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noi12.co/OnyC98. Managing your data. Trainer: Katie Ellis, NOI Facilitator: Deepa Kunapuli , NOI. Introductions. NOI O n Demand Norms Who’s on?. FOLLOWING THE LAW. Elections.neworganizing.com. FOLLOWING THE LAW. www.afj.org. Katie Ellis. Data Training Manager.
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Managing your data Trainer: Katie Ellis, NOI Facilitator: DeepaKunapuli, NOI
Introductions NOI On Demand Norms Who’s on?
FOLLOWING THE LAW Elections.neworganizing.com
FOLLOWING THE LAW www.afj.org
Katie Ellis Data Training Manager New Organizing Institute
In this session, you’ll learn to target effectively for local campaigns (with and without VAN), track and manage data, and measure your campaign’s progress over time.
The Problem: Messy Data • Building a Targeted Voter Contact List • Preparing Your Voter Contact Activity: What Data do I track? • Choosing Metrics and Measuring Progress • Q&A
Why do we need data? • Strategic Use of Limited Resources • Setting Strategic Goals & Maintaining Accountability • Demonstrating Success & Power
Why do we need data? • So we can USE it!
What are the two types of programs campaigns run? • Persuasion • GOTV (Get Out the Vote)
You need data to use data! • You can’t GOTV your supporters if you don’t know who they are! • You can’t make decisions about your programs if you don’t know how it’s going.
Your data needs to be useable • Not like this:
Your data needs to be useable • But like this! • Standardized! • Clean! • Can be aggregated, analyzed, and filtered!
The problem: recap • Data helps you make key decisions about your campaign • But your data has to be standardized in order to use it effectively!
Why do we need data? • Strategic Use of Limited Resources • Setting Strategic Goals & Maintaining Accountability • Demonstrating Success & Power
Money Time Limited resources People
The targeting matrix 1 2 1 1
OK, this sounds great, but how do I know which voters are “sporadic turnout base” or “high turnout persuasion”?
Will they support me/my issue? Will they vote? Vote History Modeling Voter Registration Factors to use in creating universes • IDs • Party (do they vote in primaries?) • Models • Family & Friends • Family & Friends of Family & Friends • Issue activists • Natural constituencies • Census Data
Examples: (Democratic local candidate) • High Turnout Persuasion: • High Turnout: • Voted in 2008 and at least one of 2006 or 2010; OR • Registered since 2008 general election • Persuasion: • Identified “3’s” • Independent or Unaffiliated Voters • Democrats who don’t vote in primaries (last 3 years)
Examples: (Democratic local candidate) • Sporadic Turnout Base: • Sporadic Turnout: • Voted in only one of these three elections (2006, 2008, 2010); OR • Registered since 2010 general election • Base: • Identified “1’s” and “2’s” • Democrats who vote in primaries (last 3 years) • Constituency Groups: • If candidate is a union member, then other union members • If candidate is a teacher, then other teachers
Examples: (civic engagement effort to turn out young women) • Sporadic Turnout Base: • Sporadic Turnout: • Voted in one of these three elections (2006, 2008, 2010); OR • Registered since 2008 general election • Constituency: • Women • Ages 18-35
What do these universes have in common? • They are very specific • Criteria exists in a voter file (VAN or State File), or can be tracked One more point… • You can narrow or expand your universes based on your capacity (how many volunteers you have)
Other Toolbox modules • GOTV Planning 1 • How do I figure out my volunteer capacity? • Vote Goals & Targeting • How many votes do I need to win? • Who do I target? • How do I construct a program? • VAN 101 • How do I run complex searches in VAN? • Grassroots Targeting • How do I search for specific voters in an Excel file?
targeting: recap • Campaigns have limited resources and need to use them effectively • Clearly define your universes so you can find those voters in VAN/Excel
Preparing your voter contact activity: what data should I track?
SCRIPTS = text + codes Hi, is this __(voter name)__? My name is ____ and I’m volunteering with ____ campaign.
Canvass results PART 1: NO RESPONSE Left Message Not Home Wrong number/address Deceased Refused Inaccessible
Successful canvass! PART 2: CONVERSATION Support Score, 1-5 Will vote (Y/N/M) How (Early/VBM/EDay) Volunteer (Y/N/M) Activist Codes
Tracking data: recap • Define what you need to know for your program. • Standardize, standardize, standardize! • Toolbox: • Excel List-Cleaning
What’s a metric? • A metric is anything you can measure! • Toolbox: • Campaigning to Engage and Win: A Guide to Leading Electoral Campaigns
SOFT REPORTING HARD REPORTING Results attached to names (volunteers, supporters, donors, registrants) Long term strategic resource allocation Verify soft reporting, increased accountability Collect data • Organizers and volunteers self-report • Quick allocation of resources • Day-to-day accountability • Narrative feedback from the front lines
SOFT REPORTING Collect data • Fast • Accountability
SOFT REPORTING HARD REPORTING Results attached to names (volunteers, supporters, donors, registrants) Long term strategic resource allocation Verify soft reporting, increased accountability Collect data • Organizers and volunteers self-report • Quick allocation of resources • Day-to-day accountability • Narrative feedback from the front lines
HARD REPORTING Collect data • Have to do data entry • Allows for deeper analysis
Metrics: recap • The more you know, the more you can proactively make decisions to keep your campaign on track
The Problem: Messy Data • Building a Targeted Voter Contact List • Preparing Your Voter Contact Activity: What Data do I track? • Choosing Metrics and Measuring Progress • Q&A