Customer Feedback Categorization Project

Customer Feedback Categorization Project Customer Feedback Categorization Project Jul 2025 - PresentJul 2025 - Present Company logo Associated with iFIT Associated with iFIT

Performed AI prompt engineering to refine model outputs and optimize categorization performance, directly improving accuracy and consistency to near 100%.

Worked with SQL in Snowflake to access, query, and analyze feedback datasets integrated with Tableau dashboards.

Validated rows of AI-categorized customer feedback by manually reviewing and comparing labels, producing an accuracy percentage score for performance benchmarking.

Provided recommendations and corrections to improve the AI categorizer’s labeling quality, enhancing the reliability of customer sentiment reporting.

Supported the project goal of refining automated feedback analysis workflows, helping stakeholders gain more accurate and actionable insights.

Performed AI prompt engineering to refine model outputs and optimize categorization performance, directly improving accuracy and consistency to near 100%. - Worked with SQL in Snowflake to access, query, and analyze feedback datasets integrated with Tableau dashboards. - Validated rows of AI-categorized customer feedback by manually reviewing and comparing labels, producing an accuracy percentage score for performance benchmarking. - Provided recommendations and corrections to improve the AI categorizer’s labeling quality, enhancing the reliability of customer sentiment reporting. - Supported the project goal of refining automated feedback analysis workflows, helping stakeholders gain more accurate and actionable insights. Skills: SQL · Snowflake · Artificial Intelligence (AI) · Ai Categorization · Data Validation · Prompt Engineering