Political parties are increasingly using data science and analytics to make better decisions. This case study focuses on the Bharatiya Janata Party (BJP) and how they have effectively implemented data analytics and data science in their decision-making process.
The BJP's organizational structure is similar to a corporate hierarchy, with party workers at the bottom and the national president at the top. This structure allows for the infusion of new faces and ideas, as the party presidents change every 4 to 5 years.
The BJP collects data from various sources, including party workers, primary members, and consulting firms. This data is used to classify voters into different categories, such as core voters, undecided voters, and opposition voters. The party then uses targeted marketing strategies to reach out to different voter segments.
The BJP uses sentiment analysis to understand the sentiments, challenges, and needs of its workers and voters. This information is then used to make informed decisions about organizational changes, candidate selection, and even changing sitting chief ministers.
The BJP has utilized AI technology called deepfakes during the 2020 Delhi election. Deepfake videos use AI to modify people's faces, allowing political leaders to communicate in different languages and regions. This personalized approach resonated with voters, as they felt the leaders were speaking directly to them.
The BJP's successful implementation of data analytics and data science has been instrumental in their year-on-year success. Other political parties have also started adopting these technologies to improve their campaigns and connect with voters. The use of data science and data analytics has revolutionized the way political parties approach elections.