TLDR: We’ve built a tool for analyzing and exploring user prompts — so you can actually understand how users are interacting with your AI product, and compare behavior across different segments (languages, paid vs free, etc).
If you’re used to Mixpanel / Amplitude / PostHog to analyze user behavior, you could notice how irrelevant they become when your product is just a chat box (or voice interface). That's because in the age of AI you don’t need button events — you need to analyze a large corpus of text.
To solve this, we’ve built what we call a Mixpanel for GenAI apps — an NLP tool to analyze and explore your user chats at scale.
We can already do:
1/ Multi-layer semantic clustering (see a big picture of all the topics and drill down)
2/ Filters and groups (compare usage between languages, demography, free/paid, etc)
3/ Latent space exploration
4/ Semantic search of prompts
5/ Topics and token usage breakdown
6/ (coming) Trends and audience drift over time
So you can answer questions such as:
- What’s the main use case of my app?
- What do users who pay the most do?
- What do users who spend the most time do?
- Which quiet audiences and use cases am I missing?
- How do the user patterns differ between languages?
- What are the new audiences we can appeal to?
Please check the link for the screenshots and instructions on how to start! Any feedback is appreciated (I don't say I won't cry if it's negative)
