I have scaled multiple projects and each one had entirely different ways it was scaled. One offered LTD, other got featured in newsletter, one got users from hacker news and other got it from product hunt. So, an AI copilot to stress test ideas based upon competitor's growth performances. Roast, validate, give feedback, anything is good.
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To develop an AI product distribution platform that advises on acquiring the first 100 users, it's essential to analyze successful growth strategies of similar products. You can leverage data from platforms like Product Hunt, Hacker News, and industry-specific newsletters to identify effective user acquisition channels. An AI copilot can be trained on this data to provide insights on the most suitable distribution channels for a given product. Additionally, the platform can offer features like competitor analysis, growth strategy simulation, and feedback mechanisms to help refine the product's go-to-market strategy.
Key Takeaways
Analyze successful growth strategies of similar products
Leverage data from platforms like Product Hunt and Hacker News
Train AI copilot on historical data to provide insights on user acquisition channels
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