I was surfing around on AdBrite’s web self-service tool, checking out how similar it is to BidPlace SB in many ways, and I noticed that they offer gender targeting. Gender targeting is fantastic for advertisers that value it, but what AdBrite offers seems to good to be true. And you know what they say about things that seem to good to be true!
If AdBrite tells you they have 22k imps available for a given target, selecting a specific gender perfectly splits the impressions. So the sum of male and female impressions equals 100% of the total impressions. While this may seem obvious and appropriate to a casual onlooker, what is insane about this is that it implies that they actually know the gender of single one of their impressions. That is simply not possible at scale. What is AdBrite doing here? No way to know, but it is clearly inaccurate.
Furthermore, they offer the same segmentation for their “Age” targeting. How can AdBrite know the age of all of the web visitors generating their acquired impression volume? They cannot.
Here is what they say about how they do it:
Demographic targeting works from user profiles built up over time, based on the websites that users have visited and spent time on in the past. The ability to use demographic targeting for a campaign applies to ads served worldwide.
AdBrite’s Open Targeting Exchange (OTEx), the internet’s first open exchange for ad targeting technologies, sharpens the effectiveness of demographic targeting. OTEx brings multiple third-party targeting providers into the marketplace—that means a higher yield and greater effectiveness for your campaigns. OTEx automatically finds the demographic targeting technology that will work best for your campaign.
Does that sound like they know the age and gender of everyone on the Internet? Nah.
I know I blogged a long time ago about how uninteresting bitching about things you saw on the web is, but that is who I am. Sorry!
Update: The next day, the New York Times did a nice article about data exchanges (which I have previously discussed are a hard sell). Two things were noteworthy:
- Stephanie makes Data Exchanges sound so reasonable. And admittedly, they sound like such a slam dunk, everyone is starting one. Alas, as I discuss, I think when you dig in, going from generating a lot of revenue to generating a lot of profits is really hard with these businesses.
- Stephanie indicates that Blue Kai has “determined” that she is a male. Woot?