Proceedings of the International scientific and practical conference ―Oxford International Science Forum‖ (April 17-19, 2026) / Publisher website: www.naukainfo.com. - Oxford, United Kingdom, 2026. - 367 p.

108 multimodal feature fusion, and development of interpretable models for early-stage campaign evaluation. Another promising direction is the integration of LLMs for advanced narrative analysis, recommendation generation, and semantic profiling of campaigns. Furthermore, further research should focus on anomaly detection, trust assessment, and platform-specific benchmarking to enhance the reliability and practical applicability of crowdfunding data analysis tools. Conclusion . This article provides an overview of crowdfunding data analytics tools in terms of data nature, classification, collection challenges, analytical insights, and methodological support. Crowdfunding data is shown to be a heterogeneous analytical entity that combines structured and unstructured representations of campaign activity. The review demonstrates that the main obstacles to high-quality crowdfunding analytics are limited data access, platform heterogeneity, multimodality, incomplete datasets, and ethical and legal constraints. These factors explain why one-size-fits-all analytical approaches are often insufficient without platform-specific harmonization. The article also systematizes the main insights that can be drawn from crowdfunding data, including success factors, early-stage forecasting, temporal funding patterns, narrative effects, campaign typologies, and anomaly indicators. Relevant analytical methods include descriptive statistics, machine learning, text analytics, clustering, time series analysis, anomaly detection, and explanatory artificial intelligence. In general, crowdfunding data mining should be understood as an integrated analytical discipline that combines heterogeneous data processing, predictive modeling, semantic interpretation, and decision support for various participants in digital fundraising ecosystems. REFERENCES: 1. Mollick, E. (2014). The dynamics of crowdfunding: An exploratory study. Journal of Business Venturing, 29(1), 1–16. DOI: