Nirviral Easter Egg Hunt #1

Hacker News

Nirviral Easter Egg Hunt #1 Nirviral is a newborn site. It is a link-sharing site much like Reddit and Hacker News. We are undergoing a massive scaling problem and we believe that having an easter egg hunt would help our website scale. There are 10 easter eggs on the site. There are 3 easter eggs in particular that we are looking forward you the hunters to find. If any of you locate the one of the 3 major easter eggs you will have the honor of winning a 15 dollars amazon gift card. We understand that this is really small of a gift card, but we plan to increase the numbers higher in the future. Places you may want to look are as follows: Source page, about page, comment section, posting page. Here is the link for the website: http://www.nirviral.com/ If you think you have found one of the major 3 easter eggs then please shoot an email to nirviral@gmail.com. Happy Hunting!

Visit product View on Hacker NewsJul 20, 2014

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2comments

Did not reach leaderboard

Launch Intel predictions

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

82%82% 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.

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

64%64% 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 HuntOn track for Day 1 leaderboard · Strong signals: new, email · Missing: mac, agents, macos

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

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

39%39% 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

33%33% 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

12%12% 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.

Incorrect prediction on native model

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