Project Overview
As part of my work with Minivillage, a social purpose tech startup, I conducted a comprehensive analysis of their beginning-of-pilot survey. This survey aimed to capture user feedback and insights early in the project, laying the foundation for understanding user needs and informing future decisions. The focus was on examining user responses to gauge their initial experiences and expectations with the platform.
Project Impact
This analysis was crucial in shaping the direction of the Minivillage pilot, as it offered actionable insights based on real user feedback. By focusing on the beginning-of-pilot survey, I helped Minivillage understand user expectations from the outset, setting the stage for an informed, user-centric development strategy moving forward.
Tools and Techniques
To perform this analysis, I leveraged data analysis tools and techniques, including:
- Data Cleaning and Processing: Ensured data accuracy and consistency by handling missing values, normalizing responses, and structuring data for efficient analysis.
- Statistical Analysis: Applied various statistical methods to quantify user feedback, identify key trends, and measure satisfaction levels, providing a robust foundation for data-driven insights.
- Machine Learning & NLP: Leveraged machine learning techniques, including natural language processing (NLP), to analyze open-ended responses and extract meaningful patterns from text data.
- API Integration: Integrated the Eden AI API to streamline and enhance data processing, automating complex tasks and increasing analytical accuracy.
- Data Visualization: Developed clear, impactful visualizations to communicate trends and insights, enabling stakeholders to quickly interpret the findings and make informed decisions.
This project underscores my ability to analyze survey data and provide actionable insights, helping organizations align their offerings with user needs and improve overall satisfaction.