Work

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water-chatbot

ASU Chatbot

ASU Blue Chatbot is Arizona State University's water chatbot initiative explaining all things about things water in the state of Arizona. ASU Blue is developed leveraging Open AI ChatGPT4's API.

The Challenge

Arizona's pretty dry and water's super important. But talking about water can get complicated and, let's face it, a bit boring. We needed to find a way to make all this water talk interesting and easy for everyone to get.

Figuring Out What People Need

To kick things off, I talked to a bunch of people through surveys and interviews to see what they wanted to know about water. I also made up some personas, which are like imaginary friends that help me think about what different types of users might like. Then, I mapped out their journeys to see how they'd use the chatbot and where they might get stuck.

I found out people wanted answers in different ways - some wanted quick facts, others wanted the whole story, and some just wanted to know what they could do to help or where to find more info.

Sketching and Testing Ideas

With all that info, I started sketching out what ASU Blue would look like. I added cool buttons in the chat so people could pick how they wanted their answers - short and sweet, the full scoop, steps they could take, or where to read more.

I made sure to test out my designs with users and kept tweaking things until it felt just right. The goal was to make sure it was super easy and fun to use.

Impact

The launch of ASU Blue marked a significant improvement in how water-related information was communicated to the public in Arizona. The impact of the design improvements was evident:

  1. Enhanced User Engagement: The interactive buttons and tailored responses led to higher engagement rates, with users spending more time interacting with the chatbot and exploring various topics.

  2. Increased Information Accessibility: The option to choose the type of response meant that users could access information in a format that best suited their needs, making complex topics more approachable.

  3. Positive User Feedback: Feedback from users was overwhelmingly positive, with many appreciating the ease of use and the quality of information provided.

Conclusion

By tuning into what users needed and getting creative with the solutions, we managed to turn a complex topic into something that people were excited to learn about.