Using AI Simulation to Optimize Ad Messaging
A UX researcher used an AI-powered multi-agent simulation tool to quickly test and refine their ad messaging, instead of relying on traditional user research methods.
Why it matters
This demonstrates how AI-powered simulation can accelerate product development and user research, especially for solo founders or small teams with limited resources.
Key Points
- 1The researcher had good ads but felt the messaging wasn't resonating with the target audience
- 2They used an open-source AI simulation tool called MiroFish to generate a virtual world of agents that represent the target audience
- 3The simulation allowed the researcher to quickly test different ad messages and see how the agents interpreted and reacted to them
Details
The researcher had well-designed ads for their SaaS product Waco3.io, but felt the messaging wasn't quite hitting the mark. Instead of conducting lengthy user interviews and surveys, they used an AI-powered multi-agent simulation tool called MiroFish. MiroFish can generate a virtual world of agents based on provided documents about the target audience and context. The researcher fed in their ideal customer persona, pain points, and existing ad copy. The simulation then produced a detailed ontology mapping out the different entity types (freelancers, agencies, clients, etc.) and how they relate to each other. This allowed the researcher to see how different 'agents' in the simulated world would interpret and react to the ad messaging, without having to recruit real users. The researcher views this as a valuable UX research shortcut to quickly expose blindspots in their messaging before investing in full user studies.
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