Using natural language to provide personalized weather information that is easily actionable and reaches people on a multitude of platforms.
The interview with WTOC helped us understand how to build trust when talking about something as serious as a natural disaster. The insights from this interview helped develop the language in which we speak to our users.
Our 60 intercept interviews were key during this project. Almost every person we interviewed mentioned that they watched the weather forecast or found out about past hurricanes through social media. This is how they were able to make the decision on whether or not to evacuate.
"I don't know how this forecast applies to me."
- Christy, Memphis, TN
The general public is subject to confusing, misleading and ambiguous information. This leads to mistrust and negatively affected decisions.
We hit a lot of walls with our initial ideation and we ended up with a product that was completely different than what we had originally planned. After going through a lot of different concepts we were able to combine what we had learned from our failed concepts to create a service that was clear, helpful to the user, and we felt would make a difference when dealing with natural disasters.
The majority of our design process was creating a language that was both friendly and also developed trust. We want the user to know that what we are telling them is accurate and personalized to them.
DAWN's weather forecast web application is personalized to the user and their specific location. When a hurricane forms, DAWN assesses the user's location and the track of the storm, and continues to send updates to keep the user informed and prepared.
- Helping with evacuation - ride sharing, checklists, suggestions
- Building trust with the user
- Natural, friendly language
- Cross platform delivery - test, push notification, VUI devices
- Community page for verified news and community input
- Understandable weather visualization
- Making sure the user is accurately informed