This project analyzes participant evaluation data from a Crisis Intervention Training (CIT) program to assess perceived effectiveness and identify actionable opportunities for improvement. The primary objective is to transform both quantitative ratings and qualitative feedback into meaningful insights that can inform program enhancements and support data-driven decision-making. Using cleaned and standardized survey data, this analysis focuses on participant-reported interest levels as a key indicator of engagement and perceived value. Quantitative measures—including frequency distributions, averages, and comparative breakdowns—are used to evaluate overall program performance, as well as differences in perception across agencies and units. These insights help identify which groups find the training most and least impactful. In addition to numerical analysis, qualitative participant commentary is examined to uncover recurring themes related to program strengths, areas for improvement, and overall participant experience. This mixed-methods approach ensures a more comprehensive understanding of training effectiveness beyond numeric scores alone. The analysis is conducted in R, leveraging packages such as dplyr, ggplot2, and plotly to produce interactive and reproducible visualizations. Results are presented through dynamic charts and summaries that allow stakeholders to explore patterns in engagement and perception across multiple dimensions. Ultimately, this project aims to answer the central question: What do participant evaluations reveal about the effectiveness of the CIT program, and what data-driven actions can be taken to improve it? The findings are intended to support continuous improvement efforts and enhance the overall impact of crisis intervention training initiatives.