| Hi HN, we’ve recently sold our previous product and are currently building on new ideas. This one may be the most exciting and overlooked growth opportunity for AI products we’ve found: 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) |