"Data Driven Thinking" is a column written by members of the media community and containing fresh ideas on the digital revolution in media.
Today's column is written by Ken Rona, PhD, V.P. Data Strategy and Client Analytics at [x+1].
Powerful predictors of likely relevance, broadly useful, for many users, simple, and standardized. All good. So, what’s the catch?
I can see three challenges on the demographic side of data. First, the cost to use demographic data has to be very affordable in order for ad networks and agencies to apply the data to all of their ad decisioning. Online data is not yet commoditized (in the classical sense), but I believe it will eventually become so.
Second, most companies don't yet know the number of unique users each data provider can reach. The value of each providers data is additive to the extent that they provide data on unique users. If they are not providing data on unique users, then the path to commoditization begins. The providers would be supplying the same product. By definition, the data would be a commodity.
Lastly, each of the data providers have varying degrees of accuracy. Online, it is difficult to assess accuracy. You need to find a source of “truth” and advertisers are often reluctant to share their verified customer files with ad networks. Some ad networks rely on straight lift to assess the value of a data set; they don’t worry about accuracy. The problem with this approach is it tends to be brittle. Data sources that have some level of accuracy are useful for a little while they are being used to target users that they can accurately associate to a given data element. Over time, their predictive power degrades. I am a big believer in taking the time and care to find data sources that accurately represent the users’ age, income, whatever. As the accuracy of your data improves, you can be more confident in the longevity of your targeting strategy.
One last point; Should the data providers worry about commoditization of demographic data? If I were them, I would not be losing any sleep over it. In this case, I think commoditization would be good for the data providers. They would get less money per user on any given transaction, but they would truly make it up in volume and because their product has zero marginal cost this is a good thing. In the offline world, that dynamic has played out to the benefit of Acxiom, Equifax, Experian, InfoUSA, etc.