Our segmentation methodology is based on neighborhoods, which means we do not segment data by age or gender. However, we have found that stereotypical targeting, such as using gender, is mostly only useful in certain cases for high-involvement products. When it comes to age, the closest we can get is segmenting users based on “lifecycle”. These audiences differentiate internet users into groups ranging from “Young couples and singles” to “Pensioners”. This approach allows us to offer effective targeting options based on lifestyle and behavioral patterns rather than just demographics.

In Digiseg we segment neighborhoods, an approach that by nature is probabilistic. When you select an audience in our Audience Builder, some users will have the right characteristics while others may fall outside of your targeting criteria. That’s why we display the accuracy of your selected audience in two columns: In-Target Reach and Excess. In-Target Reach represents the number of users who fall within your specified audience criteria, while Excess represents the number of users who don’t. Together, these two columns make up the Total Segment Reach.

It is possible in certain platforms, Adform for example. For combining audiences, contact support@digiseg.io.

This is a list of our primary data sources: National Statistical Offices.

Xandr’s Data Marketplace uses cookies to measure reach of audiences, but as Digiseg is cookie free, all Digiseg audiences are displayed without reach numbers. But rest assured, there is reach behind the audiences. Digiseg segments more than 500.000 bid requests per second in Xandr. We are probably the largest data provider in Xandr, based on segmented impressions.