<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<?xml-stylesheet type="text/xsl" href="../part2stratml.xsl"?><PerformancePlanOrReport><Name>About Valor America</Name><Description>THE SOLUTION -- We combine randomized-controlled trials (RCTs) and machine learning algorithms to identify winning messages and persuadable voters. Only an RCT can tell you what works and what doesn't. Then we head into the field with ads online, in the mail, or the air to make sure those voters move the way we want them to.We use unique online survey samples that are pre-matched to an augmented voter file, which contains over a thousand data points about each voter. We identify the precise impact that a policy position or message has on outcomes and identify which voters are moved most using a toolbox of artificial intelligence/machine-learning techniques and cross-validation to ensure predictive accuracy.We train a machine learning algorithm using the data gathered in the clinical message trial on each of the research subjects: the algorithm learns to predict the message's impact on every registered voter in the state or congressional district, using hundreds of features from an augmented voter-consumer file. We then used this trained algorithm to predict the messages' impacts for every registered voter, resulting in a list of the most persuadable/moveable voters.</Description><OtherInformation>THE PROBLEM -- How do you win elections? You persuade more people to vote for your candidate, and turn out more of your supporters. But how do you know what messages and tactics will persuade and turn out more voters?Most organizations just go with their "hunch," their best guess based on what they think worked before. Sometimes they do research. But focus groups, or simply asking respondents what they think, for example, doesn't work. Why? People are terrible at introspection and self-prediction.You can't measure the effectiveness of a message by asking a voter if she thinks a message will change her preferences. She doesn't know. We have to observe how a message impacts preference distributions in a treatment group compared to a control group.</OtherInformation><StrategicPlanCore><Organization><Name>Valor America</Name><Acronym>VLRA</Acronym><Identifier>_9f2275ca-0c0a-11eb-bb71-3d033183ea00</Identifier><Description/><Stakeholder StakeholderTypeType="Person"><Name>Joe Arlinghaus</Name><Description>President &amp; Founder -- Joe got involved in Republican party politics in the mid 80's in high school in Michigan. In 1987 and 1988 he walked door-to-door in the snow for Jack Kemp in New Hampshire. In 1992, he was a staff member in the Buchanan for president effort in the New Hampshire primary. Much of his experience has been in support of pro-life charity efforts also. In 2014 he accepted a challenge from the political team of Greg Abbott in Texas to find ways to win voters away from the Democrats using abortion messaging. In searching for a way, Joe met Dr. Adam Schaeffer and a long partnership began.</Description></Stakeholder><Stakeholder StakeholderTypeType="Organization"><Name>Evolving Strategies, LLC</Name><Description>Research Engine -- Evolving Strategies is the research engine driving Valor America's election efforts. ES is a behavioral science firm in the Washington, D.C. area that serves both political organizations and businesses. The firm helps clients modify human behavior using clinical trials and machine learning. We get more people to do what you need them to do.</Description></Stakeholder><Stakeholder StakeholderTypeType="Person"><Name>Adam Schaeffer</Name><Description>Adam Schaeffer is Founder and Chief Behavioral Scientist at Evolving Strategies. He has a Ph.D. in Political Science with a specialization in political psychology and behavior from the University of Virginia and an M.A. in Social Science from the University of Chicago. Alex Oliver is Chief Data Scientist at Evolving Strategies. He has a Ph.D. in Political Science with specializations in quantitative methods and American politics from Boston University, an M.A. in Economics from Tufts University, and a B.A. in Economics &amp; Mathematics from Merrimack College.