How Bonnie Watson Coleman Overcame The Odds And Won Her Primary Using Microtargeting

Bonnie Watson Coleman and Alan Grayson

Barbara Buono, the stalwart progressive who took on Chris Christie— and the corrupt New Jersey Democratic Machine— introduced me to Bonnie Watson-Coleman, a stalwart, principled and courageous legislator who stood strong for Barbara when other Democrats were hiding under their desks, afraid of Christie and afraid of the slimy Democratic bosses. I met Bonnie at an Alan Grayson rally in New York and Blue America endorsed her and helped her raise some money. After she overcame consider odds against a the “other” kind of Democrat, one who wouldn’t help against Christie or go up against the bosses, and won the primary, she has a relatively easy glide into Congress. NJ-12 (Trenton up through East Brunswick, Plainfield and Middlesex) is a safe Democratic seat with a PVI of D+14. President Obama beat McCain 230,899 (66%) to 103,322 (33%) and did slightly better against Romney in 2012. No outside parties are involved in the race and Bonnie isn’t facing a serious challenge from Republican Alieta Eck. As of June 30, the last FEC fundraising deadline Eck had raised $137,720 and Bonnie had raised $488,720.

She’s running her campaign the same way she ran her career— as a principled and unabashed progressive who puts working families first. Yesterday, for example, she addressed gun control— and not in the way the DCCC recommends. “We have a responsibility to take action to ensure our neighborhoods are safe, not just for today, but also for future generations,” she said. “Preventing gun violence through common sense gun safety reforms is a critical component of any plan to effectively protect all of our communities. If elected to represent the Twelfth Congressional District on November 4th, I will work to pass stronger gun safety laws at the federal level, including requiring comprehensive background checks and a ban on assault weapons and high-capacity ammunition clips.”

This week Sherrie Presische of FiftyOne Percent wrote a fascinating insiders look at Bonnie’s primary victory for Campaigns And Elections, Obama-Style Modeling Down The Ballot. When the primary began, no one foresaw a 15 point win for Bonnie; everyone foresaw an easy win for her hackish opponent, state Sen. Linda Greenstein. Preische credits microtargeting of voters with turning the race around. “We did it,” she wrote, “by focusing on a narrow communications and voter contact program governed by the targeting. We’ve seen how national and statewide races benefit from individual voter modeling. We show here that microtargeting, like President Obama’s campaign put in practice in 2012, is now affordable in smaller-budget and down-ballot races.”

Being an African-American candidate in a majority white district is a challenge in its own right, so putting together the right team was crucial. Watson Coleman realized early that to win she needed to raise money and run a very focused and disciplined campaign.

The team was led by long-time Watson Coleman strategist James Gee. The campaign manager was Adam Steinberger, who had just run Sen. Robert Menendez’s field program. The team also included Holt pollster Fred Yang of Garin Hart Yang Research Group. Longtime New Jersey communication operative Sean Darcy did the direct mail and earned media, John Rowley of Tennessee-based Fletcher Rowley provided the TV and online media. My firm, FiftyOne Percent, did voter models and analytics.

Watson Coleman began the race 10 points down in Greenstein’s internal poll, which was released publicly. As a result, the political “talking class” gave our candidate little chance of winning. Greenstein is a tenacious campaigner and initially had the support of many of the political leaders in the district. There are more registered Democrats in the Middlesex County portion of the district where she lives, and millions of dollars had been spent in her recent state races. PolitickerNJ, New Jersey’s premier political news website, ran analysis after analysis showing the invincibility of Senator Greenstein.

Still, our modeling of the district and our polling clearly showed a path to victory as long as we stayed focused and disciplined with our message and communications universe. This gave our communication team, headed by Darcy, a former staffer of Gov. Jon Corzine (D), the ammunition it needed to chip away at the media’s perceived view of the race. It also helped to bring early support from the Progressive Change Campaign Committee and Laborers International Union, critical early endorsers of the campaign, and to drive the all-important fundraising effort as more and more people came to believe that Watson Coleman could win.

Understanding the challenges in this election, the Watson Coleman campaign invested early not only in a poll but also in a voter model to catalogue those who would support her, those who could be persuaded to support her, and those who were likely never to support her in the primary.

A microtargeting voter model gathers large amounts of data about each person to gauge the likelihood of their behavior. For each voter, that data includes not only their own demographic and voter history, but also things like estimates of income, education level, and particularly consumer behavior. It’s the same type of information that Google and others are using each time you see an ad online that you know has been tailored to you and your interests.

Back in 2012, a combination of campaign contacts, internal polling, past records, and consumer data allowed Obama’s GOTV team to create the best door-to-door interactions with voters when they canvassed. Those interactions went back into the campaign’s database after individual door-to-door conversations and then their microtargeting models were refined based on that information.

To build the support model in our case, we used not only our internal polling but also additional phone support surveys, historic voting behavior, and IDs the campaign has made by phone and door-to-door canvassing. All of this is used to estimate the individual likelihood that each particular voter will support our candidate or not.

As a new campaign tool, a microtargeting model can be difficult for some candidates to wrap their heads around because it’s difficult to see. This is not broad-based “targeting” such as women in their 30s or some other demographic that many people say they do. The key is that microtargeting is specific to each person, because each person has different interests and behaviors.

