No code page builder for Web3

Hacker News

Hey HN, I'm Gokhan, co-founder at Stubs (https://stubs.world/signup). We just opened Stubs for beta and wanted to bring it to the HN community for feedback. With Stubs, you can create NFTs, write decentralized blogs, deploy DAOs, digitize your Shopify storefronts, and more. All in minutes. All no-code. Our goal is to allow users to reap the benefits of Web (super easy content monetization) without worrying about wallets, keys, and code. We have an intuitive, drag and drop UI builder that we worked on very hard to make as easy to use as possible. You can join the private beta today at stubs.world/join with the invite code STUBSHN. Super excited to hear your thoughts, our team will be monitoring here the entire day today to answer any questions :)

Visit product View on Hacker NewsJun 14, 2023

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Did not reach leaderboard

Launch Intel predictions

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

82%82% 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.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: intuitive, builder, users · Missing: plus, platform, reviews

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: shopify · 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: web3 · Missing: chat, crypto, cryptocurrency

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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