forgetting, however, is to bring the science into this data mayhem. It is a known fact that we have been accumulating an enormous amount of data for years but all of this data is raw. At Mediative, we feel that in order to make sense into all of this, we need to make a better job at qualifying human beings instead of computers (IP addresses).
Data Advertising is the science by which we predict online consumer profiles, intention to buy products and services, and future online/offline activities. This is now possible because of Data Management Platforms.
According to BlueKai.com, DMPs are “sophisticated data management platforms that allow publishers to get critical insights from both their own 1st party data and the 3rd party data. They enable publishers to better monetize and drive yield from their site audiences by enabling the creation of new lucrative audiences, and expanding reach of those audiences, on their own sites and across the web. By analyzing a vast amount of audience data in a DMP, publishers can more effectively segment inventory and obtain rule-based control over audience definition and ad distribution.”
Based on our Data adNetwork and Data adDirectories, we created profiles by combining data from our Data Management Platform (DMP) third party database, and geocoded consumer profiles. Our perspective is to move away from what we’ve always known as behavioral targeting and get into the next generation of data analysis and data targeting.
Our key differentiator in Data Advertising is the way we treat the information. Where behavioral targeting cumulates the number of pages a user has seen to define his enthusiasm towards a topic, Data Advertising analyses, compares and cross references different sources of information (online and traditional), to predict the human being’s behaviour behind the screen, and its intention to buy certain products and services. In addition, key learnings about cookies life spent enable us to bring Data Advertising in real time. According to contextual specialists “Behavioral targeting is certainly valuable. Knowing what a prospective customer has recently read, browsed, watched, and bought online is definitely useful. But all it illuminates is past behavior. (Why Context Is King in the Future of Digital Marketing February 02, 2012 by Jonathan Gardner)”
The combination of all those assets allows Data Advertising to be not only about past behaviour, but also about present behaviour and consumer activities. Now, as the database populates with more valuable information in respect with consumer privacy (follow our next post on privacy issues), the greatest challenge is to predict future purchases.
If you believe this is science
iction, it’s not. It is the combination of predictive mathematics, statistics and the Data Network.
Missed our Webinar on Data Adertising? We have it on-demand here.