Shop Talk MICROTARGETING
Explaining the “Dark Magic” of Microtargeting
Bryon Allen is the chief operating officer at Wilson Research Strategies, a Republican polling and targeting firm.
Joel Rivlin is director of analytics at MSHC Partners.
Andrew Drechsler works for Strategic Telemetry, one of the premier Democratic microtargeting firms.
Michael Meyers is a partner and president of Target Point Consulting, one of the first Republican microtargeting shops.
Four experts discuss the latest trends in the constantly evolving field of microtargeting.
C&E: Let’s start with where things are now. What are some of the capabilities you all are developing now?
Allen: Maybe it’s just because of where we are in the election cycle, but one of our biggest interests right now is a con- stant endeavor to push down the fun- damental insides of microtargeting and modeling to lower-level races. It’s always fascinating to look at where everybody’s coming from. The traditional pollster– media consultant relationship, in our opinion, needs to be just as strong, with pollster–mail, pollster phones, pollster direct voter contact, and that works well in a big race where you can afford your own microtargeting.
Rivlin: I get asked a lot, “How do you work with pollsters?” One of the sim- plest ways I like to answer is, we look through the other end of the telescope. The pollsters are more involved in mes- saging and working out exactly what the language is and what the landscape is. We’re more nuts and bolts, the people you need to speak to. We find that the data is not refined enough to get to the nuance of messaging, but the data can
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get to divisions that really speak to peo- ples’ big ideological breaks. One of the big repercussions of the 2008 election is that more people want microtargeting. There are a whole lot of people who worked on the Obama campaign—their first-ever campaign— who are used to seeing a model score on the voter file. They’re surprised to open a voter file and not see a model score.
C&E: Maybe you could expand on that a little for those who don’t know what a model score is.
Rivlin: Model scores come in a lot of different guises. There are models that do the clustering and divide the popu- lation into different categories. Another way of doing a model score is to give a predicted probability or a ranking of someone having a particular attribute. How likely are they to vote, how likely are they to vote democratic, how likely are they to have a particular issue? You know the way that these things have been increasingly used, is that people do a select on a list of people from age 35 to 47; you can say, I want a list of people that are 35-47 who are likely to vote. So
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