Team Retrofit

Inspiration

What it does

To increase electrification retrofit rate by 1) using data from SVCE dataset to to determine household that benefits from electrification and then 2) use public record data to to determine home ownership status so targeted educational information and resources are provided, thus making the retrofit process easier and more automatic.

Online surveys use photos and visual information to help customers identify the types of appliances that they have. Survey also asks for the customer’s relationship to the house (homeowner, landlord, or tenant).

Customers are presented with different messages based on their survey responses. Messages focus on the benefits (both “hard” financial and and “soft” emotional) that customer would receive from converting to electric.

How I built it

Python to analyze customer usage data to identify customers with gas usage higher than those with comparable houses.

Survey prototype is built in Sketch, website is built in ReactJS and Material UI.

Challenges I ran into

Our initial hypothesis that electrification would lead to cost savings turned out not to be correct in most cases. This led us to pivot toward appealing to other value streams for customers, such as increasing property value or accessing larger pools of high-quality tenants.

Accomplishments that I'm proud of

What I learned

What's next for Team Retrofit

Built With

• javascript
• jupyter
• material-ui
• pandas
• python
• react
• sketch