iCal RSVP Helper

Hacker News

iCal RSVP Helper

Hi HN, We use HEY for Work at my startup, which doesn't have a calendar integration. This is mostly fine, as we can simply use our private calendars, but has a major drawback: We can't reply to invitations in an easy way. I made this microsite to help with this problem until they implement simple Yes/No/Tentative buttons in HEY. It's fully client-side, and gives you the ICS-file you need to attach in an email, and the correct address it needs to be sent to as well - just select your file and RSVP. Hope it's useful for someone else too!

Visit product View on Hacker NewsMay 24, 2023

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

60%60% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

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

43%43% 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

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

nativeThis product was originally launched on this platform.

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

43%43% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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