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I made a website that lets YouTubers make money from fan questions

Hacker News

I made a website that lets YouTubers make money from fan questions

Just wanted to share with you something I built. If you’re a creator or someone who financially supports creators, this will be of interest to you. Qufro.com is a site where creators can monetise their fan interactions. It works this way: A creator sets an amount for answering fan questions. A fan posts a question or a comment and is only charged if the creator responds. From the fan’s perspective, we’re solving the following problem: Not all fans want to commit to a monthly subscription (e.g., on Patreon) to support their favourite creators. With Patreon, ko-fi, etc., there is also no guarantee that the creator will ever personally interact with you. From the creator’s perspective, we’re solving this: There are only so many people willing to subscribe on Patreon, but there’s a lot more people willing to provide one-off monetary support. Moreover, since engaging with fans is key to building a loyal audience, we combine fan interaction with payments so that creators can make some extra income. Thanks for your feedback!

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Strong signals: personal, month, monthly · Missing: mobile apps, ios, entrepreneurs
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: make money · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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