We know that voters can behave differently as they move down the ballot to different races. An area that might be reliably Democratic at the federal level may also lean Republican down the ballot at the county level. Likewise, primary voters behave differently in different elections depending on the candidates. Therefore, having a model specific to the race you’re running is critical in close elections.

While support models in general elections are usually dominated by the partisan behaviors of each voter, in a primary, with little space between the candidates on issues, we had to find the many other factors driving voter decisions. Some support factors were well understood by all candidates; particularly that each of the state legislators in the race had his or her own geographic regions of support. But even within these regions, our support model could tell us which particular voters might be more open to our candidate. Each voter was given a support score, representing the likelihood of that voter supporting our candidate.

We also had a model for individual voter turnout in this primary election. Recent Democratic primaries had been uncontested, so we expected higher turnout than in recent primaries for this contest. The challenge was to figure out who the extra voters would be. Partly because primary voters are pretty dedicated voters anyway, our turnout model brought out nuances in people’s voting behavior in primaries. It allowed us to see not only the voters who vote in every primary, but also a second set of voters who would be the easiest to move to the polls, voters who might not vote but whom we needed to pull out to win.

Normal turnout for a Democratic primary in this district is between 15,000 and 27,000 voters.  But our model showed that if all sides inspired their voters to come to the polls, we might expect higher turnout— up to 44,000 voters.

Combining support and turnout models showed us exactly which voters we needed to reach out to with a persuasive message, which voters we shouldn’t talk to at all, which extra voters we needed to pull out, and which voters we were confident would come out for Watson Coleman. This allowed the campaign to come up with a win scenario based on real numbers and individual voters. It also allowed our field program, mail, and media buys to focus on the select group of voters who were most important to winning.

The model informed every aspect of the program. While it was an up-front investment, it allowed the campaign to use all its resources—the candidate’s schedule, volunteers’ time on the phones and on the streets, and paid media— most effectively.

The model identified more than 42 percent of the probable primary voters who we knew would likely be supporting one of our opponents and another set of voters who would likely come out and vote for Watson Coleman if we did nothing. This allowed the campaign to concentrate its resources— money and time— on the select group of primary voters, persuasion and pull targets, who we knew were going to make the difference in this race, with a message tailored to their interests.

For the model to be the most useful, it needs to be more than just an analysis of the numbers and a score assigned to each voter in the database. Having the campaign and political experience to know what the numbers tell us about voter behavior, and how the campaign can best deploy the model, is critical to making this tool most effective.

Although Greenstein and Chivukula had significant TV buys, the model allowed Rowley and Darcy to focus 100 percent of our paid media, TV, and mail in our top persuasion areas. All of our online pre-roll ads were directed to townships and areas that were our top persuasion and GOTV targets. Rowley also integrated the model into the online advertising campaign, targeting specific voters to receive pre-roll video ads.

While we were outspent 7-to-1 on paid media, the model identified the individual voters we needed to reach. We repeatedly communicated with this select group of voters who we knew would make a difference in the election. As the primary vote approached, we needed to expand on our initial support model.

We conducted an IVR (interactive voice response) support survey about a week before the election and integrated the results with our turnout model and the voter IDs the campaign identified through its phone and direct voter contact program. That allowed us to create a GOTV model and refine our categories of voters. The campaign was then able to prioritize its GOTV program and resources for those extra voters we needed to win: those most likely to support Watson Coleman but who needed a little extra incentive and reminder to vote.

Two weeks before the election, a public poll was released from Monmouth University showing Greenstein and Watson Coleman essentially tied at 25 percent and 24 percent respectively, with 11 percent and 6 percent for Chivukula and Zwicker.

Often in these types of elections voters are somewhat hardened in their positions, and the universe of voters who can actually be persuaded is small. It can also be expensive to earn a vote through persuasion. Persuasion is the most expensive communication of a campaign. Limiting that universe to those most likely to be persuaded more than pays for the cost of modeling. That’s why broad TV buys in a race like this can be less effective. In addition to our persuasion universe, our model also identified people who might not be regular primary voters but who would be relatively easy to turn out with a pre-GOTV and GOTV program. We focused a lot of attention on energizing them. The result was that the political establishment was shocked by the large turnout in support of the perceived underdog.

The final tally was 43 percent for Watson Coleman and 28 percent for Greenstein, with Chivukula taking 22 percent and Zwicker 7 percent. And more than 36,000 people voted. The Watson Coleman team had identified and communicated effectively with the right voters.

There’s an adage that repetition is the key to victory. That continues to be true, but with voter analytics and modeling we can now target the individual voters that matter most, giving campaigns more repetitions without much additional cost. A voter model is a wise investment even for down-ballot races. It’s a small fraction of the campaign’s budget, but it makes the overall program more effective and efficient, and it ensures the communications and field operations are targeted to the voters who will make a difference on Election Day.

Bonnie Watson Coleman is one of the brightest spots in the 2014 congressional cycle. She should be an important leader inside the House Democratic Caucus, the Congresssional Black Caucus and the Congressional Progressive Caucus. If you’d like to contribute to one of the best functioning Democratic operations in the country, you can do that here on the Blue America ActBlue page.