</Description></Stakeholder><Stakeholder StakeholderTypeType="Organization"><Name>Republican Party</Name><Description>Our specialty is discovering and investing in strategies that the Republican Party and establishment consultant class don't see. We can do that because we use gold-standard testing and state of the art machine learning techniques to make sure we'll get a return on our efforts. </Description></Stakeholder><Stakeholder StakeholderTypeType="Generic_Group"><Name>Valor America Clients</Name><Description>THE RESULTS -- We’ve conducted over a dozen experiments across five states in the last five years, identifying messages that work, and the voters we know we can move.We helped Kevin Cramer win in North Dakota, Mike Braun win in Indiana, and Josh Hawley win in Missouri. We moved targeted voters by close to +10 points in the Michigan Senate race – a winnable race had the funds been available.We develop creative messages on a range of topics, but test them to make sure they will work. Sometimes, we find they don’t, or that a race isn’t worth investing in. For instance, we ran randomized-controlled message trials and modeled voters in Pennsylvania in 2018, but found the messages weren’t moving enough voters and the race was too far gone.Knowing what not to do is a critical part of making an impact. Knowing that an ad will work gives us the confidence to go all-in. That makes us efficient and effective with investor funds.And as a result of our efforts, we’ve built a data and knowledge for key 2020 battleground states like Pennsylvania and Michigan.</Description></Stakeholder><Stakeholder StakeholderTypeType="Person"><Name>Kevin Cramer</Name><Description/></Stakeholder><Stakeholder StakeholderTypeType="Person"><Name>Mike Braun</Name><Description/></Stakeholder><Stakeholder StakeholderTypeType="Person"><Name>Josh Hawley</Name><Description/></Stakeholder></Organization><Vision><Description>More people to do what you need them to do</Description><Identifier>_9f2276f6-0c0a-11eb-bb71-3d033183ea00</Identifier></Vision><Mission><Description>To use testing and machine learning to get a return on our efforts</Description><Identifier>_9f2277a0-0c0a-11eb-bb71-3d033183ea00</Identifier></Mission><Value><Name/><Description/></Value><Goal><Name>Political Research</Name><Description>Carry out a political research strategy</Description><Identifier>_9f227872-0c0a-11eb-bb71-3d033183ea00</Identifier><SequenceIndicator/><Stakeholder StakeholderTypeType="Organization"><Name>Pennsylvania</Name><Description/></Stakeholder><Stakeholder StakeholderTypeType="Organization"><Name>Michigan</Name><Description/></Stakeholder><Stakeholder StakeholderTypeType="Organization"><Name>Wisconsin</Name><Description/></Stakeholder><OtherInformation>THE 2020 ELECTION IS CRITICAL.There is no way around it – 2020 will not be easy to win. That's why we're launching a unique and powerful research strategy for 2019. We have a large knowledge base about the upper Midwest and working-class voters that we will expand on in 2019/2020. If President Trump keeps the states he won in 2016, but loses Pennsylvania (won by +1.2 points), Michigan (won by +0.3 points), and Wisconsin (won by +1 points), we lose. If Trump wins just one of those states, we win. We will be launching a tracking poll and series of experiments for these three crucial states that will provide us with the most powerful, detailed voter data ever seen. We will test messaging as we go, and continually update our machine learning algorithms to precisely predict which voters need to be persuaded, kept on the team, or given extra encouragement to turn out and vote. You can be a part of winning 2020. And as we update our knowledge about these voters, you will have access to the most exclusive and sophisticated information about 2020 there is. </OtherInformation><Objective><Name>Polling &amp; Experimentation</Name><Description>Conduct a tracking poll and series of experiments for these three crucial states that will provide us with the most powerful, detailed voter data ever seen</Description><Identifier>_9f22791c-0c0a-11eb-bb71-3d033183ea00</Identifier><SequenceIndicator>1</SequenceIndicator><Stakeholder><Name/><Description/></Stakeholder><OtherInformation/></Objective><Objective><Name>Learning &amp; Messaging</Name><Description>Test messaging and continually update our machine learning algorithms to precisely predict which voters need to be persuaded, kept on the team, or given extra encouragement to turn out and vote</Description><Identifier>_9f227a0c-0c0a-11eb-bb71-3d033183ea00</Identifier><SequenceIndicator>2</SequenceIndicator><Stakeholder StakeholderTypeType="Generic_Group"><Name>Voters</Name><Description/></Stakeholder><OtherInformation/></Objective></Goal></StrategicPlanCore><AdministrativeInformation><StartDate/><EndDate/><PublicationDate>2020-10-11</PublicationDate><Source>https://www.valoramerica.org/about-us</Source><Submitter><GivenName>Owen</GivenName><Surname>Ambur</Surname><PhoneNumber/><EmailAddress>Owen.Ambur@verizon.net</EmailAddress></Submitter></AdministrativeInformation></PerformancePlanOrReport>
