Sue: Harvesting of voter data, what worked and didn’t?
Ben: On the GOP side, for almost any GOP campaign, there’s a narrative who’s ahead or behind on digital? Now, the GOP feels pretty good where we are. The real act is encouraging all campaigns to use data trust. From elections local and across the country, bring in more people. We feel good about the quality of data, use new ways to bring in new information.
Pamela: This cycle, there was never a single race that we didn’t use more than one set of data. When we’re thinking about what we’re going to use, thinking about what make most sense. When we know there are traps with certain data sets, use other targeting methods. Holisitic in that sense.
Phil: The reliability of data for modeling became reliable. Suburban GOP women pro second amendment and pro assault weapons ban, for example. Helps us drill down on these targets. Go from target universe to turnout universe.
Sue: Modeling data. Voter file is not the key, it’s the modeling data. How quickly do you turn to that?
Phil: On GOP side, with organization we work with, voter file is foundational. All the layers, modeling, data points that flow in make then greater indicators. Availability of data lain on top of the voter file has changed the game.
Ben: understanding how people are going to behave is a starting point at beginning of cycle. GOP Gov. Assoc. looking at 2017 results. See how turnout differed from polling. Going into 2018 with polling, focus groups looking closely at data. What were we accurate about, wrong about? 36 gov elections in 2018. Are we informed? Starting point on how to allocate funds.
Sue: Voter file, programmatic data talk to each other well. But what about walled gardens? Frustrations?
Pamela: About voter file, modeling, we use that as a base line. Built our way up from that. Walled garden will be increasingly problematic as regulations increase. How are we weighting data sets to modeling to ZIP codes and other forms?
Ben: You can’t just send them a list of voters and say we want to hit these people. Force view audio, list of voters, doesn’t mean you can’t break them down via ZIP codes, male vs female, HHI, age. By understanding what the list looks like, you can find the most effective counterpart that the system does allow. We would try to find universal targeting options.
Phil: Data is their to serve me. Sometimes you have to use what’s available in that platform. So many factors go into deciding how and when I’m going to target, which list. Touch and go based on a series of factors, geography, time, budget.
Sue: How to answer the question, “What’s the frequency?” How do you know it’s too much or not enough?
Pamela: we’re going to have to address. Curious to see role of first party data. How we’re tracking pixels.
Sue: Native data. Preferences? Successes? Failures?
Ben: positive on in-platform data. How well they know the users. Trust but verify. They have most access to information. Might know who’s on their platforms through their targeting tools. They have every incentive make native targeting tools the best. Less interested in having third party data imported to them. They’d rather you use their inhouse targeting. Using Live Ramp, but match rate can often be low as 30%. Or could take a week to onload. Google says they know how to find people who care about X, pretty reliable.
Pamela: I agree. Absolute share FB, Google have in terms of data, they have more points, in the business of data, why not use or continue to engage in that platform data. We engaged in a lot of lookalike models this cycle.
Phil: I am expensive data addict. Gives me a strategic advantage. I work with small dollar campaigns, too. Best data they can get a hold of is first party data. Not losing anything by using that data. It’s about not being dogmatic with platforms, use common sense.
Ben: Most campaigns are surprisingly small. Lot of pressure to put on them to say you have to have data. Makes things a lot easier, efficient to use data from places like Verizon, etc.
Phil: My only problem with first party data is the sensibilities of companies collecting it. Not every point is available. Kind of at the whim of FB, sometimes important to know who you’re targeting.
Ben: This last year, lot of FB, Google changes came in. Some states have significant restrictions demanding transparency. FB rolled out a lot of changes. The people who would be most opposed say the secrecy is gone. We don’t want digital to be a surprise attack. Traditional platforms upset that secrets would be made public. Horse race mentality in TV comes to digital.
Pamela: In re transparency reports, every cycle we go through learnings with various platforms. A lot of things ruled out. I have found it’s been pretty exciting. Always be very nimble in that regard. We are at the Whim of some of these platforms. Have to move and change quickly. As to walled gardens, number of shifts made regarding first party data. need to be cognizant of.
Phil: it just made me more creative in how I approach a race. Life finds a way, we’ll get around it. Everything we put out there can be seen at some level. We don’t want to be part of the news cycle.
Sue: Keeping, retaining talent in this field. What do you look for in your team members? How to keep them?
Phil: This is a big deal for me. When I try to hire somebody, I’m looking for someone who just won’t bullshit me. As long as you’re telling me the truth, we can navigate an election cycle. You’ve got to pay them well. I want people who will stick with me cycle after cycle and learn with me.
Pamela: Talent is tough. Our approach is getting fellowships, building more infrastructure, creating space for digital. As those conversations continue to grow, talent will as well. It’s not always someone with the most prolific background, experience. Things change in digital so fast, you want to work with nimble people who question their own assumptions.
Ben: Recruiting is one of the most important roles. People are passionate about the success of the project, what type of people get elected to office. You have people who really care in a way that’s hard to find in a non-political space. Digital teams working in a lot more complexity. Making sure there is morale, buy-in among the teams. More good partnership, the more you can have a good team. A lot of knowledge about digital is hard to replicate.
Phil: My team knows their institutional knowledge is irreplacable.
Pamela: Hard to bring someone in from scratch.