HOW PARTIES KNOW WHO YOU WILL VOTE BEFORE EVEN YOU KNOW

Did you know that political parties can know who you are going to vote for even before you do, backed by data and scientific techniques? They can even determine your policy positions on specific issues before you are aware of those issues. Surprisingly, your everyday purchases can play a role in making these determinations.?

Credits: The Victory Lab by Sasha Issenberg . Several incidents, facts and concepts are taken from the book.

Before delving into the details, let's understand the significance for a political party in knowing who is more inclined to vote for them. Last-minute voter mobilization initiatives, also known as Get Out the Vote (GOTV) efforts, can make or break elections. These initiatives include activities such as voter registration, postal votes, and ensuring voters reach the polling booths. Failing to mobilize supporters on election day can lead to a party's defeat. Therefore, knowing which individuals are more likely to vote for a party is invaluable in effectively mobilizing them.

In the past, this was done based on conventional wisdom and past polling data. For example, it was commonly believed that minority voters in the US lean towards Democrats, while white males tend to support Republicans. Such generalizations guided resource allocation to mobilize the most favorable voters.

However, political researchers in the United States felt that this level of segmentation was not enough. They believed that segmentation should not be solely based on race or geographic areas but should be based on individual characteristics. Yes, every single individual can be segmented.

Taking inspiration from the business world, the political consulting field borrowed strategies and data analysis techniques. Consultants and marketers in the business world had already been using consumer data to derive patterns, insights, and inferences.

Alexander Gage, a US political consultant, conducted a study where he tried to match a five-million-person state voter file with consumer data from Acxiom, one of the large commercial data vendors. He found that 80 percent of Michigan voters had corresponding records in Acxiom's database, which included hundreds of variables, from marital status to pet ownership. Gage then commissioned a survey to ground those personal details in the political realities of a campaign year. He randomly selected a “test set” of five thousand households from the Acxiom records and called them with around twenty questions about the 2000 election, Michigan politicians (like outgoing governor John Engler and the various figures plotting to replace him), and issues that played a role in state politics (like abortion and the role of unions). He used algorithms to find patterns linking personal characteristics with political beliefs, enabling him to predict how the other five million voters likely approached politics.

These insights can further categorise voters into different types and issue clusters. This information can be utilised in various ways, such as adjusting candidates' positions or determining which issues should be highlighted to specific voters. An example of the effectiveness of this strategy can be seen in the 1960 US presidential elections.

During the 1960 campaign, John F. Kennedy faced a major challenge regarding his religion as a Catholic candidate in a country that had never elected a Catholic president. Richard Nixon, his opponent, was leading in the polls, and reports of anti-Catholic sentiments were becoming increasingly frequent. Kennedy’s advisers knew they had two strong options: they could ignore religious questions altogether or they could address the subject directly and condemn as bigots those who would let Kennedy’s faith affect their vote. So (the consultant) Pool ran the numbers for the Democratic National Committee. One of the issue-clusters had compiled respondents’ views when asked how they felt about having a Catholic president. (The typical question: “If your party nominated an otherwise well-qualified man for President, but he happened to be a Catholic, would you vote for him?”). Among his 480 voter-types, Pool identified nine significant subsets he thought worth measuring on the faith question, mixing and matching between three party categories (Republicans, Democrats, and Independents) and three religious ones (Protestant, Catholic, and Other). Inside was a ranking of thirty-two non-southern states in their likelihood of going for Kennedy if he directly addressed the Catholic question. Eleven states, they projected, would move away from Kennedy on religion alone, totaling 122 electoral votes. But the issue could pull six states, including three out of the four largest in the country, into the Democratic column. Together they were worth 132 electoral votes. Under these circumstances, it makes no sense to brush the religious issue under the rug. Less than three weeks after, the Democratic nominee traveled to Houston to talk about his faith before a gathering of ministers. “I believe in an America where religious intolerance will someday end,” Kennedy said, “where there is no Catholic vote, no anti-Catholic vote, no bloc voting of any kind.”

Couldn't help but notice the irony. There are a number of similar instances. Needless to say, the reliance on data analysis and algorithms introduces the possibility of inherent biases in the models or the data used, which could result in unfair or inaccurate predictions. But it is still vastly superior to previous models.

In today's digital age, targeted messaging can be easily tailored to different voter segments. While targeted communication based on demographic variables like gender, age, and community is common in Indian politics, segmentation based on voters' consumer decisions and individual characteristics is yet to be fully developed. The lack of organised consumer data could be one hindrance on that regard.

As like any powerful tool, this is both fascinating and concerning. While it could help parties help their supporters to vote thereby aiding in democratic process , it could also lead to issues like targeted voter suppression (violence, fear..). And needless to say, it could further exasperate the lack of level playing field among contestants and become a matter of who has more resources as different from who is the best for the voters. If parties solely focus on targeting specific segments of the population, there is a risk of neglecting the concerns and interests of other groups.

What do you think about it? Do you think it is a indication of a advanced democracy or a threat that needs to be managed cautiously? Comment your views.

#politics #indianpolitics #politicalconsulting #policy #uspolitics #targeting