Save your words online forever - Wrytten

Hacker News

Hi guys, Built in a few weeks Wrytten.com. In simple it’s a way to save your words forever on the internet using the blockchain. It’s not that complicated to do it yourself if you know crypto and hold your own keys but I wanted to make this for non crypto users as most people don’t want to hold crypto or learn and it’s a paid service. I threw some ads up and showed to a few thousand people and so far no interest at all. Appreciate any feedback from your end. If you would like to try it , message me on the site and I’ll give a full trial for no money. Really trying to figure out what’s wrong with the pitch, service, idea, etc

Visit product View on Hacker NewsMar 25, 2024

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Actual performance

3points

8comments

Did not reach leaderboard

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

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best fitHighest predicted score across all platforms for this description.

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

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, using · Missing: mac, agents, macos

40%40% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto, paid · Missing: web3, chat, 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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