Project Overview

AI Chatbot Performance & Data Analysis

This project analyzes testing data from an AI chatbot to identify performance trends, defect patterns, and quality metrics. Raw test execution results were transformed into structured reports to support data-driven decisions on chatbot reliability and performance.

Project Structure

Data Collection (Test Plan & Scenarios)

• AI_Chatbot_Test_Plan.docx
• AI_Chatbot_Test_Scenarios.docx

Raw Data (Test Cases & Execution Results)

• AI_Chatbot_Test_Cases.docx
• AI_Chatbot_Test_Execution_Report.docx

Issue/Defect Analysis

• AI_Chatbot_Defect_Report.docx

Insights & Summary Reporting

• AI_Chatbot_Test_Summary_Report.docx

Key Analysis Areas

• Pass/fail rate trends across test cycles
• Defect frequency and severity distribution
• Root cause categorization of failures
• Performance metrics summarized into actionable insights

Skills Demonstrated

Data collection, structured reporting, trend analysis, defect pattern analysis, data-driven summary reporting