We were inspired by this project because it combined social impact, data, and technical problem-solving. We started by learning how SVP operates today, identifying gaps in impact measurement and communication.
Our main challenge was designing a system that delivers meaningful insights while remaining simple to use. Using surveys, Python, and machine learning, we built a tool that analyzes both quantitative and qualitative grantee feedback, turning it into clear, visual data that reflects the real impact SVP is creating.
Another key challenge was participation. How do we motivate grantees to engage with the system? To address this, we designed a model that uses a VIP alumni network as an incentive, encouraging long-term involvement and community connection.
We’re proud of how intuitive and scalable the final product is, and of balancing powerful analysis with ease of use. Next, we plan to launch outreach by sending surveys via email, building the VIP alumni network, and beginning to collect the data needed to measure and improve impact over time.
Built With
- excel
- google-docs
- google-sheets
- html
- matplotlib
- python
- scikitlearn
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