CSY-022. A data analysis and presentation on targeting voters in a political campaign.

PROJECT COMPLETED: August 2021

Florida Congressional District 27 Voter Targets | Data Visualization by David White

Florida Congressional District 27 Voter Targets | Data Visualization by David White

THE STORY OF THIS PROJECT

I completed the Arena Academy in June 2021. Arena Academy is a bootcamp-like training program for aspiring political campaign professionals. The program provides immersive, hands-on training in seven different tracks: Campaign Manager, Communications Director, Data Director, Digital Director, Finance Director, Organizer, or Organizing Director. I completed the Data Director track.

As a capstone project, the participants are divided into teams comprised of one member from each of the seven tracks. The team is tasked with designing a winning strategy and presenting their campaign plan to a panel of expert judges. Our team was assigned a hypothetical challenger, running against against a real-world incumbent in Florida’s 27th Congressional District. I used simulated VAN voter file data to help develop our team’s finance, organizing, voter registration and turnout goals. For our final presentation, I created a data dashboard that illustrated our voter targeting strategy. (Following Arena Academy, I made further revisions to my dashboard based on the feedback our team received from the panel of judges.)

Here’s the design process I used to complete this project—

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Case Study 022. Voter Targets Dashboard: Step 1
CSY-022., Arena Academy
CSY-022., Arena Academy

Step 1. Discovery

My very first step was to gather background information on the district and flesh out my ideas for what a winning campaign strategy might be.

CSY-022., Arena Academy
Case Study 022. Voter Targets Dashboard: Step 2
CSY-022., Arena Academy
CSY-022., Arena Academy

Step 2. Sketch

Next, I made a rough sketch of how the various segments of data relate to each other. I wanted to target voters by focusing on where certain segments of voters intersect.

CSY-022., Arena Academy
Case Study 022. Voter Targets Dashboard: Step 3
CSY-022., Arena Academy
CSY-022., Arena Academy

Step 3. Prep Data

Then, I wrote SQL code to:

  1. Pull and combine voter data stored in different locations

  2. Filter the data by my campaign’s congressional district

  3. Group voters into buckets by age range

  4. Assign tiers to voters based on their attributes and voting records

CSY-022., Arena Academy
Case Study 022. Voter Targets Dashboard: Step 4
CSY-022., Arena Academy
CSY-022., Arena Academy

Step 4. Build

I took the output of the code I wrote in step 3 and I connected it to Google Data Studio. Inside of Data Studio, I built out an interactive data visualization which highlighted our voter targeting strategy.

CSY-022., Arena Academy
Case Study 022. Voter Targets Dashboard: Step 5
CSY-022., Arena Academy
CSY-022., Arena Academy

Step 5. Publish

I published the final report to the cloud using Google Data Studio and I used screenshots from the dashboard to create slides used in our presentation.

CSY-022., Arena Academy

Final Results:

 
case studies, data visualizationDavid WhiteGoogle Data Studio, SQL, Google BigQuery, dashboard

3. Work Samples - Content | Work samples of data visualizations, data dashboards, websites, infographics, publication-quality reports, slide decks and visual presentations I've created (detailed)