Predictive Analytics in Non-Profit Organizations: Applications, Models, and Strategic Implications
Author: Dr. Anna Neya Kazanskaia
Publisher: NEYA Global Publishing
Article | NEYA Global Journal of Non-Profit Studies
Year: 2025
ORCID: https://orcid.org/0009-0009-5669-1676
DOI: https://doi.org/10.64357/neya-gjnps-adv-dt-an-03
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About the Article
Predictive analytics has become a critical tool for non-profit organizations striving to maximize impact while operating under resource constraints. This article examines core predictive methods—including regression analysis, time series forecasting, classification, and clustering—and evaluates their practical applications in donor management, volunteer coordination, fundraising, and program allocation. Case studies illustrate measurable improvements such as reduced donor attrition, optimized resource distribution, and increased volunteer retention. The discussion highlights challenges including data quality, financial limitations, and skill gaps, and outlines strategies for adoption through pilot projects, open-source tools, and interdisciplinary collaboration. By embedding predictive models into strategic and operational processes, non-profits can strengthen accountability, enhance efficiency, and expand the reach of sustainable social impact.
Key Topics
- Predictive analytics in non-profit organizations
- Regression analysis and time series forecasting
- Classification and clustering techniques
- Donor retention and volunteer management
- Resource allocation optimization
- Strategic applications and governance challenges
Suggested Citation
Kazanskaia, A. N. (2025). Predictive Analytics in Non-Profit Organizations: Applications, Models, and Strategic Implications. NEYA Global Journal of Non-Profit Studies. Neya Global Publishing. https://doi.org/10.64357/neya-gjnps-adv-dt-an-03
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