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Zigg.be – A link shortener that creates short speakable links

Hacker News

Zigg.be – A link shortener that creates short speakable links

I created this a year or so ago but recently made updates and I thought people might like to know that it exists. I made this to easily send links or text to someone else verbally, like over the phone or over voice chat (which is what I made it for). The goal is to be able to tell the link to someone else without being ambiguous or needing to spell it out, so I grabbed the words off a Grade 5 level dictionary. I understand that the domain itself doesn’t qualify but I’m trying to get a better domain.

Visit product View on Hacker NewsJan 24, 2013

Actual performance

75points

48comments

Made the leaderboard

Launch Intel predictions

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

74%74% 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.

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

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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

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

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

42%42% 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

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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