Data analytics enhance library’s fundraising efforts | Lifestyles
The New Castle Public Library is proud to announce significant advancements in its fundraising strategies through the use of sophisticated data analysis techniques.
This initiative was made possible through Rutgers University’s Master of Business Science (MBS) Externship Exchange Program, which ran from January to April, and enabled the library to better understand donation patterns and predict future fundraising outcomes.
Through a comprehensive exploration of donor retention and campaign performance data, students Janki Patel and Dev Shah identified key trends crucial for optimizing fundraising efforts. Mentored by NCPL Development Manager Carissa Neary, the team was charged with guiding the NCPL through optimizing fundraising campaign timing and location for exponential donation growth while maintaining current donor retention rates.
Utilizing the R programming language and advanced data modeling, including time-series analysis and the Gradient Boosting Machine model, Janki and Dev forecast the donation amounts for the calendar year of 2025. These models considered various factors such as month and day of the month, which significantly influence donation trends.
“Our data-driven approach has allowed us to strategically plan our campaigns and engage with our community more effectively,” said Andrew Henley, library director. “We are excited about the potential of these tools to further our mission and enhance the services we provide to our patrons.”
The predictive models developed by Janki and Dev indicate the library can expect heightened donation activity during specific periods aligning with historical peaks in donor generosity. This insight allows the library to tailor its outreach and engagement strategies to maximize potential donations.
The New Castle Public Library remains committed to leveraging technology and data to improve its operations and better serve the community. The insights gained from this project will guide future fundraising.
