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The Reality of Localizing Strategy
All politics is local…or so it is believed! The democratic process during local elections is expected to reflect the aspirations of all demographic groups in a constituency and be influenced by the needs of the constituents at a grassroots level. In reality, it is not easy for campaigns to target specific demographic groups and establish customized constituent-specific communication strategies and outreach approaches.
The main challenge in targeting specific demographic groups is the lack of information on where these groups are located within a constituency. As a result, even in local elections, political campaigns are forced to adopt a “one size fits all” communication strategy across all demographic groups within the constituency. This broad-based voter outreach approach leads to a less informed electorate and fundamentally weakens the democratic process.
Political data analysis presents a path to address some of the communication and voter engagement challenges that lie at the heart of our democratic process. Demographic data analytics can help establish the physical distributions of diverse demographic groups in a constituency and enable more targeted outreach by campaigns to each specific group. Such targeted communications will result in more informed two-way interactions between the campaign and the constituent and, ultimately, strengthen our democracy.
Driving Democratic voter turnout in Arizona Legislative District 9
As a Bluebonnet Data Fellow, I had an opportunity to influence the development of such communication strategies when I supported the Seth Blattman + Lorena Austin Democratic campaigns for the two State House seats in Arizona’s Legislative District 9 and the Eva Burch Democratic campaign for State Senate in the same district.
A major focus of the campaigns and, by extension, the Bluebonnet team, was to find creative & effective ways to drive higher turnout of Democratic leaning voters. The campaigns identified three important demographic groups to target in this regard: Latinos, low income voters, and registered Democrats. They wanted to allocate their “get out the vote” resources, especially Spanish-speaking campaigners, for door-knocking efforts in a pinpointed fashion. However, given that this was an entirely new constituency after a recent redistricting, the campaigns did not have a complete understanding of how these demographic groups were distributed in the newly formed district.
The campaigns had also identified education levels as a key demographic consideration, but it was believed that a subset of both low and high-education voters were Democratic leaning.
Identifying the areas of concentrations for both these types of potential Democratic leaning voters would be extremely beneficial to the campaigns as they worked to increase voter turnout.
Data Analysis Process
The campaigns planned their communication strategies on a precinct by precinct basis, therefore I focused on collecting precinct-level data–sourced from the 2020 US Census and Voter File Data from the Board of Elections–for the following four demographic characteristics:
Education level- specifically % of population with Bachelor’s degrees (Census)
Race- specifically % of population that consist of voting age Latinos (Census)
Income level (Census)
Voter party registration (Voter File, Board of Elections)
I categorized each precinct in District 9 as “High,” “Medium,” or “Low” for each of the characteristics listed based on analysis of the trends within that precinct. The Voter party registration helped me identify precincts that were Democratic-leaning (> 50% of active registered Democrats) and Republican-leaning (>50% of active registered Republicans). Given the primary focus of the campaigns to drive higher turnout of active registered Democrats, the information on the party-leaning of each precinct is a critical input to be considered in planning the communication strategies.
The data analysis that I carried out validated the campaigns’ thesis about focusing a significant portion of their communications on the demographic groups identified as important. Precincts which had a higher concentration of Latino and lower income constituents were also the ones which were Democratic-leaning. The only Republican-leaning precinct which had both low education and low income levels was Palm Harbor, but that had a lower Latino population. I found that this precinct had recently become a part of District 9 after a 2020 re-organization. It is possible this precinct could become more Democrat-leaning over time as the Latino population increases.
My analysis will help the campaigns optimally plan on which Democratic-leaning precincts they need to deploy Spanish speakers for door-knocking efforts and Spanish language advertisements. At these precincts, the messaging could focus more on addressing challenges related to education and living expenses. I was able to identify Kleinmann, Heritage, and Guerrero (as shown in Figure 1) as the precincts that Spanish speaking campaigners should focus on most.
I noted that there were two precincts (Water Works and Carriage Lane) which had high median - income levels and were Democratic-leaning. I also observed that 50% of the top 10 highly educated precincts leaned Democratic. The campaigns could focus selectively more on these precincts during their outreach, but these would not require Spanish speaking campaigner involvement since they had smaller Latino populations.
One other key observation from my data analysis was that there are a significant number of registered Democrats in some precincts which are nominally more Republican friendly. The Democratic campaigns I supported would be stretched, from a resource deployment perspective, if they targeted all such precincts but the campaigns believed it was possible to opportunistically target a select few such Republican-leaning precincts with focused door-knocking efforts. I identified three precincts (Pilgrim, Dobson Ranch, Crismon) that had Republican majorities but also had a significant number of registered Democratic voters to be credibly targeted for driving higher voter turnout through targeted door-knocking (highlighted in Figure 2).
Looking to a more constituent-centered future of politics
My findings on the locations of the target demographic groups will help the campaigns employ communication strategies that are tailored to the constituents’ specific needs and aspirations. I am hopeful that such customized voter outreaches will lead to more meaningful interactions and richer discussions between the campaigns and the constituents on the issues that matter. It is highly satisfying to be a part of such constituent-centered campaigns that will strengthen our democracy at the grassroots level through greater inclusion of diverse demographic groups and historically excluded populations.
About the Author
Anirudh Mani (he/him) is a senior at Bellarmine College Preparatory in San Jose, California. He is passionate about harnessing computing and data science methods to make a difference in his community. As a Bluebonnet Data Fellow, he found a way to channel his interests in Social Computing and Data Science by immersing himself in political data campaign analytics for progressive candidates in Arizona and Minnesota.
If you like what you’ve read and want to learn more, you can reach out at info@bluebonnetdata.org. Or, If you're interested in doing similar work, apply to be a Data Fellow!