Cent – Earn ETH by answering questions

Hacker News

Hey HN! Today my cofounder Max and I are launching the beta version of Cent — a question-and-answer service that allows answerers to make money, and curious individuals with a need for knowledge a way to get quick answers on anything that comes to mind. When a user asks a question on Cent, they place an ETH bounty on the question as well. The higher the bounty, the more the network is incentivized to answer you clearly and concisely, providing you more valuable information for your inquiry due to the additional monetary incentive. Users then vote on which answer(s) they determine to be deserving of the bounty and then the funds are distributed to the users who wrote the best answers. Our eventual goal is to create several mechanisms for people to earn money remotely, but this is our first major feature, and we wanted to gather as many useful comments and feedback as possible. Would love to hear any feedback from you all! Our site is https://cent.co and the direct link to the beta is https://beta.cent.co

Visit product View on Hacker NewsAug 15, 2017

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Product HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: answers, users, way · Missing: mobile apps, ios, personal

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: lua, io · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% 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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