Transforming an idea and hypothesis into a testable MVP
We started with the question - Can AI help provide more transparency into voter sentiment?
MY ROLE:
- Head of Product
- co-founder
hypothesis
AI can provide unique insights into voters that existing methods of research don’t capture.
What we learned from organizations
Key topics
Organizations were interested in key topics and narratives specific to their audience. Things like abortion or voter fraud.
Limited resources
No one had the time or resources to digest complex reports. Customers needed just the most relevant information on key topics.
Ai, but not chat
When most people think of an AI product, they immediately think of something like ChatGPT or Gemini. Both require you to know what questions to ask, rather than presenting you with the information we know you need.
Just the metrics you need about the topics you care about
a powerful tool with limited novel insights
After building an MVP, and testing our hypotheses, we found we weren’t able to uncover meaningful insights that organizations weren’t already aware of through other sources. We concluded that this was a result of two things:
1 - The current state of online conversation is flooded with misinformation and fake accounts. AI in its current form struggled to differentiate signal from noise.
2 - The insights we were able to uncover weren't different from what more traditional methods were able to glean.
See other work
- 01
- 02
- 03
Let's talk
Interested in working together? Have a question? Drop me a note.